April 16, 2011

Solve the Right Problem

Posted by Malcolm Ryder at 1:02 PM

October 24, 2010

Social Knowledge versus Business Networking

More and more businesses are assertively working on using "social networks" to try to move the business operations to a more "advanced", and at least more agile, stance.

We would say that "Social Networks" are something whose time has come. And this would be true due in no small part to the acceptance that business really does run fundamentally in and on an "Information Economy" -- with social networks being a dazzling opportunity to easily generate and acquire information heretofore untapped or even orphaned in time and place. In short, what is sought is an infusion of Social Knowledge into Business Networking, and "social network" actually becomes a handy abbreviation.

No wonder that the phrase "Social Network" has special meaning to a large business.

But in reality, businesses have a funny way of not worrying about the "special meaning" of something, and instead grasping and acting on the "convenient use" of something. Convenience is sometimes pleasant but often unruly, which, in business lingo, probably means counter-productive.

If everyone keeps their head on straight, then there will be agreement that "a Network becomes a Medium for Communication of Information that may be Shared in the Production or Distribution of Knowledge"... With all the capitalized moving parts in that description, a few questions arise. For example: did the business actually "capitalize" (i.e., fund) all the parts (on its own or through partners)? Is the "connectivity" of the Network to the Production or Distribution being managed? What if anything is being done to transform Communication coincidences or Information coincidences into Shares? And does the business acknowledge that each moving part already carries a legacy of "administration" that is different from the other parts? Does it acknowledge that applying a "social" aspect to any of the parts requires both control and flexibility (i.e., policy)?

In the last four companies I've worked at (present included), none has actually licked the problem because the effort to cover these bases is huge and in fact there has been no "chief knowledge officer" to lead and enforce what is really necessary to make these parts work together properly and sustainably: namely, Engineering!

Let's face it, the "culture" of social networking is emotionally averse to the idea of environmental engineering, because the culture is about finding the magic in organic evolution, and it thinks that engineering will work against it. This aversion results in having the sense that crafty opportunism, packaged as "innovation", "grass roots" and "collaboration" should be the strategy for growing the environment we want to call the Social Network. The problem is, of course, that making a Social Network into an actual Business Environment is the only way that a social network can be both valuably and practically leveraged by or integrated with a larger, legitimate, managed business environment. The goal of that would be to eliminate the most predominant problems of business (not workforce) adoption of social networks:
- information mistaken for knowledge
- expensive and unvetted redundancy both within and across different information and communications systems
- unreliable completeness of collections and conversations
- unaligned value judgments amongst frequent users vs. occasional users
- and unaligned value judgments among managers of the business vs. non-managers.

Posted by Malcolm Ryder at 11:19 AM | Comments (0) | TrackBack

May 30, 2010

How IT Strategy and Business Strategy Co-Operate

What is the relationship between business strategy and IT strategy?

IT strategy must be seen not as a monolithic pronouncement but instead as a continual practice with which use of information technology is tailored to the business use of information.

Business use of information falls into many separate but inter-operable domains including (but not limited to) communications, learning, analytics, research, and history -- along with production, and then of course, process management.

When we say "business strategy", the assumption is that there is a type of influence that the business seeks to have on its community of stakeholders and in its operating environment. This is an influence that depends on a position that the business can establish for itself, relative to other functional or operational entities that are either contiguous or party to the community and environment. The strategy is made up of the intent and plan to take the position for the purpose.

The use of information corresponds to the strategy, but -- not all information usage is about the strategy, except in the sense that it needs to either allow or cause the strategy to succeed. This means that the usage itself needs to succeed given the particular method of usage and the actual information itself.

IT strategy must concern itself with what methods can be combined with what kind of information, to provide the opportunity that the business strategy needs, by creating effects that are either preconditions or causes of the opportunity.

Accordingly, for IT strategy to make sense, first the opportunity needed by the business strategy must be identified, and then the type of information usage needed for the opportunity must be enabled by IT.

This requires understanding how the different information usages will co-operate to create conditions that will add up to the opportunity.

Some of those combinations are intuitively appealing because they are part of proven past efforts.

• Communications, Production - selectively informing participants and stakeholders to establish efficiencies and quality in work
• Research, Analytics -- diligent search/discovery/arrangement of data, patterns and models that are useful for making and explaining things
• History, Learning -- compiling descriptions and interpretations of experience that clarify contexts and relationships

Bottom to top, those pairings usually allow the business to identify functions, design ways to conduct them, and generate specific operational capabilities from the designs. Obviously, relevant capabilities are an essential type of "opportunity". Drawing learning from history, or drawing analytics from research, and so forth, are typical interactions, and the effects of one pair are commonly leveraged by the pair above it. 

At the same time,  there is no guarantee that accomplishments in one area will flow up into others. Even where certain lineups are compelling, it is necessary to look into how a network of influences can arise in non-linear fashion amongst the full set of usages. These influences can be inhibitors as well as promoters.

For example: history can predispose analytics, by culturally reinforcing attention to some issues and neglect of others. Meanwhile, learning can predispose communications, by preselecting audiences. And production may impact research, whenever they compete for resources or persuasiveness.

Along with new capabilities, most business strategies can think in terms of ideas (knowledge), relationships and assets when exploring the types of opportunities that may be needed. Usually, in a mature business organization, these are all enjoying focused management The question is, for each type of opportunity, what should IT do to enable and orchestrate the six or more basic information usages required for creating and maintaining it?

The touchpoint between business strategy and IT strategy is those usages. In practice, the business strategist must determine which certain opportunities should be pursued. The IT strategist must identify, engage and evolve the related touchpoints so that their interactions are balanced towards providing the opportunities that the business strategy needs.

 

 

Posted by Malcolm Ryder at 1:00 PM

May 23, 2010

The Seven Ways that People Don't Listen

We know that strategy is essentially a proposal. All strategy says, "Let's try it this way..." -- or it says nothing at all.

But one of the most understated things about strategy is that it is more a response than it is anything else. The value of a strategy is not primarily in the impact that it ultimately has. Instead, a strategy takes its basic value from the problem that it wants to solve. In most instances, if the problem is very important, then the strategy that responds to it will be important.

However, what many people, including practitioners, fail to attend to is that a strategy's being important does not cause the strategy to be a good one, nor does it prevent the strategy from being a bad one.

That fact is why the quality of the strategy must have high priority, and why making strategy must prevail over the culture of execution. In too many cases, practitioners trip over another conceptual stumbling block, which is that execution does not make an important strategy good. Instead, a good strategy enables execution to be effective.

The most prominent dimensions of a good strategy are the following:
- Relevance
- Logic
- Credibility
- Visibility
- Urgency
- Distinction
- Change

What practitioners may discover, to varying degrees of surprise, is that the list above is a good predicter of whether execution is likely to result in effective outcomes. Even more importantly, they may discover the reasons why an existing strategy may be unusable or failing. In general, any point in the list makes sense only if the point preceding it is in good stead.

The overall single reason why a strategy may be structurally predisposed to fail is that the chain of dependencies inherent in the above list can be broken at any point by a failure of stakeholders to "buy in" at that point. What is even more surprising to presenters of strategies is that such "buy in" failures are not due nearly so often to rejection as they are to indifference.

The cult of execution holds that indifference can be pushed out of the equation by performance incentives. This poses the situation that a key participant need not worry about why assignments matter if they are well rewarded for being carried out successfully. These "rewarding" outputs are then advertised as "priorities", and managers are deployed to enforce priorities and to maintain a balance of their alignment amongst the complexity of their concurrent demands. This is exactly why metrics dominate management. Management then tends towards the idea of "best practices" -- the patterns associated with manageable high performance. But this is fundamentally different from strategy.

Let's turn back to the essentials of strategy and look at how indifference first appears. The most important notes to make are about why people decide to not buy in -- which takes place mainly by their choosing to not listen. As opposed to merely hearing, listening requires that the person absorb, interpret and represent the offered idea in their own mind. This is not the same thing as acceptance; instead it is the same as "realization", which for that person allows the idea to become the basis of their follow-on action. Otherwise the strategy remains an external fiction: someone else's story. In noting this, we also have to remember that typically, with strategy, exposure is not a universal experience. Different people need to listen at one or more different points in the chain of dependency:

- Relevance: how do we know that the problem being tackled is the right one? This may start out with identifying what the problem is really pointing at -- namely, a need. The primary needs are innovation (evolution), preservation (growth and health), and recovery (healing).

- Logic: what plausible mechanism is readily apparent to address the need given the most plausible disruptive risks or inhibitors to that mechanism?

- Credibility: who is the source, and presenter, of the case for the need and the logic? What is the agenda of that source?

- Visibility: what modes of validation-on-demand are available for the participants approached with the presumed relevance, logic and credibility?

- Urgency: why is the opportunity for the presumably required effort (not the desired outcome) more available now than it is later?

- Distinction: what is it about doing this with the designated parties that makes the effort as likely to succeed as competing strategies?

- Change: how do I know I will wind up better off than I am now?

Experience shows that strategies are often undermined or aborted due to such things as competing ideas, turf wars, and under-resourcing. That is, that actual design of operations indicated by the strategy cannot be fully completed, communicated, and subscribed. This general picture of resistance or disconnect suggests the scope of challenges to any strategy. But the picture should be much more specific; and again the matter is not so much one of rejection as it is a failure of the strategy's proposition to overcome the inertia of the present.

Given the specific dimensions listed above, here are the associated ways that people are predisposed to not listen. The idea that a strategy has high quality is all about the way that the strategy predictively addresses these issues:

- Relevance: not aware of this need's primacy over other possible or identifiable needs
- Logic: don't understand the mechanism
- Credibility: lack of trust
- Visibility: limitation of information access
- Urgency: risk to current commitments
- Distinction: appearance of being excluded
- Change: fear of loss

Given those issues, it is apparent that the most important things to materialize for substantiating the strategy at the participant level are models, education and proof -- none of which are the domain or responsibility of execution.

Without end-to-end substantiation, the interdependencies within the proposed strategy are not integrated, and this in turn means that the organization available to execute the strategy is either missing, logically misaligned or inherently deficient -- in other words, the engineering of the strategy is suffering from classic flaws of omission, errors or defects.

The pressure on managers and executives to deliver "performance" can often provoke them to "re-organize" somewhat ruthlessly as a way to "enable" a strategy. This is not uncommon as a business practice, and none of the above argument is intended to claim that it should or should not be done. Instead, the takeaway from the above is more importantly an awareness that aggressive management is not a substitute for actual strategy, and that the purpose of strategy is to create a basis for effectiveness, not to to create results.

Strategy designs operations; execution conducts them. As a further caution, it must be pointed out as well, though, that strategy is not static; as it is fundamentally responsive and is a design discipline, strategy must be dynamic and itself must be managed for real-time quality -- an ongoing process, not just a product.

Posted by Malcolm Ryder at 9:20 AM | Comments (0) | TrackBack

September 28, 2009

KM Unplugged

Well into the 21st century, knowledge management still circulates around many neighborhoods looking for a definition. With a definition, it could get grounded in a budget and, taking root, actually grow into a support system of record in the enterprise. It could get a job.

Or that's the script, anyway. Notable exceptions include sites where it has already taken root, sites where it is not debated and is actually planned for implementation, and sites where it is just a cultural reality not needing additional formal justification. But even if all of those sites made up half of the places that use the term KM, the other half are places where KM is still either unconvincing or on the loose. What needs to happen at these places? 

Let's approach the challenge like this. ask the question(s), "how do you know if you are managing knowledge?"

Of course, that is really two questions: how do you know if you're managing, and how do you know that it is knowledge that you are managing?

For the most part, knowledge is a "resource" and management is a practice that pursues the efficient and effective application of a resource to operational performance requirements. But let's be far more specific.

As for distinguishing knowledge from other resources, we like the value-chain model that shows data becoming information through modeling, and information becoming knowledge through practical utilitarian relevance to a context or presumed circumstance.

In effect, knowledge is a status, not a material -- very much similar to "health". This helps to identify what is at stake when managing it, as well as suggesting what kind of risks accompany neglecting it.

We know that under pressure, healthy bodies can do more than less healthy ones, and/or that it will take more out of a less healthy body to do the same thing that a healthy one does.

This throws the light on the matter that the skeptical half need: the big problem of not doing knowledge management is the opportunity costs that result. For an organization that presumes to compete and win based on advantages, understanding knowledge management is a no brainer.

Posted by Malcolm Ryder at 7:47 PM

September 1, 2009

The Media Middle

Many writers of many ilks ask the question of "where" we will be going with the new social networking tools including Facebook, Twitter and the like. It makes for fun reading, with science on one end of the spectrum and fantasy on the other. Chances are that the differences in their predictions have more to do with which writers are getting paid, which have someone's attention already, and which are seeking attention or pay versus which could care less. It might be that the most reliable statements are the ones that fall into the "notes to myself" group because they are relatively unadorned or unfettered -- whether they later prove to be right or wrong. They will be the breadcrumbs on the thinking trails that can be reviewed later and learned from, as evidence of what helps analyses succeed. But, there is this problem of whether there are too many useless crumbs with no one coming by to sweep them up. On that note, welcome to the web.

And still, below, my notes to myself.

As these social networking instruments continue to power up the breadth of opportunity for participants in the "read/write web", it becomes more evident that vast social experimentation with communications will fall into a relatively few categories of general importance.

Each of these categories will be an arena where we will see development (planned change) and evolution (adopted adaptation), and eventually we will see certain types of relationships developed and evolved between the categories as well. The categories are content, community, and channels, in the midst of which sits a media user.

 

Content

Self-publishing is the primary driver in this category, with multi-media presentation being the most compelling target. Technicians point to "rich media" on the developer side, but this is essentially about bringing portability, seamlessness and streaming to presentations. On the evolution side, the goal is convenient compilation and tagging as a way of dynamically organizing and discovering special interests. 

In fact, discovery is the key link from here to the next category.

Communities

This area is driven mostly by communications dedicated to representing and validating common interests. On the development side, discovery tools are premium; and on the evolution side, sharing is the top priority, which as a result also makes access privileges and property rights a key issue to decide.  Social policies emerge as the main indicator of evolution here, which is why the cultural dimension of social networking is most basic in this area compared to the two other areas (content and channels). 

The key link between this area and the next is targeting.

 

Channels

The exponential increase in "offered information"  does not cause a similar level of increase in "attractive content", but it clearly stages the occasion to produce more content that is attractive if the information can be appropriately contained. It seems inevitable that information consumers, who are the full population of social networkers, will not spend most of their time "boiling the ocean" by speculatively exploring unfamiliar information, much of which is hardly, if at all, "packaged". Instead that they will increasingly devote their consumption time to credibly familiar information sources. Social networkers will do an entirely traditional and conventional thing: they will more and more often pick certain routes and destinations first, and those first picks will use up most of their time and, barring interventions, become somewhat habitual. This will be the case regardless of what communication instrument is in use. Typically, when innovative instruments are released, the excitement is all about convenience and this stimulates speculative use. But familiarity of results will almost inevitably take over as the ersatz "content" either delights or frustrates -- and this will make discrimination the user's priority over convenience.

To make use of that discrimination, the link between Channels and Content is, not surprisingly, promotion.

Survival Strategies

As we can see, there is not really that much new going on in the overall dynamics of communications. Instead, there is a difference in the task-level efficiency of communications efforts, which amplifies the dynamics in various ways. Depending on who the stakeholder is, some of this amplification is deemed positive and some negative.

Arguably, fatigue is the main culprit in content, as publishers find a recurring audience more or less elusive and begin to evaluate the effort to continue publishing. Whether we point at blog graveyards or a deeper excavation of sites like Facebook, it is predictable that most publishers will significantly diminish their output over time unless they can leverage discovery to refresh their audience and thereby regain incentive to publish.

In the area of community, the most obvious dynamic is that communities are, from the bird's eye view, "chaotic", with ongoing splintering being just as important as ongoing conventions. What this really means is that communities are not so much simply environments themselves but also they are organisms within a larger environment. Organic development, assuming survival, may mean compositional change, maturity change, change in range and reach, or any mix of those changes. This is continally fortified by the ever-increasing ease of communications, which presents alternative stances and boundaries to the current community. So while communities are concerned with sustainability, what actually happens is that the community is more dedicated to the survival of "a" community than it is to the retention of most of its particular members. It is predictable that a community will diminish unless it can leverage targeting to reinforce adoption of its agenda, whether by new members or old.

And with channels, the lack of regulation means that a limitless number of potential channels compete and must rely on profiling the relationship of their content to channel users -- then promoting the profile. The underlying secret success factor, however, is that the promotion must actually change the cost effectiveness of competing --favorably for one's own channel, and unfavorably for competitors. The content itself is possibly a way to do that (think historically: MTV and "reality" shows), but such cases will be few, unusual and at best famously disruptive with an uncertain timespan of reaching evolutionary equilibrium. Some get there almost immediately, but some never quite make it.

 

So, in the full picture:

- Content is linked by Discovery to Communities

- Community is linked by Targeting to Channels

- Channel is linked by Promotion to Content

 

This is certainly not always a virtuous circle or even one that can be fully traversed by any one party. But importantly, it is more like a spring coil spiralling up and away over time/distance, while the whole coil might rock to and fro in different directions, pointing at a wide range of destination points. With predictions, one needs to consider also how long the coil is and what direction it is pointing in. In that light, what causes the coil to change directions? As of this writing, one of the curiouser matters is that promotions are getting more attention as content than is nearly any other kind of content, because there is such a frenzy about how to "monetize" social networking. But if this monetizing was not such a prominent issue, other kinds of content might be more highly valued.

This model looks an awful lot like marketing. And if marketers find it appealingly credible and familiar, they risk being accused of wielding the marketing hammer and seeing all problems as "nails". Non-marketers may be much less comfortable with it all. On the other hand, few disciplines are as relentless in their study of social communications as is marketing. So, as one of my colleagues taught me to say, this is king of the hill until somebody knocks it off.

Posted by Malcolm Ryder at 6:45 AM | Comments (0) | TrackBack

August 13, 2009

Why Business Processes drive Customization... and what to do about it

Customization of business processes means that there is more "precision" in the targeted effort to succeed. But in situations where support may not be up to speed and where targets may change, this precision comes at a high cost of achieving readiness and warding off eventual irrelevance, making it just as risky as it may be attractive.

The general sense of "customization" compares against three basic options for the formations of a business process.

Option 1: One-Size-Fits-All

For business processes, this is a myth, because “business” is primarily about accommodating multiple relationships and requirements, not primarily about manufacturing a standard product. The “process” must support what business “is about”. Relationships tend to be privileged, not indifferently available.

Option 2: Specialization

Sometimes incorrectly called “customization”, specialization is different: it means variations on a single theme. The theme has standard requirements; the fulfillment is where the variety occurs.

Option 3: Customization

Customization begins in the requirements, not in the fulfillment of them.
There are three reasons why requirements may be “custom”:

• Cost structures


• Competitive Innovation


• Capability Immaturity

Three reasons why requirements may be custom, not generic.

Cost Structures:

• Satisfying customers is not profitable if it is too expensive; different organizations (different suppliers, and different consumers) have different cashflows

Competitive Innovation:

• Existing customers, to decide to stick around, need to feel that the relationship is fresh and current
• Potential customers need a reason to prefer one provider over another

Capability Immaturity:

• The time available to use for improving capability may not be in synch (priority, availability) with other resources

Three reasons why requirements may be "custom", explained.

Cost Structures:

• Lack of visibility on true economic impacts puts operations on a risk-aversion basis seen in typical micro-management approches

Competitive Innovation:

• High rate of change is necessary to sustain improvisations that generate necessary nw effects or advantages

Capability Immaturity:

• Required performance level outstrips currently available supporting mechanisms, forcing risky workarounds. 

How to mitigate or avoid customization.

Micro-management:

• An operational performance model allows activity to be prioritized and weighed by differential contribution to goals and thus by ROI perspective. (For example, the 80/20 rule.) Relieves pressure to dwell on the microscopic. Define objectives, CSFs and KPIs. Switch to “trust-and-verify” mode.

Improvisations:

• Linking process models to knowledge management allows standardized roles to be able to move quickly and differently on incoming information, without re-organizations.
  

Workarounds:

• Organizing around known best practices clarifies ways to structurally reduce risk and to more rationally divide the labor required to meet performance targets. Such greater clarity allows managers to make the compelling business case for additional help to cover properly allocated responsibilities.

When to Customize.

Considering the above notes, executives should still project the likely value of customizations. The punchline is that it cannot be taken for granted that customization is the best path to take, neither in the short run nor the long. Customization proposals that withstand comparison to the above considerations should be given even more enthusiasm than usual, as they probably then point at nearly unique opportunities to do something strategically important to the business.

 

Posted by Malcolm Ryder at 10:37 AM

August 2, 2009

An Inconvenient Reference. (Content, Knowledge and Information Networks)

At The Global Human Capital Journal,GHCJ pays respects to the passing of an empire of bound knowledge: the Encyclopedia Brittanica. Noting that online search is giving a better topical hit rate, the compelling value proposition of going to the paper shelf comes up mainly as a memory. Somewhat proving the point, I came to the GHCJ post online via a colleague, but at the same time there's irony in the uncertainty of relying on unfamiliar online sources to be authoritative about the passing of familiar offline sources. Online, when it comes to navigating certain topics, I'd prefer to route through a colleague than through Google. That said, as the GHCJ piece was really well put together already, I collegially posed some off-shoot thoughts in a comment left there, and shown below.

When you said "Authority", I first thought of "credibility", not of "power". My reading of your Authority description is that it is about power. I think the credibility issue is more critical to pursue. I would compare not the old hierarchy of a production "pipeline" versus the newer flatter production "collaboration", but instead the old value "chain" versus the new value "network". So far, I think the new production paradigms distinguish themselves primarily in terms of convenience, not credibility nor value: what does happen is that I can presume to meet information deadlines "cheaper", and maybe "faster', although far less certainly "prettier" (even though the acceleration of work is economically "sexy" so to speak). Tech innovation a la the web poses essentially the same risk that process automation does: it is now much easier to do something poorly more often.

And when you said "Knowledge Economy", I again experienced a related but tangential thought. Much of the widespread discussions of these affairs appears to me to terribly confuse "content", "knowledge" and "information". Each term respectively already carries a relatively new and trendy mythology about "producers", highlighting in common the newfound convenience of being one. To this I say that being a producer is "valuable", but being a producer does not "cause" value. And more to the point, the confusions I fear are the heavily marketed notions that content producers create better knowledge, that information producers create better content, that... well you get my drift. I suppose if I could make a practical point here, it would be that while the innovations in production may be revolutionary, the innovations in knowledge are instead still evolutionary. We are experiencing an expansive Content Economy that far outstrips the growth of actionable knowledge.

This brings me to the last thought to share for now: the notion of "reference". By exploiting the vehicles (let's not call them sources yet) for acquiring information, we do one or both of two different things, and it is worth knowing the difference. One of them is "referencing". The other is "researching". Part of the competency of KM is knowing that there is a difference while knowing how to relate them; to create a reference from competent research is still something that is a practice with differing degrees of acquired skill, differences that are more important than whether we are known as professionals or amateurs.

All that said, you hit a big nail right on the head. To summarize my takeaway from your posting: an inconvenient reference will lose out to a convenient one, for better or worse.

Posted by Malcolm Ryder at 11:26 AM | Comments (0) | TrackBack

July 19, 2009

The Smarts about Experts

In the article Your help with the new expertise By David Weinberger posted Jul 3, 2009 at KM World, three things stand out in his "arc" of thought as factors of "expertise" -- credence, confidence, and communication. How they are blended for consumption is the matter that is under observation.

In effect, he describes that using a network to access a healthy debate is like watching the sausage getting made instead of just heating up the product already in its skin by buying the expert book or the expert consultant.

Or to be fair, he indicates that when it comes to "managed" knowledge, participation is more compelling than mere consumption.

What is really at stake here though, I'd say, is the ability to accept the quality of the production as being good enough for the issue at hand. In this analogy, the production is not the knowledge itself; the production is the communication experienced. But communication and expertise are not the same thing at all.

Of course, communication can provide very high quality knowledge, but it might instead just provide very high confidence in something that is not very high quality knowledge.

So where is the value, actually? We are *not* necessarily smarter than me; instead, a network hosts collaboration -- and from that, we might be way more productive than me. Unfortunately, ad hoc collaboration is often unpredictable: you don't know whether you're going to get a committee or a team, and you don't know whether the practical impact of the group fest is likely to cover the opportunity cost.

Nonetheless, thanks to networks, collaboration is a more usable path to effective knowledge now than it has been in the past; but counter to David's hypothesis, I suggest that it does not change the nature of expertise.

For example, the difference between an edited book and a networked interaction is about the same as the difference between an authoritative critic and a peer review. They presume different kinds of credibility but it is not a given that either one of them is credible until they prove it. And they *can* come to the exact same conclusions.

So, what happens next? Someone who needs to make decisions will go back to whichever party has the best proofs. Someone who is just thinking about stuff can go with whichever party is most convenient. The latter is much more sensitive to culture than is the former. I think this will be borne out by truthful stories of how people are pursuing expertise so far in networks.

Those of us who are cheerleaders for innovation might confess that we'd prefer to invest in making the new convenience cough up the better results. Given the latitude to have that attitude, the real burden on us is to establish that "convenient" is better, not that the product is better.

Posted by Malcolm Ryder at 10:44 PM | Comments (0) | TrackBack

February 23, 2009

Federation, Synchronization and Consolidation in I.T. -- a lot, but not enough.

Famously saturated with acronyms, the world of managing information technology (I.T.) is rocked today mostly by a little old one newly coming into its own -- the "CI", or "configuration item".

Very roughly speaking, a CI is often identified as a piece of equipment that needs to be carefully protected against unapproved modifications of (a.) its own characteristics (called "attributes") and of (b.) its operational relationships with other CIs. Interrelated CIs typically make up larger single systems, and the required on-demand access to those continually operating systems by business users allows the systems to be thought of as "services".

Anyone who has done systems research or done the care and feeding of systems is familiar with the idea that a system is often made up of sub-systems -- for example the way that the human body is composed, or a good old-fashioned hi-fi stereo component hookup, or compounds made of molecules made of atoms. One of the key things to consider in managing the higher-level systems is that their sub-systems are indeed complete systems themselves and have their own internal complexities of components.

"CIs" are things that are similar to the above, in that a higher-level CI such as a "service" may be composed of other "sub"-services having, in turn, their own constituent services -- but this is why in the conversations about "CIs" in many companies, confusion develops amongst the terms "service", "system", and "component". Questions and even arguments follow this confusion, such as "when is a system a CI? Are all services CIs? Do components combine to make CIs? Do CIs combine to make other CIs?" This puts an end to the usefulness of speaking roughly.

So instead, if we take the term "Configuration Item" and break it down without regard to its actual linguistic history, we should think freshly: the term "configuration" means something on its own -- i.e., a certain arrangement of selected parts -- and the term "item" represents something involved in a configuration -- namely, a part. Any construction has a configuration, and the parts in the configuration are items. This conceptual abstraction is still easy language, and it completely covers the aspect of drilling down into one thing to find, among its parts, other things that each can likewise be decomposed. What follows below intends to apply such consistency across old terminologies as well. 

 

 

 

 

 

 

 

 

 

 

For our purposes of discussion, the key construction is going to be some service that we want to have. As we'll see in the illustration here, there is an important and consistent way to discuss what is found in the drill-down on a service. Generally, we drill down onto two different kinds of resources for the service. On the one hand, sub-sections of a construction are what should be known as "components". On the other hand, the materials that are used to make up the subsection are what should be known as "elements".  Like fire, earth, air and water, there are different kinds of elements; they combine to make up components that can be sub-sections of constructions, including of course constructions that have only one logical subsection: the unit whole. Logically, this is always true regardless of what particular construction is developed. But now, to address an earlier question, when is a construction a "CI"? And the answer is, a CI is not a thing; it is a management perspective on a thing. This thing might be an item or a configuration. What makes the thing a CI is management's attention to its role as an "element" of a service. 

Now, when the main construction will be provided for use as a "service", and we are talking about the "components" of the service, we are referring to the configurations within the service. Remember that the essence of a "service" is in that it is something being provided for use in a given way; the type and complexity of a thing does not define it as being a service. However, logically, the components in the management view are the actual "instances" of whatever type of CI, since the instances are what the service user is actually reliant on.

Remember also that the configurations within the service are constructions themselves. What we must recognize is that for a construction seen at a "top" or "parent" level, the involved configurations have elements; but at a lower "child" level, those elements of the parent may be constructions for the child. In this way we see the drill-down through a structural hierarchy based on a recurring logic.  For pragmatic reasons, organizations increasingly adopt names for the different levels, such as "Business" (parent), "IT" (child), and "Systems" (grandchild). By this logic, systems configurations become items for (i.e., elements of) IT configurations, and IT configurations become items for business configurations. Meanwhile, "services" may occur at any level, because what defines a service is how something is provided, not what something is. 

What is more interesting, then, in this whole thing is not so much the parts (items) themselves but the relationships that become the structural arrangement (or actual configuration) within the construction provided as a service.

In a management scenario, relationships become important mainly because, not surprisingly, they make the configuration manageable. This intent immediately makes some relationships more important than others depending on the perspective of the particular manager. And most interestingly, it throws attention on items (parts)that are not "equipment" such as hardware and software, but instead are "instruments" such as supervisory people, or regulatory documents -- indeed, any influential entity that can be logically assigned (i.e., related) as an enabling part in the ongoing functionality of the construction.

Now, since one of management's primary concerns is to establish and maintain the appropriateness to task of whatever is being managed, then another large focus of management is configurability. To throw quality control into configurability, there is initially the aspect of design, and quickly thereafter the matter of change-control.

The design side of things calls for specifications, which basically are descriptions of the particular configuration and/or item that is intended to be realized. With design and specifications, many instances of the same type of thing should be possible to produce with sufficient similarity to make the instances interchangeable if necessary, but all of the instances would be examples of a specific and unique version of a specific and unique model.

The value of specification is in its precision, which allows managers and users to have confidence that they have their hands on exactly what they need. The specification may point out that there are characteristics of a configuration that are produced or contributed by supplier X while other characteristics are given by supplier Y.

Keeping a central library of trusted configuration descriptions is the idea that gave birth to the Configuration Management DataBase or CMDB. In a CMDB, it is usually the case that configuration characteristics are identified as parts meeting specifications called "attributes".  It stands to reason that a CMDB needs to gather reliable data from multiple suppliers responsible for the attributes of any of the configurations on record. The problem of managing the CMDB itself, then, is no different from keeping any complex database in good shape. If anything, the degree of confidence that the CMDB users want in its data makes the complexity that much harder to cope with.

Centralization of the data is the easy way to describe the strategy for meeting the goal of a highly-reliable CMDB. To really appreciate what this means, it is necessary to understand "centralization" in three tactical ways that reflect and resolve the CMDB's complexity:
- federation,
- synchronization, and...
- consolidation.

Federation refers to the multiple donors of trusted information working in a co-operative manner so that they do not fail to contribute the right thing by the right time. As teammates, they need to all be on the playing field together when the play is about to be run.

Synchronization refers to the possibility that more than one party knows about the same thing, but they know it and talk about it in dissimilar ways. In this case, if one of them is more up to date in its knowledge than is the the other one, the other needs to get up to date in the terms that it uses to refer to the same thing. This paralleling, in which if A=B and B=C then A=C, calls for some mechanism that can assure the parties' two different terms (A and C) can again represent each other correctly in the same moment.

Consolidation refers to the case where multiple terms that refer to the same thing are reduced to one term which becomes the singular preferred referent, making the redundant others unnecessary.

Ideally, any configuration in a CMDB is an instance of some single type that is a successful consolidation of descriptions. Each unique type can have, theoretically, an unlimited number of instances.

In typical implementations, a CMDB may or may not be federated, since the CMDB might be held responsible for only certain types of configurations that could be confidently composed and described without multiple suppliers. Federation, always a possibility, is usually more the exception than the rule.

Synchronization is initially an issue when the first decisions are being made about which data sources are the ones that should be considered authoritative. If there are already multiple systems recording descriptions of the same thing, they probably need to be checked against each other to see how well they match, before either one is chosen over the other. This will be most useful when CIs are being initially defined for inclusion in the CMDB, since there is no point in recording a CI unless there is a trusted mechanism for keeping the record up to date.

As the above issues go, things tend to resolve in a way that there is not much discussion about federation, synchronization or consolidation (!) -- however, a different term is constantly used and rules the roost: reconciliation.

Reconciliation refers to the need to take recent validated discoveries about the characteristics of actual instances of configurations, and compare the findings to the record about those configurations as found in the CMDB. Updating the CMDB records means that the recorded versus discovered information must be checked, with mismatches resolved through a manager's decision about whether to change the CMDB record or change the actual configuration instance. Because a CMDB is not trusted unless it is known to be up-to-date in its authority, reconciliation is a critical success factor for the CMDB utilization. However, in a little recognized nuance, "reconciliation" is often mis-applied to the effort to remain up-to-date.

To appreciate this nuance, consider that two parties start out disagreeing, but they wind up agreeing with each other in the end. This would be reconciliation. However, if the two parties cannot agree with each other, and a third party is required to make the decision for both of them, then the original two parties (still disagreeing) did not have a reconciliation but instead an arbitration. An important thing to note here is that an arbitration effort can always come up with the same results that a reconciliation can, but a reconciliation effort cannot always come up with the results that an arbitration can.

It is often the case that I.T. managers rely on a mix of tools providing highly reliable feedback each in its own terms. This sets up the important necessity for arbitration to the degree that the tools do not share a common descriptive dictionary. Arbitration rules enforce "tiebreakers" and properly dispose of exceptions; this clears the way for consolidation of information within the CI record.and brings the CMDB closer to the capability that management really wants the CMDB to support -- risk avoidance in decisions, under the pressure of Quality of Service expectations.

Posted by Malcolm Ryder at 4:17 PM

September 6, 2008

Management Improvisation

Normally, management authorizes actions based on information. But the most frequent and expected connotation of the word "manage" is the word "control".

Given that management is undertaken to provide some assurance of "success", this connotation may be why management effectiveness is most often sought in terms of proof of control. The problem with this attitude is that it ignores more than half of the range of opportunity that is available to deliberately effect valuable progress in an endeavor.

In the framework below, a much fuller range of management is identified, in a way that puts "control" in context -- and shows it to be not only more varied than we typically allow it to be, but also that it is accompanied by important complements and alternatives for driving progress. To start with, the framework shows how the usual old notion of "control" is probably contained by items (left column) that are not best called control but rather "organization".

As seen here, a new semantics of "controls" is proposed (and explained later below). And still, the value of controls is to promote success.

A simple observation that may capture the ambitions about success in management is this: if it takes scoring to win, intending to score is more essential than planning to win. In management, progress is essentially like scoring. Given that, strategy is fundamentally about how to enable progress under the prevailing circumstances -- which in turn means that as circumstances change, strategy dynamically identifies and solves the problem of sustaining an ability to progress.

This readiness to improvise the action -- to take the "fast break", acknowledges that the circumstances of the game are all incidental within the basic boundaries that others play within as well. That is, within the same standing set of boundaries, many separate games are played -- and one game never necessarily predicts the next even if it winds up resembling it.

In that regard, what may be most difficult about competitive strategy is, first, to identify the boundaries that most matter; and second, to invent relevant actions within that awareness. In a competitive situation, much of what truly surprises the competition is an action that they didn't foresee because they hadn't identified the pertinent boundaries yet. (This is exactly why we often tend to speak of game-breaking competitors as being outfits that "change the rules"...)

Arriving at the necessary awareness is the product of surveillance and analysis, to which much dazzling and complex effort is formally dedicated now through business intelligence and knowledge management.

But the framework above imagines it more simply. It is not hard to see that the three forms of "management affects" -- controls, influences* and standards -- correspond respectively to knowledge, communications, and references -- are different modalities of common information that generate authority and action. The question is, how are the modalities currently being used?

So, what we get from this framework, mainly, is another perspective from which to assess how we manage now and whether the right modes are applied in the right ways.

Along with showing how information figures in, the framework helps show that the nature of management authority ranges (bottom to top) from being externally objective (standards) to being more cooperatively elective (influences) to finally being internally directive (controls). This tracks the application of recognized authority from its lightest to its heaviest.

The layout of the framework also corresponds (left to right) to the difference between micromanagement (organization) and macromanagement(improvisation). From that viewpoint, when we think of managed action as execution, the span of potential methodologies shows up being quite broad. Assumptions about what is needed to realize a strategy are challenged by showing that taking management more "micro" is possibly an inhibitor, but really just a supporting option, not a defacto requirement. For example, we have to allow for the possibility that individual contributors, rogues or artists -- left unbridled amongst changes -- may be enough, or even best.

In short, the old notion of control is really micromanagement. And as argued by the framework here, a big implication is that micromanagement and strategy are possibly allergic to each other or at least require arbitration -- a thought that may be the cause of some fresh assessment of management.

* While the word "influences" seems somewhat forced here (and may be replaced in the future), the intended sense of it is as a degree of imposition, here being neither benign (like standards) nor compelled (like controls).

Posted by Malcolm Ryder at 4:57 PM

August 25, 2008

Cyberpresence Socx

Some of the most nuanced things that we can encounter come from marketers. But the enduring charm of marketing is, basically, shamelessness.

That sounds bad, but the only problem with shamelessness is that it's hard to pull it off successfully, so not everybody can do it. In the strategy of shamelessness it is still, paradoxically, a requirement to maintain some cool.

This amounts to predetermining what kind of "online presence" is needed, and why -- backed of course by the right tools to generate that online presence. Where should people find you online? who should they meet when they find "you"? and why should they (from their perspective) find "you" the way that they do? Assume that they are wherever they are not because of you but because of what that channel offers them; then determine what version of yourself is appropriate to have appear in that channel. "You" might be different from one channel to another, but the different "You's" need to all be appropriate representatives of the brand you are trying to maintain.

It's pretty much like getting dressed to go out with strangers. But how hard could it be? Humphrey Bogart got to say it first: "The only cause I'm interested in is Me."

The scary part is finding out there's not much mileage in your hype. You remember: there's the famous Andy Warhol saying: "In the future everyone will be famous for 15 minutes."

As for blogs, it's more like "in the future, everyone will be famous to fifteen people." (I can't remember who it was that said that, but the quote is certainly memorable, and the citation for it is probably retrievable via Google, etc.)

There are different levels of shamelessness, with blogging and online social networking holding down the opposing goalposts. (Incidentally, Archestra is not a blog, although it runs in blogware. Archestra is, instead, just an open studio.)

Surely, blogging is important to marketing, particularly with the aspect of staging a "market" of ideas about what you sell. But blogs are just the booth in the marketplace. Blogs are inherently editorial, and the only reason we would expect one to succeed is because of the popularity of the personality that is the explicit editorial energy of the blog. (Note: not being a blogger myself, I can't claim to have any expertise on making one work; but having subscribed to several in the past, I found that I only go to the ones where I feel like I am interested in the person whose blog it is. Moreover, with zillions of blogs out there, the fatigue factor of going through yet another new blog is a real impediment that makes it just seem unnecessary. What gets me past the impediment is either a recommendation from someone or a sample of the subject handling that shows me the blogger is unusually interesting.)

Wikis are a bit like blogs in that they have a subject focus, and that subject attracts a crowd (you would hope), but the subject focus is maintained by a crowd, not by a singular editorial personality. With a wiki, one always hopes that peer criticism will culture the crowd towards "wisdom", as they like to say.

Finally (for the moment), the point of a social network is that the crowd moves its focus around and shares what it finds by talking to each other. Focal points emerge rather than being prescribed. But the sharing occurs because of people in the crowd who are already interested in each other and keep introducing who they know to other people. This thing about "buzz" is about when the communication gets flowing strongly about an emergent focalpoint.

A marketer should look at how the online forums* perform compared to each other:
- blogs establish relevance
- wikis establish credibility
- and social networks (which I hereby impertinently deem "SOCX"), being where markets actually live, establish importance

(Let's face it, most people who have used the sound "SOX" outside of baseball could not tell you who Sarbanes is nor Oxley nor whether their company would survive an audit. So why should they get to monopolize the phonemes? In the real world, social exchanges are vastly more interesting, and after I've said "blog" twice and a quick "wiki" a few times in a row I'm not interested in two-part five syllable elaborations for the rest of the choices. SOCX it is. Could be lonely, but I don't care.)

* apologies to anyone with a language degree

Posted by Malcolm Ryder at 8:49 AM

The Mystery of I.P., or Not

What mystery?

The rule of thumb is that concepts are not property. The challenge is to wrap "property" around the concepts, so that the property is where people go to find the concepts. Since the value of the property is to some degree related to its scarcity, it is not difficult to understand what to do next.

- Use of ideas can be licensed in certain contexts.

- Information is either confidential or it is not, and you can sell access to confidential information.

- Knowledge is proprietary only if you have the ability to control the context of the knowledge delivery; control is all about packaging (whether the package is a venue, an event, a medium, or a box). You can sell the package; you can also sell delivery.

Posted by Malcolm Ryder at 7:27 AM

May 29, 2008

Savvy About Knowledge?

Just what is it about knowledge that makes it so.. interesting... so... appealing?

On National Public Radio's KQED show "Forum", much of what was discussed recently about the elusive nature of knowledge had to do with the experience of being "certain" or "uncertain", and how that experience could be provoked, as it turns out, by altering not only the state of consciousness but the state of the brain itself. This argued that we must be able to admit the difference between believing we know, versus objectively being correct.

But it's not so important that there is any state of being absolutely "right or wrong" about what is real or what is actual.

Instead of right or wrong being the decisive criteria, what matters is that knowledge as an embrace of abstraction is different from knowledge as an embrace of concreteness.

Abstraction leads us to expect that future experience will have some particulars; concreteness leads us to accept that current experience has some particulars. Abstraction provides models; concreteness provides examples.

In both cases, selectivity is a critical determinant; maturity in knowledge broadens our scope of selectivity.

And in both cases, our mind invents experience as well as receives experience. Note that we constantly take models as examples of something, and we constantly take examples as models of something...

This "flexibility" shows that as an ongoing phenomenon, our knowledge is continually tested by the activity of inventing and receiving particulars into what we call our awareness.

In the end, we are certain that we have awareness, but we may be uncertain of whether our awareness is all it can or should be. This throws the value more on being knowledge-able than on "having" knowledge; a mind is a terrible thing to close, and uncertainty is actually a key to generating the value of knowledge. Ultimately, the important thing about "knowledge" lies in what knowledge makes you do.

Posted by Malcolm Ryder at 10:42 AM

April 26, 2008

Inciting Insight

In the big picture of purposefulness versus accidents, management accommodates a coincidence of things that ought to make a difference, such as designs, events, and states. Information systems grind on each of these, going both deep and wide. But what matters is whether management orchestrates a convergence of those things. Is such orchestration forcing the issue, or is it simply the way these things actually turn out to have meaning?

It's customary to eschew information overload; but the key to their useful combination is not the specific information compared, rather how the available information is positioned in the overall scheme of interpretation. As seen in the picture above, intents and impacts which superficially represent "how things are going" will relate in terms of the "5 W's and How". Seeing the certain blending of factors here, it is easier to realize that most insights will be moments of correlation that are the prize for maintaining ordinary but diligent awareness in a variety of ways.

But just like money, insights are mainly worth the use to which they are put. So, whether this big picture describes the competency of an individual savvy person or of an enterprise, it tells something about being strategically capable but the goods are in the doing after the learning.

Posted by Malcolm Ryder at 6:15 PM

April 19, 2008

The Innovator's Real Dilemma

Jessica Stillman at the new BNET1 blog rounds up research from Accenture, the Conference Board, and Wharton to talk about why Fostering Innovation Stumps Executives ...

This is an interesting situation to ponder: making choices about how much to invest in innovation , versus in knowledge management and, separately, business intelligence as other paths to insight. Overall, what the organization is mainly after -- where the real money rests -- is the insight, whatever the path. But the current thinking about management priorities indicates that insight is pretty hard to come by, so lesser-beaten paths to it are also getting a lot of attention.

One challenge that surfaces, somewhat amusingly, is the presumed need to be innovative about how to foster innovation. For example, given that "innovation" is so easily approached as "creativity", it is not surprising that at places where real urgency comes from competition against either industry rivals or the budget, the idea of stimulating the worker's right brain with art experiences can gain some real traction.

But perhaps everything new is old again... The simplest way to assure that innovation is "fostered" is to provide
(1.) a clear statement of why the company will consider something to be "innovative" and...
(2.) a clear statement about what circumstances will cause the innovation to be rewarded in a way that directly benefits the individual(s) involved.

Generally, if company leadership can't get that much communication together and abide by it, then most other "fostering" efforts are essentially arbitrary.

Furthermore, this effort should not be confused at all with management's concern about how to measure the innovation's impact on the company's performance. The performance impact issue is not something that should be making innovation special. Any management team that rewards "performance impacts" with bonuses should simply add innovations to the mix of things that can be clearly accounted for as contributors to better performance. Meanwhile, innovation is about doing things differently to create opportunity; but execution is about doing things a certain way to hit performance targets.

This is where managers have to get real: if they will not reward innovators for being innovative, as opposed to making the reward conditional upon performance increases, then people will learn that innovation is not worth the effort at this organization. So in step (2.) above, the "circumstances" to be declared must start with something other than performance metrics.

Posted by Malcolm Ryder at 8:42 AM

March 30, 2008

Careful What You Ask For...

Anyone who has visited Archestra more than once ( all nine people! ...well, ok, eight not couting myself) knows that a major point getting made is this: what looks like problems without solutions is often due to the romantic allegiance we have to a misleading vocabulary.

It's especially important to catch those times when strategy, management, execution, and other fundamentals are being wrestled by name. In that vein, one of the longest-standing friends of Archestra -- Bruce MacEwen at Adam Smith, Esquire -- caught the notice (again) of a somewhat newer friend -- Jack Vinson at Knowledge Jolt -- setting the stage for the commentary now here.

Bruce starts it off by reviewing ideas in the The Halo Effect, by Phil Rosenzweig. Rosenweig explores the historical ineffectiveness of management guru wisdom, and Bruce shortly comes to his own punchline: "In this unknowable world, what attitude and what approach grace us with the best odds of success? Only one: Critical thinking."

But as you read Bruce's fluid argument to the conclusion, you pass through the equally important question in his theme: "What do you have to know, to be the best performer?"

Jack, a seasoned spokesman for the Theory of Constraints (TOC), embraces Bruce's conclusion; but moreso he picks up that earlier question with his own followup, posing a perhaps ironic counterargument to Bruce's conclusion. With no pretense of being gurus, both men argue for the value of logic to management that would aspire to the top rung of performance. But Jack shines a light in the dark corner of logic's chronic problem with gaining broad acceptance. Case in point: Jack's observation that TOC works but still doesn't proliferate poses this question: "What does it take to get chosen as the management approach?" And our question, naturally, becomes "if you aren't chosen, then how can you be the key to success?"

Evidently, what it takes to be chosen is a combination of marketing and politics -- and the facts may be that the underlying genius of "success" is not the management approach used but instead the competitive approach employed by the executives. What Jack points out, intentionally or not, is beautifully brutal: that sometimes things work and sometimes they don't. And we must remember that winning ugly is still...winning. TOC companies may be winners, but most winners don't use TOC. (True, or false? Jack suggests, True.)

Consequently, when it comes to competition, we can't be sure that a great lot of companies should do anything in common; but instead we have to focus on why something works for the company that it works for.

In other words, there is a glaring difference between strategic management and competitive strategy, with the better competitors doing most of the winning, not foremost the better managed.

What executives must be responsible for is figuring out what strategy their company can win with; and what managers must do is figure out whether the company is doing what that appropriate competitive strategy calls for.

As both Bruce and Jack assert, critical thinking ought to be a key tool, and here we assert that it is a key tool in both competition and management. But what overrides both circumstances is the possibility that the thinking will be done about the wrong thing.

Eschewing mythologies and the emperor's new clothes, Jack quotes Bruce's counsel against that problem : "rigorous and unblinking analysis of reality as it is, not as you want it to be..." What we must take this to mean is not that some approach is inherently more competitively clairvoyant than another, but instead that executives and managers must not run the company based on a mythology (of an approach) that does not fit the company. To puncture the mythology, you have to be able to cut through the marketing and politics that surround it within the company.

New punchlines: as the top person in charge, you can't know what strategy will be your most successful against the competition before you know your organization; and when you reach an understanding of what your organization can do, you then have to either select a strategy that fits the organization, or you have to change your organization to fit a different strategy. What's tough is that you have to do this while the game is already underway.

Posted by Malcolm Ryder at 1:53 PM

March 21, 2008

Who Knows how to Manage Knowledge Management?

The initial impetus for practicing knowledge management as a discipline is to Effect a different outcome from what has already otherwise been obtained.

Best practices of knowledge management are meant to Affect the approaches to gaining the target outcome.

Question behind the outcome: "Why should knowledge be managed?"

Answer: knowledge has proved to be a resource that is critical to efficiently determining a two-part condition:
- when solution options exist and
- which options are optimal.
In the past, opportunity and quality have both suffered because effective knowledge was not available to be incorporated in a timely way during investigations and decision-making.

The goal of managing knowledge is to achieve timely discovery and acquisition of quality-checked knowledge for use during "live" investigation and decisioning.

It is important to recognize that investigation and decisioning are "constants" across a wide range of distinctive eforts:
- development (design, build)
- analysis (assess, interpret)
- auditing (measure, validate)

The management discipline provides people (roles), processes and tools to facilitate the following treatments of knowledge:
1 - discovery/generation
2 - QA
3 - acquisition/distribution
4 - lifecycle control (content versioning and retirement)

Practices within the discipline are "best" when they accomplish the following two things:
- they manage to align each of the four treatments individually with the operational environment that is meant to be sustained by executive influence (or group culture),
- but the practices align them in a way that allows each treatment to align with the other treatments (!) -- especially so that you get a chain linkage from 1 to 4 that allows 4 to also loop back as a "supplier" to 1.

With this overview, it is possible to understand where most of the phenomena that are now associated with KM should be able to fit in, and to simultaneously recognize that the various phenomena can be creatively "fitted in" to exploit special circumstances such as existing resources, emergencies, enthusiasm, or general curiosity and inventiveness. Those circumstances should be governed by a higher-level strategy. The typical phenomena include collaboration, multimedia (rich content), social networks, semantic search, library science, and games.

Posted by Malcolm Ryder at 9:51 AM

Who Knows how to Manage Knowledge Management?

The initial impetus for practicing knowledge management as a discipline is to Effect a different outcome from what has already otherwise been obtained.

Best practices of knowledge management are meant to Affect the approaches to gaining the target outcome.

Question behind the outcome: "Why should knowledge be managed?"

Answer: knowledge has proved to be a resource that is critical to efficiently determining a two-part condition:
- when solution options exist and
- which options are optimal.
In the past, opportunity and quality have both suffered because effective knowledge was not available to be incorporated in a timely way during investigations and decision-making.

The goal of managing knowledge is to achieve timely discovery and acquisition of quality-checked knowledge for use during "live" investigation and decisioning.

It is important to recognize that investigation and decisioning are "constants" across a wide range of distinctive eforts:
- development (design, build)
- analysis (assess, interpret)
- auditing (measure, validate)

The management discipline provides people (roles), processes and tools to facilitate the following treatments of knowledge:
1 - discovery/generation
2 - QA
3 - acquisition/distribution
4 - lifecycle control (content versioning and retirement)

Practices within the discipline are "best" when they accomplish the following two things:
- they manage to align each of the four treatments individually with the operational environment that is meant to be sustained by executive influence (or group culture),
- but the practices align them in a way that allows each treatment to align with the other treatments (!) -- especially so that you get a chain linkage from 1 to 4 that allows 4 to also loop back as a "supplier" to 1.

With this overview, it is possible to understand where most of the phenomena that are now associated with KM should be able to fit in, and to simultaneously recognize that the various phenomena can be creatively "fitted in" to exploit special circumstances such as existing resources, emergencies, enthusiasm, or general curiosity and inventiveness. Those circumstances should be governed by a higher-level strategy. The typical phenomena include collaboration, multimedia (rich content), social networks, semantic search, library science, and games.

Posted by Malcolm Ryder at 9:51 AM

January 1, 2008

Driving Value from Change with Knowledge

Frank thoughts about why people are important to an organization mainly go down two tracks.
One track examines what is necessary for the organization to be "in the game" it plans to play... The other examines what is necessary for the organization to play the way it wants to play, when already in the game.

Few experienced people still hold on to the simplistic idea that the former track is about line workers with the latter being about the managers. Since the recognition of CRM's dominant influence on the top line of the business, ample evidence establishes that alignment of front and back offices is critical to sustaining wins. Repeatedly getting the right things to the right place at the right time for the right reason means that staff in management and in line production must both attend to operational fundamentals, and both attend to situational performance differentiators.

During the early adoption period for that principle of alignment, "knowledge worker" became a profile arguing for distinction. We identify it as a profile, and not as a role, because it is an optional mode for every role. In organizations where it actually makes sense to discuss "knowledge workers", I.T. has made the greater part of production dependent on information processing and on interpreting the status of the processing outputs. Net: in the procedural life of the organization's activity, analysts now constantly threaten to outnumber mechanics.

The appropriate new idea of worker "productivity" follows quickly on the management of information, where the issue is about what value the worker's information management should provide. In the usual formula, value is expected to result where experience influences the information management.

But there are two tracks involved in applying that experience to the information:

- keeping things the way they were designed to be; and,
- successfully adapting as necessary to changes.

Most practical experience in organizations is role-based. In fact, we must assume that managing experience through roles is the complement to managing information, with their sum being what we recognize as practical knowledge. The question that the information age has added to the foreground of this discussion is how the manager role and the line worker role respectively exercize the knowledge worker profile to provide the value expected from their roles.

Workers with a higher degree of performance recognition in the organization are most frequently those who run the second track -- adapting to change -- in the knowledge worker mode.

To point this out more specifically, it helps to identify what qualifies as "change". The table below identifies, in ordinary language, the key types of change (points where value is generated), and the relevant "valuable behaviors" sought from managers and line workers executing their roles in the knowledge-worker mode.

Aside from confidential facts, the most privileged type of information is ideas. Speaking broadly, we can say that an "idea" is a proposed condition with an expected meaning. Left to its own devices, the "k-worker" (knowledgeworker) profile is about managing ideas for specific circumstances. As shown in the table, that relatively "pure" focus is pulled to different pragmatic effects by the role that uses it (manager or production line worker). That said, for most companies relevant to this discussion, a prescribed business process is the production line of importance that "manufactures" the necessary deliverables from the organization.

Posted by Malcolm Ryder at 12:30 PM | Comments (0) | TrackBack

September 14, 2007

Smart enough to be Lucky

Along with confusion about "business intelligence" comes similar uncertainties about "predictive analytics".

Aside from the very entertaining irony of not being able to predict the value of predictive analytics, is this another case of managers and markets just making things harder than they need to be?

The very notion of analyzing one's way to a "correct prediction" is so provocative, it's hard to even make a comment about it that stays on point instead of swinging freely between paranoia and irrational exuberance... But let's look at the enthusiasms, this way:
- everyone wants predictive analytics;
- a subset of everyone wants to pay for it;
- a subset of that payers' group is willing to trust it;
- and a subset of that trusting group is willing to depend on it.

Meanwhile, the difference between what makes predictive analytics successfully marketable versus successfully useful is a gap just as large as between the whopping percentage of enthusiasts versus the miniscule percent of dependents.

Useful? To figure out where you ought to be within that gap, you have to decide whether you need, or not, to bet on change in order to get what you insist on gaining. The more you need to bet on change, the more you're ready to rely on predictive analytics.

But "predictive analytics" is confusing to people because it makes them think of "calculation" which makes them think of "facts" -- and in other words encourages the idea that there's science leading to certainty. The problem is that it isn't the kind of certainty they suspect! The real point of prediction is not to identify certain future outcomes; it is to identify certain future possibilities. If you're only interested in one possibility, you're not looking for analysis, you're looking for accounting.

(Timo Elliott's BI Questions Blog is the most recent location of discussion that provoked these comments.)

Posted by Malcolm Ryder at 10:16 PM | Comments (0) | TrackBack

July 31, 2007

The DnA of Knowledgebased Producers (Pt. 1)

Pretty much everyone recognizes "R&D" -- research 'n' development -- as a discrete activity with a special place in supporting the future prospects of the business.

Even so, the explosion of literature on how hard companies find it to make profitable sense of their desire for "innovation" certainly suggests that the expected output of R 'n' D is too often either missing or mystifying.

The current official wisdom is that these companies need to step up to an innovation *process*. This is pretty difficult to argue against, since management will likely not finally be tolerant of any sustained activity that can't be designed as such. So the emphasis shifts quickly to wondering what the process should be like, especially in terms of how to link it to other "normal" incumbent management processes.

If there is a flaw in this attitude, it is a fundamental flaw. By definition, innovation must be derived from having a supportive perspective on a change to a designated status quo. But since "perspective" and "status quo" both call for awareness based on presumptive ideas (which we'll call knowledge), the problem to solve about innovation is not to generate "auto-magic" extension of *activity* called R or D. Instead, the problem is first to understand why innovation would be the true nature of any outcomes, and then to look into how to breed it or at least capture it as it occurs.

It is in that light that the framework below provides the corrective lens spotting the place where innovation would emerge on the scene. It represents an important shift away from the presumption of R 'n' D and moves instead on the basis of Design and Application, or D 'n' A.

This organizational DnA breaks out the issue with a cross reference of the two key elements of design (concept and form) versus the two key elements of application (specification and implementation).

The shorthand supported by this framework is for representing the range of circumstances that might be "innovative" in character. Typically, these circumstances will include (a) new items on old contexts, (b) old items in new contexts, or (c) new items in new contexts.

Said even more briefly, when something old or new is used in a new way, there is apparent innovation. But this situation of associating some item or function with a usage will have included interesting particulars. For example, how did the idea for the association arise? What criteria established the practical acceptance of the association? How was it recognized that a new association -- proposed or found -- was possible and/or meaningful?

What the DnA framework exposes is the way that the intersections of design and application generate innovation and position it for leverage. Here are just some of the observations that match the framework:
- Inspiration: borrowing details from an existing specification provides us with inspiration.
- Invention: reconnecting the details in a designated arrangement generates our invention.
- Innovation: even without a prior invention, the decision to implement the inspiration can drive forward progress in an explicit attitude of accommodating new methodology and goals. (e.g., inernal organization or reorganization)
- Orchestration: to actually execute the accommodation, the arranging of feasible adaptations and options generates the output that can "go to market"... Without this orchestration, there is little reason to expect that either an invention or an innovation would have a channel of delivery to appropriate recipients. (e.g., external organization or reorganization)

One test of the framework is scalability -- meaning that it works, and works the same way, regardless of whether the trip from concept to delivery is only the few microseconds needed to blurt out in a useful language a sudden original thought, or instead is the many months in a cycle of product or corporate reorientation in its industry's marketplaces. Either way, the producer's initial efforts, in DnA, may not necessarily result in innovation; but given the material effects of Design (already perhaps "keepers"), we can always try to move from the framework's left to its right in Application and reach different and/or more "marketable value". These movements, including Form (e.g. models), Specification, and Implementation are easily recognized as domains of knowledge that are typically extant in the organization regardless of how well they are currently managed. Meanwhile, a producer may move within the framework in many different actual paths; one of the most typical paths to innovation means taking a concept through invention and various orchestrations to arrive at an innovation; but this is not the only path necessary or possible.

This knowledge-based perspective in no way displaces RnD from a position of critical importance. Instead, it helps to clarify that RnD is "instrumental", yet is not the point at which target value is primarily generated. The products of RnD (engineering) are not ready to be valued; instead they need to go on through to DnA where the value gets defined through the knowledgeability of the producer.

The important pattern of progression that hosts the emergence of innovation along with other productivity will begin with a *motivation* to manipulate the status quo. Something about the way things already are leaves something to be desired -- in other words, a perceived "need"... Illustrated left to right, the full progression goes on to look like this:

[End of part one. All images copyright 2007 Archestra / Malcolm Ryder]

Posted by Malcolm Ryder at 11:17 PM

July 14, 2007

The Radical Evidence of Artistic Research

Everyone who has ever argued about something is familiar with the challenge, "Prove what you know!"

This provokes a popular and creepy confusion. Taken to its extreme, the challenge even shifts its own point -- from establishing "truth" as a quality of knowledge, to estabishing proof as a quality of technique. That is, what is really demanded is not so much the absolute veracity of the ideas but the circumstantial reliability of "expertise". In that way, for example, the mode of scholarly evidence is allowed to overrun the confidence in artistic opinion. Yet when time has passed and reality aligns with artistic opinion, that opinion is seen (in hindsight) as being "foresight" and -- belatedly if not quite posthumously -- granted its due value, except of course by those who going forward want to co-opt the credit.

What is artistic opinion? Most people recognize it as "intuition", and this discussion recognizes intuiton as knowledge. In what follows below, the point is not to discuss opinions about art but instead to discuss the nature of the labor of formulating and presenting an idea. Two of its three key considerations will be that: (a.) this labor is artistic; and, (b.) the opinion produced by it is a form of knowledge.

The third consideration? When it comes to accepting things offered as "knowledge", we worry only because we need relief from the anxiety of uncertainty. But if we discover that we don't need the anxiety, then uncertainty is not a bad thing per se, and instead it becomes intellectual freedom that allows new knowledge to occur.

Still, looking briefly at the phenomenon of art works is helpful in setting the stage for recognizing this . A work of art "proves" something, but actually all that it proves is its own mechanism of conveying what it is about. That is, it's "proof" is essentially structural, more or less in the same way that a math equation is... but the structure takes its significance (literally, its ability to convey an idea) only from the context of what it is concerned about. The key question about a given work of art is, "why is (or was) its structure important?" And the correct answer will be primarily about that why, not a substitute answer describing the how. The "why" answer will wind up describing what concern was the one to which the structure was responding as it developed -- thus providing the context for understanding the importance of its "how".

In large part, this is what many people can find to be so exactly aggravating about an artwork -- either that it is not apparently concerned with what the observer is concerned about, and/or that the choices made by the artist to develop the responding structure are unexplained. Since there is vastly more art, and vastly more variety of art, than a typical single person has experienced and reached familiarity with, it is not at all improbable for a given artwork to be "about something in a certain way" where the observer is sympathetic neither to what it is about nor to the way it is "about it"...

In moments like that, the observer may have the high anxiety of uncertainty -- of possibly being fooled by something that doesn't actually try to successfully mean anything; by something that might be just "going through the motions" without detectably bothering to try to convince us even that the motions are taken seriously.

But with that same moment there may instead be the challenge of confronting knowledge that one simply didn't have before. And to avoid observer cynicism about the unfamiliar, the moment calls for realizing that not all things can be known the same way.

As goes with art go other presentations of ideas as well.

It might be considered fair for an observer to always ask the presenter to push an unfamiliar idea at least half of the distance towards being familiar knowledge. If the observer wants to accept the idea, and the presenter wants the idea to be accepted, then why not go at least 50/50 on the effort? The answer would be that the producer has typically done far more work already just to produce the artifact for the first time, than has the observer to become exposed to it for the first time. It would appear that the workload starts out with a huge imbalance, as the producer's "half" may not ever be balanced by an equal effort of observation on the observer's part.

The way that this balance is achieved, however, is not by the observer waiting for the presentation to occur and then giving it "equal time" -- but instead by the observer having already behaviorally invested in intellectual openness to new forms of knowledge before the presentation occurs.

For too many serious-minded people, the ability to accept some given presentation as "knowledge" is all bound up in an insistence on some particular technique of "proof" in presenting evidence. In the heat of the moment, their comfort leans, let's say, towards academic footnotings and away from unfettered idiosyncracy. Said differently, it is a competition between citations of historical factversus proposals of theory. In order for theory to be accepted as (conventional) knowledge, the burden of "proof" must be lifted in the form of historical citations. Science, not art.

Well, interestingly, the history of science has the characteristic of revealing that theories are often more reliable representations of truth than is the "evidence" dug up to support them -- simply because in the heat of the moment, the conventional program for generating the evidence just can't get it right, and much later, after that program has been abandoned, the theory is admitted by some other means (e.g. a better program). That is, scientific revolution has always been much more a story about our ability to know something, than about whether what we thought we knew was "actually the truth"... Certainly we do believe that we now know vastly more than we did even thiry years ago -- but the bigger story remains that we now have many more ways of knowing something than we did before. Re-inventing investigation is actually the key to knowledge breakthroughs. And investigation is essentially about actions, not about results.

Let's run with this a bit: the basic activity of knowledge acquisition is the thought process, which is what allows a way of knowing something. What is tricky about a thought process is that if the process is being invented, too, then it is more highly uncertain what it will allow us to know, and meanwhile it can be quite difficult to know whether the current process is conclusive. This is strongly reflected in the saying "a work of art is never finished, rather, it is just stopped"...

But to put things more to our point, when the process reveals something to us, we often hit the pause button and show off what was revealed so far. These exhibits (or "findings") are the knowledge in the moment. From there, they may or may not be formatted for re-presentations. Another option is of course to formalize the process so that the revelation can be re-produced.

Preserving findings for future reference stages the occasions where they may later come off as being "predictions" (literally, "said before"). Case in point: this article you are currently reading is content in the Archestra repository, where the bulk of the material to be found is, persistently, findings from an artistic research mode rather than from an organization of empirical evidence. Even the oldest of the Archestra content, going back to about 1996 origins, most frequently states or argues circumstances in some combination of "what if" and "as if" postures, seeming speculative and not academically rigorous. Yet the oldest of these ideas and assertions are sometimes only now showing up as "valid" in the conventional broad publishing of consulting firms, corporate marketing (especially by IT firms), and the like -- venues where there are customers who immediately demand "prove it!" because, for these customers, investing in uncertainty is an unacceptable risk. Typically, consultants and marketers, once they decide to collect conventional evidence for a theory, kill a significant amount of time and/or money doing that before they bet their business on it. The major point here is that those efforts are not about turning something into knowledge that wasn't knowledge already; instead they are about turning exposure to existing knowledge into adoption of it.

It's a nasty marketing habit to call those conversions "thought leadership", but no one wants to leech the fun out of marketing. At least today -- thanks to the web or other modern tools of exposure, surveillance and access -- we can more likely watch where ideas are actually coming from and get beyond the less benevolent artifices of "intellectual property".

To return to the beginning of this discussion: is there any reason to avoid identifying intuition and opinion as "knowledge" ?? The usual rap against them -- lack of credibility or objectivity -- is so rooted in anxiety over uncertainty that the rap should be discounted except in certain practical circumstances like heart surgery or legal contracting. The supposed alternative -- empirical evidence and testing -- is a power play, but it is so vulnerable to the capriciousness of competition and politics that it, too, should be discounted as an automatically correct default.

But does this mean that neither approach should be embraced? No, only that they are peer opportunities that both need to be understood before either is tolerated or used.

As a matter of "knowledge management", a responsible party must be able to determine what is really being asked for, whether what is received is appropriate to the request, and whether the request is appropriate to the circumstances in the first place. Education (exploring thinking) and execution (acquiring results) are simply not the same thing. Even more basic: does the requester need truth or instead a belief? Facts or confidence? Insight or accountability? As a knowledge provider or cog in the knowledge provision machinery, is your responsibility to provide insightfully truthful facts, believably confident accounts, or some other blend? Can you tell the difference, and is what you provide even the right thing for the recipient to be using?

Posted by Malcolm Ryder at 8:32 AM | Comments (0) | TrackBack

April 28, 2007

Knowledge as Capital

The McKinsey gang examined corporate performance on two fundamental indicators of sustained competitive advantage—revenue growth and profitability—over an 11-year period from 1994 to 2004. Their finding:

"...we found that ...nine companies had higher market-to-book ratios than their competitors did. (The M/B ratio is a measure of corporate performance that compares a company’s market cap with its book value.)...the top nine performers strongly preferred organic growth: they made few acquisitions and divestitures when compared with other companies in their industries...
In our view, their ability to generate value from knowledge-intensive intangibles (such as copyrights, trade secrets, or strong brands) represents a good starting point for further exploration of their superior performance."

Just connecting the dots.

To connect them yourself, log in at The Elusive Goal of Corporate Outperformance -- McKinsey Quarterly 28 April 2007

Posted by Malcolm Ryder at 6:28 AM | Comments (0) | TrackBack

April 22, 2007

The Value of Intellectual Property

Nearly all discussion of intellectual property is intellectually dishonest without the acknowledgement of the most essential aspect: that "property" means "taken", specifically as in "a portion of"...

An extension of this is the matter of what defines "not taken", which must also mean not withheld. Withholding is a major consideration, as in usual practice, enforcing property gets tricky, but most often winds up focussing on the matter of having the right, even more than the opportunity, to take a part from the whole.

But on whose terms do we get the privilege, in the first place,to take? Or to put it more bluntly, at whose expense or benefit is it done -- by which we justify the act?

The following discussion, along with the illustration below, describes the layers of transformation that partition a supply of ideas into an artifice called intellectual property.

I.

Again, on whose terms do we get the privilege to take? Takers would like to think that the terms in question are both ordinary and appropriate in some obvious way. But what is obvious to some of us will often be obscure to others of us. For example, the "I'm doing this for your own good" school of taking is ethically justified as "beneficial protection". But the only thing that makes it ethical is the special reasoning by which it is considered to be "beneficial"... You know the drill: major museums nab artifacts from third world countries for "preservation", and cities nab private homes and grounds under "emminent domain" for developers. Clearly, the trick here is in who really gets the net benefit, which calls for some yardstick. But in my neighborhood, regardless of the measure, gaining benefit at someone else's expense is generally unethical except in sports, crimestopping, or other mutually declared wars.

Continuing to question the idea of just who's good is at stake, look at withholding. Not just a nuance of taking, "withholding" is commonly accepted in ordinary marketing, where the basic idea is to compete for (and win) control of a supply -- control that effectively makes the supply itself "property". Such withholding -- that control of supply -- finds itself ethical only in the same manner as benefits are accepted in sports -- namely, by convention amongst the players. The beneficiary? In this case, everyone playing who agrees to let everyone else "do it too if you can"...

In that scenario, what's actually most interesting is this: before "property" is established, all the fuss is really over opportunity even more than over rights or actual possessions; thus the game can't actually be played without judges and referees who evaluate the fairness of the fight for opportunity.

And at this "pre-property" stage, there is something even deeper. Unless everyone assumes some limiting factor that creates the need for "defense" of the supply, the agreement that condones taking is unnecessary in the first place. For example, in sports, this limiting factor might be a timer, or a fixed number of allowed attempts, or some other arbitrary boundary on a key enabler -- an enabler which could therefore run out or be hard to come by. Without the limiter, you don't need defense, and thus you don't need property.

Likewise, the first gimmick behind conventionally justifying "intellectual property" is to create an artificial limiter. This limiter might be a purely imaginary one, but marketing teaches us that we can make the perceived virtually real, and that's practically good enough.

Before we investigate the artifice of that limiter needed for intellectual property, consider the starkly contrasting issue of the supply of intellectual capital.

II.

Virtually no one knows how much intellectual capital there really is out there, but there is an accepted industrial practice of estimation. Namely, at any given time, the detectable level of supply is virtually created -- by organizations that measure the level in terms of "products" to be appropriated to one agenda or another. In fact, in common across all particular instances or organizations, the standing agenda is to convert capital into products that represent property. Why? Because property is worth more future capital than the amount of past capital consumed to make it.

For these organizations, it hardly matters to the agenda whether 5/10's or only 1/10 of the "real" supply of capital is available, if in effect both amounts are only capable of the same product. So the organizations don't measure the "real" supply, but instead only measure the effectively available part (i.e., not all the supply that there is to hold, but just what opportunity they have to hold, captive, any of it in a practical way.)

Not to say they are worry-free about the beginning level of capital. They do have to work to get some, from somewhere. Ironically, the organizations with the most ferocious marketing of an agenda to "produce more intellectual capital" inhabit the most painfully costly strata of stakeholders' investment (think public elementary schools and Ivy League universities) even though they also inhabit both the lowest and highest extremes of operational ROI (think public elementary schools and Ivy League universities). For the record, note that they are gone missing in the middle. Oh well.

Whatever: so what drives it all anyway?

Answers vary. In some realms, it is possible to think that intellectual property is bought with intellectual capital. This is neither completely hallucinatory nor broadly true. The mechanism that allows intellectual property to appear to be bought with intellectual capital is... politics! -- or in other words, rhetoric.

This shouldn't be taken lightly at all, because rhetoric is the basis of the construct called 'the marketplace of ideas".

It doesn't matter whether that dynamic is being manifested by Gallup polls; or by the Thomas Kuhnian structures of scientific revolution; or by US Weekly, InTouch, and the rest of the pop porn periodicals that duly say Who's It And How. All these examples have the same thing in common. They all show us that our luckiest experience as consumers of rhetoric is to learn that we can believe anything we hear but we might be wrong -- merely perched, anxiously, on the fence between ideas and products.

III.

Forget "mindshare." Instead, consider the two most basic intellectual products: fiction, and non-fiction.

Often, we intentionally choose to ride "fiction". And often, that's okay. After all, there's no special reason why we should be forced to confuse good fiction with truth or bad fiction with lies. As one friend of ours likes to say, they are orthogonal to each other:

When you keep the picture straight, it's easier to understand that what's at stake, usually, is not the thing that gets told but instead the art of the telling. In the scenario above, we'd love to be in the upper right quadrant, but we'll settle for the upper left when we can get it. As audiences, we're all about having a preference for plausibility, and we simply, and usually, require a better performance over any other matter.

For example, what do we learn from Google, the marketplace of ideas? We learn that for a given idea, 86 people will have had it and taken a shot at packaging it, some of them pretty good. Of those 86, thanks to Google, who do we now care about? Answer: not necessarily the name brands amongst them.

So why should the name brands get paid more, and why shouldn't the others get just as much play? By removing (as Google has) the artifical defense of scarcity, we've left old school promoters facing the equivalent of an absolutely thriving black market suddenly declared legit, like, like... Second Life.

What about non-fiction? Here the magic is actually not "plausibility" but the "service" of delivery. Limited service is much more aggravating than limited information, because if the information supply overloads the service, the orphaned information is still not useful,regardless of what it might be about. Our emotional response to service is key. In non-fiction, it's really about tolerance, and in the range of tolerance we go, worst to best, not from lies to truth, but instead from the inconveniently alien to the conveniently familiar.

IV.

Against the production rhetoric of both fiction and non-fiction, of plausibility and service, we have to bring our skepticism, or else caveat emptor. We'll demand that we get a good performance in either case, but in getting it, we have to be sure that the delivery is neither turning non-fiction into fiction, nor vice versa.

V.

In exposing the nature of these products, it seems that their packaging would make them property at least for their producers. But their prospects for success are in the control of the packaging facility; that is, it's actually the facility that is the property.

At this point, let's imagine that the mind is the facility. Then of course it is not the mind's ideas that are the property, but instead the mind itself.

Is it plausible to extend our identification of that mind by abstracting the distinguishing model of its behavior? After all, we can say that the packaging facility called the mind asserts itself by it's repeatable application to the raw materials that it processes. The essence of "property" here is the way that the mind does it.

This issue of "process" makes it worth pointing out that "taking" should be seen differently when the event is "consuming" versus "holding" however briefly. But more importantly, we have to see that when the mind's process has finally output a product such as an idea, withholding the idea from other minds doesn't make the idea "property"; instead, it simply leaves the idea captive, uncommunicated. The probability is that the idea can be reproduced somewhere else, in another property. And, of legal note, the other property need not be dissimilar in order to be an "other". It only needs to be a different instance.

So logically, we can see that many identical intellectual properties can occur, notably by mechanisms other than "copying" one to another. (And empirically, we already knew this to be true, having seen that some great ideas have occurred at multiple points in time or space with no discernable "live" connection of those points.) Not only does this demonstrate that an idea is intrinsically not captive to only any one mind (property), but also that the active restraint of an idea's reoccurrence is truly artificial.

VI.

That realization puts heavy pressure on the dumber ideas held about intellectual property -- the ones which like to flog the criteria of uniqueness and exclusivity in the face of a much more obvious probability that "my" intellectual property may be practically indistinguishable from someone else's.

The full reality is that my intellectual property is publicly interesting only to the degree that either other people's is unavailable or that mine (my mental behavior pattern) is relatively inventive.

VII.

Now we have the terms to untie a couple of knots in the line of thinking about intellectual property.

For example, what is copyright about? It can't be about the final similarity of products, alone, since (a.) re-production is not actually necessarily "copying", and (b.) the ability to reproduce is more likely to be the property than is the product; and (c.) my property need not be any different from another.

Instead, copyright is fundamentally competitive, a limiter attempting to regulate the presence and use of a like property for a like outcome in a prescribed market. Naturally, unless the market itself actually has a prescription (i.e. definition), then there is no artificial or conventional limiter that necessitates a defense of exclusive opportunity.

Copyright specifically intends to prohibit a "same" opportunity to compete. But in a fair market, the convention normally established is about having an "equivalent" opportunity to compete. And finally, where competition is irrelevant, so is copyright.

Next: just as the purpose of intellectual capital is not to purchase intellectual property, the purpose of intellectual property is not to support copyright. This assertion doesn't keep those components from being used that way, but there are no inherent protections or mandates to do so -- except in the agreed conventions of some agenda that has the need.

VIII.

The last area of consideration is to distinguish, in accounting fashion, intelectual property versus "assets". Intellectual property may or may not be an asset. Proof? Ask any artist who is not independently wealthy, or any person who cannot speak the language of his current domestic or local community. How you know what you do know may simply be mis-fit. What you don't know may not hurt you, but what you do know may not help.

But let's get away from the accountant's schema of things and look at "assets" differently. In real life, property is always an asset, but it may just be worthless until it is given a job to do, which them makes it a functional resource. The importance of the resource is what attributes value to the asset. Naturally, if competition proceeds in a way that makes the resource unimportant, then the relative value of the asset decreases. The question is, to whom does it matter? If you take your assets to a different game, or you don't care what game they are in, it doesn't necessarily change the asset in any important inherent way.

IX.

Finally, then, what is inherently important about intellectual property? Intellectual property is a resource, and here's what it's for: the designation of "intellectual property" brands something as a design benchmark for follow-on invention that can evolve or even revolutionize the conditions of the environment. In management practice, the point would be to use it as a base from which to cultivate 5 new offshoots; then take the one or two best of those five and focus all parties on sprouting five more offshoots from that; then trim and sprout again; etc.

Some will see that as just an argument for innovation. But the impact is more profound, as it equally affects all points of the spectrum ranging from renovation, to remodeling, to reengineering, to innovation.

Posted by Malcolm Ryder at 7:19 AM | Comments (0) | TrackBack

February 16, 2007

Mind Canary

For decades, as a precaution, miners have been reeling canary birds down into their mines to warn them of potential disaster -- as the canary is particularly sensitive to toxic gases such as carbon monoxide which is colorless, odorless and tasteless. If the canary dies, then the mine is dangerous.
A mind canary is very similar, with the word "mind" as a play off of the word "mine." If the "idea miner" sends an idea canary into the "mind" and it fails to return, then the mind may be lethal!

Thanks to marketing pro Alan Brooks at Mindcanary.com for memorializing this bit of Archestra legacy. He's adapted it a bit (as you'll see in the wording on his homepage) -- but to good purpose: he's guiding folks to safe mines. Hi Alan!

What do you do with a lethal mind? See "change management" and/or "knowledge management" -- at an Archestra location near you...

Posted by Malcolm Ryder at 6:28 AM | Comments (0) | TrackBack

January 2, 2007

Role Your Own

Note to Sun Microsystems: now, the network is the producer.

Increasingly we read that the new books of importance will be written collaboratively and, in fact, will be Wiki-ed.

Aside from inciting thoughts about the demise of Books 2.0 (remember when Scrolls 3.0 was crushed by Books 1.0?), what are we to make of this?

Well, blending what we generally think about wikis and books, this news presumably heralds the rebirth of the Collective Wisdom.

Or not.

Proof? It was fairly predictable that Wikipedia's own founder would eventually rate it a failure. But it wasn't because people couldn't use it; it was because it was mis-used.

If the "open to all" offering of the production approach is merely a free-for-all, then all bets are off. To understand what is most likely to happen, someone who cares will need to know and cultivate what the real profile of the group effort ought to be, as detectable by the terms of the framework here. In the simplest terms, one should be able to put an "X" in the boxes that distinguish the nature and objectives of the group effort, and leave the other boxes empty, and tell everyone the same story:

Otherwise, one of two things will likely take over-- .the fatigue of herding cats, or the natural inclination towards entropy.

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By the way, due to laziness and working solo, "we" took a really long time with this article, during which Infoworld coincidentally arrived with a more conventional but important review of Wikis. Click it up now, or come back to it afterwards, as you like.
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I.

For the general populace in-the-know, things are still new enough so that when one says "wiki" it likely means the real branded thing -- dubya3 dot wikisomething dot xyz. But already, we can safely say "wiki" the way we say "kleenex".

It's what happens with all perfect products: we didn't know we needed it until we got it, and now we can't live without it -- so we talk about it in an absolute or archetypal sense, and, we don't use upper case.

In saying "wiki", most people already could, and might as well, really mean any of fifty different but similar online-powered production collectives -- whether fragrance free, textured, twin ply or whatever -- instead of only authentic Wikispots. For most people, the obscure technical diffentiations of the exact underlying brand of technology are unimportant: the main attraction is always the same -- functional collaboration. Collaboration is hot.

What we still have to worry about, though, is that "functional" part -- the part that gets wisdom out of the collective. Understanding the nature of the collective is more work than many care to worry about. Working together has never been more convenient; but is it a community, a workshop, a studio, an archive, a marketplace, or what? In other words, how is the collective managed?

As for the big rebirth, let's curb our enthusiam... It isn't proven yet that wiki wisdom is superior to any predecessors - it simply collects a hell of a lot faster.

II.

That might be cool, but inevitable or indispensable?

Nahh. This is an option or tactic, not a sure thing. Being online facilitates a higher speed of cooperation, but if you don't know where you're going, it doesn't matter how fast you get there. As for being indispensable, if you don't know any happy people who do not use and do not need a wiki, then you should get a bigger life than the one you have.

If you want to be a contributor yourself, though, life is good; wikis make donating easy. Now, that irresistable urge to share is covered.

Still, we can't assume that the effort to contribute to the production will wind up making the final product important. Now it's more convenient than ever to make bad stuff as well as good stuff. Meanwhile, getting a lot of bad stuff will make the novelty of this production wear thin really fast -- leaving it not much more important than anything before it.

Easy donations are just the starting line. If this is really going to work, then somehow the good stuff has to come about because of the way that the donations get handled.

Beyond the hype, the real story of the online collective is about the open-invitation supply chain versus a discriminating value chain -- when open-sourcing and authority mix in production.

III.

Deep within the cloudy buzz of collaboration, open-sourcing is the great (we believe) new extension of production mechanics. But great for whom? The null hypothesis isn't that open-sourcing is magically delicious, but that adult supervision creates collaboration from open-sourcing -- when collaboration has some specified advantage for the supervisors. It doesn't just happen by itself.

Probably the most generic form of collaboration is the workshop. Collaborative workshops, whether for making books or something else, are not new. The online part isn't even new. (Remember Compuserve?) But since we don't need collaboration to make a book, and we don't need a workshop to make a book, what the online collaborative workshop actually does of importance is bring is a workshop discipline to all comers.

IV.

Challenging that, one of the most popular supply-side notions of a collaboration is inclusiveness: the idea that anyone who can pass muster can contribute their labor to the works. While this has normally resulted, actually, in an advantage (cost) for the main producer, what's greasing the wheels on lots of the new online stuff is on the contributor side. Namely, thanks to the tools, there's not much muster to pass. For skeptics, this threatens the ambition for quality. But on the other hand, some thinkers propose the distinction "peer-production" as a way to indicate a "flatness" or absence of excessive hierarchy in the natural diversity of production roles. Is this stance a breeze of creative enlightenment, or merely political correctness? You be the judge.

Another, older spin on this flatness is the idea that the membership of a collaboration is a community gently floating in "equal rights". But that equality really applies to the benefits, not to the producing: it isn't equal opportunity. Community-based production is usually not "peer". Why not? Remember that when the producer is "the community", the community typically embraces a wide variety of roles in the production to be sure it gets what it wants, some supervisory (or "leader") and some not.

V.

With a product like a book, we also get the connotation of an outcome having quality -- here attributed to concentration of the kind from a studio. In a collaborative "studio", getting from the labor to the works -- from the acts to the results -- is not just a collaboration. It really is a study, whether it's collaborative or not. The ongoing study itself is the main point of the studio. Not a product, but a process.

Facing that fact, we'll frankly note that some people study better than others, and that the attraction of "innovation" is not necessarily a given objective of the studio. We bring this up because it might be that many people find innovation sexy and studying not sexy -- leaving an online studio with a couple of inhibitors that push many early enthusiasts into the trough of disillusionment after the initial blush of procedural simplicity. Production is not easy, whether there are hierarchies or not.

Meanwhile, even for studios that are targeting innovation, neither is collective production usually "flat" -- otherwise, we'd only need to post the old Suggestion Box, and cool things would just sprout from it into realization. (Instead, our experience is littered with stymied suggestion boxes, probably outnumbered only by dormant "collaborative" websites).

Normally, delivering value features some complexity, which confronts the ersatz participant seeking the warmth of collaborative inclusion. For example, the ongoing effort conducted by a collaborative studio typically has a topic -- like "ferrous glass" or "business-IT alignment" (or perhaps even "How To Make A Book") -- and the topic will immediately triage at least some potential participants. Then, beyond self-selection away from or towards the topic, there is generally some authority conducting a further ultimate triage. Why is this authority there? Well, for example, the benefit of participation in a studio is aimed at promoting the value of its topic; and where participation is not seen to be promoting the value of the topic, that participation gets weeded out.

VI.

As a great benefit of online contributions, exploration for "supply" is scaled up by orders of magnitude without extra cost. But if the the collective takes on any responsibility for generating groupwide benefits, then it must decide whether it wants to find value in whatever suppy it receives, or instead wants to vet the supply for its fitness to a predetermined value. That is, the responsibility of the collective is still to convert the supply into value.

Call that governance or go-to-market, the basic problem is the same.

What's interesting is that to be a community, the collective has to declare a self-interested group need for one or both of them, or else it has little claim to actually being a community. This is the authority of the community. It begins to make the gap between participation and importance fairly explicit, and weaker participants fall into the gap.

Yet these Darwinian consequences are not even the interesting part. They miss the bigger point and breakthrough of the collaborative environment. Namely, who needs community, anyway? What we really want is not community but that underlying production network, and this difference is now much more explicit due to wikis.

VII.

Having something like Wikipedia lose credibility (and thus fail it's mission) is disappointing. But the story might not be over yet, anyway. A general difference in the collectives that wikis foster is between collectives pursuing connoisseurship (quality) versus ones pursuing entrepreneurship, and a switch in direction is not out of the question.

In the case where an "online collective" commits itself to defining new value from its available content supply, the most common cycle of events is that someone in its communications network proposes the value, and the rapidly expanding acknowledgement of it creates a demand that can be met by the incredibly rapid supply of uninhibited contributors (suppliers) in the same network. And when membership in the collective does not require prequalification, the communications network expands exponentially. What isn't predetermined is who will come up with the good idea. For the source of the idea, if everyone has to agree on who has the "good" idea, it's a problem. But if the idea can simply find its own audience, then for the source it's pure opportunity.

So, for example, is there a particular need for, or interest in, Valentine's Day jokes for divorcees? Let's find out, in an online production network. The cover story here is not that these particular jokes might become a success or not, nor that the network should get seriously focused on divorcees or holidays or jokes, but instead that anyone in the network could come up with it and trigger its pursuit. Anyone in the network can now be not just a source but a producer. What's needed from the network is its natural ability to grow itself, and the ease that it offers the individual in finding a hospitable sector.

This doesn't mean that everyone should be a producer, and certainly it doesn't mean that most will be any good at it. But now the opportunity is there.

Posted by Malcolm Ryder at 2:07 PM | Comments (0) | TrackBack

December 26, 2006

KM and "the Need To Know" Basis

If you're a provider of knowledge, then blogging, social networking, globalization, and other developments ought to be so liberating. The payoff: orders of magnitude more audience for you.

But somehow, it's turning out to just be disappointing. The downside: these changes are actually more work! They have made it far more important to understand how information can travel and how it gets contextualized as "knowledge". Anything you send out might get more abuse or misuse than use.

AND what's worse, the fun of being exclusive isn't there. It's all... less grown up. You have to regress to the old "party in your head" instinct of having more people involved just for the sake of having more people involved. Otherwise, it turns out that you're working a lot harder to be noticed (as opposed to merely exposed), and right when you are noticed, a bunch of people just like you get noticed too -- and it's not even clear that they worked hard for it; why should you?

I'm not happy with all this freedom. Call it an open market if you like, but when information is free, only bums will have information.

All this unrestrained circulation reduces your knowledge to information. Ouch. What are you gonna do?

Well, some knowledge is really, in the first place, just information that is appropriate to a needed decision. In fact, it's not the provider that gave the knowledge, it's the needy recipient that makes it out of the information. In this case, they don't need your stinking knowledge; mere "data" would suffice. What's finally being called "knowledge" here is simply an awareness of facts -- not the provider's awareness, but the recipient's. [Note: clearly, you have to pick your audience.]

Gaining awareness and gaining facts are bundled together in that thought, but they are rudely separated in action. Unless the facts seem appropriate, gaining them is not what amounts to "knowledge" for us. We don't value awareness of facts that we don't care about. Without the value, we don't think of the awareness as knowledge.

This indicates that, because of a difference in context, one person's knowledge always risks being merely another person's information. [Note: send the context along with the info.]

Of course, there are conventions formed to brand certain classes of information more "absolutely" as knowledge. "Instructions" come to mind. Providers who subscribe to the convention enjoy some confidence that their information exchange really is knowledge transfer, because they are aware, in advance, of how it is likely to be used. But we know that it's sometimes pretty hard to understand instructions; after getting them we can sometimes still feel like we don't know anything.

The thought here is that the information may originate as knowledge, but in transit it is just information again, and then it arrives in the recipient's processing where it becomes knowledge again -- or not...

In other words, knowledge is not a material -- it's an effect. It's a condition, different from information in the same way that being amused is different from a joke.

Here's no joke. An article in the "news" says that 2% of the world's population owns over 50% of the world wealth. Some may say that they've heard it before; but this time it comes from research. The warm aroma of validity wafts across the counter, and where before if we thought there was only opinion (and not even convention), now there's "knowledge" again... this time, our own willingness to believe. Frankly, this is the kind of information that many in positions of authority would not like to have circulated. The whammy is doubled by the further news (says Anuradha Mittal of the California-based Oakland Institute) that "unfettered free trade tends to benefit the wealthy at the expense of the poor".

Speaking colloquially, is it safe for everyone to know this? Or, asked more along the lines of the points made earlier, should this info be passed around strictly on a "need to know" basis? When you think about what people might do with this information, you can understand why some authorities don't want people to "know it". (gasp! say it ain't so!)

This makes us ask about what's going on when managers "manage knowledge". What's the deal? [Parents of preteens, don't get cocky. What follows is not what you're thinking already.]

Here, the key aspect of management is the designation "information of note", which we observe is just like the police designation "person of interest" -- i.e., not quite a suspect, but not quite scott free either. Hey, you there, stay in town, and be ready to answer questions.

Rounding up persons "of interest" is kind of a stretch of our tolerance, but its a practical strategy for the authorities to acquire the person that they eventually really want, so that they can do what they really want to do: charge someone!

Paralleling that, perhaps the real basis of practical knowledge management is strategic roundup of information . But what makes that containment (content!) strategic is not the information that's rounded up; rather, it's what you eventually get people to do with it. -- which is what makes it interesting.

Net: the beginnings of knowledge management are in organizing people to use information in a certain way. Then you have to aim the information providers at those uses. [Note: oh yeah, libraries..]

Posted by Malcolm Ryder at 11:10 PM | Comments (0) | TrackBack

December 23, 2006

Street Cred versus the Uncommon Knowledge

In the world of expertise, knowledge is power; but power isn't enough. Knowledge and expertise go hand-in-hand, but if not for marketing, the value of knowledge could be largely undetermined.

Before we go on with this, prime your pump with this holiday sampler of pieces from Jack Vinson at Knowledge Jolt With Jack. Jack writes about knowledge management, personal effectiveness, theory of constraints and more. He's offered a quick tour that you can take at your leisure, in handy categories. Definitely do the first one, if your'e squeezed for time:

Expertise:
http://blog.jackvinson.com/archives/2006/11/22/clay_shirky_on_expertise_again.html

Expertise locators:
http://blog.jackvinson.com/archives/2006/06/23/expertise_locators_on_the_brain.html

The KM keystroke:
http://blog.jackvinson.com/archives/2006/09/06/f1_as_the_knowledge_management_key.html

Definitions:
http://blog.jackvinson.com/archives/2006/08/29/km_definitions_from_my_perspective.html

Jumping into the fray, here's my pitch:
Knowledge is content, but by itself it isn't product. In the markets, "expertise" is the packaging used for knowledge transfer. Its point is to convert contents into applications. Applications! Now there's a product.

This is why it actually makes sense to hire experts; that's how you, as the consumer, access the knowledge. And yet there still might be an issue of customer satisfaction; what if the expertise doesn't bring the knowledge you really wanted? It's not that it couldn't -- just that it didn't. Is that aggravating, or what!

This ultimately highlights the issue of value: when we're shopping for expertise, we're shopping for knowledge delivery, not necessarily for the knowledge itself. In the end, the credibility of an expert is usually about his track record of delivery. It's nice if that credential is based on delivering under real-world pressure, not just under pressure of exams. But let's not get distracted: we know the knowledge is out there in many places, and we want the credential to tell us the best place to get it.

This helps explain the difference between credibility and authority. To the point, we can think of authority in terms of "authorship" -- nothing less than the virtue of having defined the knowledge in the first place and thereby being its master. Authority is at a different location than credibility in the knowledge supply chain. It's not the distributor or the retailer, it's the manufacturer or producer.

Consequently, the more we are determined to get right to the knowledge and skip the packaging, the more we're predisposed to cut out the middle man: experts.

Of course, cutting out the middle man leaves us with a situation:
- we either have to do more work (shopping), or
- we have to accept that what we buy may not be the best of breed.

In the first case, we probably want to be lucky; and in the second, we probably want to be... smart!

My favorite practical stance on that is all about being able to accept what happens.
- In the former case, it's the first rule of shopping -- After you've bought it, stop shopping.
- In the latter case, it's the second rule of shopping -- You're not perfect, but you're perfect for me.

This practicality isn't very sexy. Being your own expert is just not the same as being someone else's. But the good news is, not being someone else's expert isn't going to hamper you in getting your hands on authentic knowledge.

The bad news is that you might be competing with other people's experts, to get your hands on it first, before they obfuscate it with packaging.

In the Web Do Dot Oh-ver era, the biggest problem is getting faked out by electro-powered shoppers and distributors posing as authorities. Be forewarned, they might be merely experts.

Well, gotta run; my unauthorized autobiography is overdue at the editor's.

Posted by Malcolm Ryder at 5:18 AM | Comments (0) | TrackBack

December 1, 2006

The CMDB as a Knowledge Base

An executive overview.

In the front-office world of a business, the holy grail of a "360-degree view of the customer" is already old hat.

Well, much of what is now happening in the middle office -- the IT world -- revolves around the criticality of utilizing a "configuration management database", or "CMDB". This database is the key to a 360-degree view of any IT asset. In particular, it is a centralized repository of information about how items are defined and situated as components of the information technology infrastructure on which the business runs.

As a singularly authoritative (or "master") source of information about the infrastructure's components, the database content is very involved in the documentation and decision support for almost any business process workflow requiring IT enablement. But what is it about the components that the CMDB describes?

Typically the components for which the CMDB holds descriptions are referred to as "configurations". A quick survey of the CMDB literature shows that would-be CMDB users can get mired in great controversy about what consitutes a configuration, because there are so many ways to segment a chunk of infrastructure IT and legitimately call it a component. After all, the notion of a component necessarily refers to the idea of some larger entity that the component helps to make up. The problem is that any entity's distinctive identity must be defined with a boundary around its scale, complexity and purpose -- but just as any category may be said to be a subcategory of something else, any entity may be a component of some other entity. Thus it may be unclear where to draw a boundary, create an object, and call it a "configuration". The question always begged is "of what entity is this item a component?"

This makes it very difficult to decide what to include and exclude -- the CMDB's catalog of entities should be neither too general nor meaninglessly specific. How many levels of categorization and subcategorization (so to speak) must the CMDB contain?

In the below, we skip all of that confusion by looking at "things" in a more objective way. First, we take the notion of configuration not as a noun but instead mainly as a verb that has a result. The focus is on the motive for action. That is, nothing in the IT infrastructure is there except through the labor of making it fit into the company of other things -- and our first emphasis is on the labor that takes place to respond to the perceived need for including something that wasn't there before. This allows us to think of a "configuration" as the output of a system of functions, and the CMDB first of all collects facts about that output (and other ones, similar or related, in the same infrastructure ) -- as accounted for by its system.

But why collect the information? The primary reason is to put management of these outputs on a foundation of knowledge instead of on hunch. The CMDB's content can fuel knowledge by organizing its information into the three main contexts that matter to the difference between being managed and unmanaged.

Managed conditions always compare the actual against the planned and the authorized. This indicates three forms of knowledge that the CMDB would support: respectively, models, analyses and histories.

The essential CMDB content will be descriptions of states generated by the functions (as illustrated above), to be evaluated in these three contexts.

However, management tends to root itself in the posture of "operations" -- with the difference being that operations are mainly about organizational responsibilities while functions are about activity. This distinction is more profoundly yet simply identified in the hierarchy of management as shown in the next table. Top-down, starting from a focus on business value, the table rows address the questions "Why are we doing something?"; "how are we going to do it?"; and, "what are we going to do it with?":..

It is easy, then, to recognize the same top-down pattern in management's attempt to associate the needs of the business with the infrastructure that would address it.

Arguably, tactics are derived from respect for the customer's agenda, and functions leverage the offerings of suppliers -- so the primary challenge for differentiated management is in the operational dimension. Not surprisingly, Operations lays out responsibility areas in a way that tends to generally reflect functions. For example, the operational chain of development/implementation/administration/support is, on the surface, an echo of the functional flow of build/release/monitor/maintain. But Operations must intentionally, not coincidentally, associate its responsibility areas with the functions it can govern, if the dynamic is to be called "management". Operations must decide what functions will "execute the infrastructure" and how.

Consequently, what management wants from the CMDB is content that helps construct the artifacts of management that should populate the following framework. In this framework, captured knowledge explains how Operations currently puts functions into the context of the bigger management picture -- the one that generates business value. That overall knowledge-based governance looks to the CMDB to fortify its perspective and acuity on what to change, when and why.

In the above article:

Posted by Malcolm Ryder at 11:14 PM | Comments (0) | TrackBack

October 17, 2006

Where's the "System" in Managed Knowledge?

Swimming around in phrases like "knowledge management" is easy until it comes time to actually do the management. The abundance of innovations for promoting the transfer of knowledge from point A to point B is exciting and often dramatically leaps over old barriers to practicality. But just getting knowledge moved around more readily is no guarantee that any significant achievement results from the activity. By comparison, if our wariness of email's excesses is any indication, we gave up on that kind of naivete long ago.

Yet, getting past the romance and denial in the "knowledge management" label is something most users of managed knowledge would like to leave on someone else's To Do list.

If that To Do list belongs to you, a major first step is to note and remember that knowledge exists in an environment, not in a container, and knowledge users roam all over the environment doing spontaneous and therefore frequently unpredictable things. The idea of transferring knowledge from A to B is about hitting moving targets with items you first have to catch.

To start catching the important items, it helps to categorize them according to why they are useful to you and to the presumed recipients. The users themselves also should be categorized according to what we can expect them to do about what they receive. Otherwise, the constant risk is that you don't get the right thing to the right user at the right time, meaning that the effort is somewhat wastful and, what's worse, discrediting to further efforts.

Taking the idea that the recipients should get what they actually need, the high-level perspective on managing knowledge has to do mainly with context-sensitivity. In pursuit of repeatable, optimal, reliable context-sensitivity, the mechanics of managing knowledge have to take care of combining a knowledge "supply chain" capability with a knowledge "value chain" capability. In the picture below, this combination is represented so that the reasons why anyone should care are exposed at the different points between "not knowledge" (lower left) and "full knowledge" (upper right).

In this scenario, most users are "consumers" and hang out at the upper right. Wandering leftward brings more and more responsibility to be a "producer" -- taking what is there and driving it right-ward, or at least making it highly available and suitable for that. Going from left to right, the "Who Cares" factor goes higher and higher. Having an idea is fine, but packaging it makes it more valuable, and targeting it to a matching audience tops out its probable value.

Meanwhile, going from the bottom of the layout to the top similarly sets up responsibilities and value-generation. Here the most important thing is to handle the transformation of data first into information and then on into knowledge. We already have various repositories that we think of as systems for separately managing the three things . That is, we can point at a data base, at an information base, and at a knowledge base. But often users don't distinguish them from each other, counting on a wild array of tools for search and analysis to force transformations (i.e., "interpretations") from whatever base the user starts with.

If knowledge is really being managed, then instead the different responsibilities of the repositories won't be indifferently violated. For example, what should a database contribute to knowledge transfer? At most, a focus on (i.e., selection of facts according to) a defined subject. Heading upward, an information base should emphasize the ability to associate the data with the circumstantial need. A knowledge base emphasizes the perspective of the user who is actually in that circumstance.

If knowledge is systematically managed, there will be clarity about what kind of value is being generated at the different points in the process of making, saving and delivering it, and users will not hop around randomly in this production environment but instead be guided through it appropriately in real-time as they work.

Posted by Malcolm Ryder at 12:33 PM | Comments (0) | TrackBack

October 16, 2006

Harmonic Convergence

Welcome to the harmonic convergence of new-wave KM where, in the (flawed) holy triumvirate of People/Process/Technology, it's sometimes hard to tell whether the people are processing technology, or whether its the technology that is processing the people.

By now, it is already mainstream to think of blending blogs, wikis, search, and business intelligence into a hyperethos of "smarts". IT industry writers such as Michael Vizard at Ziff Davis go so far as to say, "This means that companies for the first time might actually be able to figure out who knows what, and when, within their organizations in real time."

Academics haven't changed their outlook a bit, however. Serious researchers rightly refuse to confuse data, information, and knowledge, understanding that crucial transformations must occur in order to get from data to info, and from info to knowledge. Taking that as a cue, and as the only one that we need, our understanding of a "process" for managing knowledge clearly embraces an expectation that systems will be developed to power and control those transformations.

Is it just me, or do you agree that the Card Catalog is still where the bar got set in knowledge management systems? When I was five years old, I learned how to use it and it worked for forty years virtually unchanged. It even withstood, without blinking, the unmeasured nuclear explosion of bad poetry brought on by the advent of the home word processor. I sometimes wonder why "management" people are so eager to dismiss the discipline of library science and insist on hot dates with so-called "self-managing" or "organic" content.

That is, let's not forget that the user-community for knowledge is not homogenous, and even unscientifically it can be confidently separated into roles like managers, knowledge workers and line workers. In a business, these roles are distinct, are actually held to some standards of accountability, and a lot of what passes as "process" exists mainly to avoid having these roles waste time. These aren't per se "knowledge management" processes -- they're work management processes. Knowledge isn't supposed to be magical; it's supposed to be practical. How does it get that way?

Interestingly, the card catalog is brutally efficient. It just doesn't work well until you learn how to use it. But when you've learned, it works for two key reasons: one, it has built in accounting; and two, everything it knows about is formally published. Let's see: if you were paying someone out of your pocket to be responsible for assuring those two characteristics, do you think you might call them a "knowledge manager"?

I'd sure hate to go into a library where the catalog was missing, the shelves had all fallen over, and anyone could arrive and poke around adding, moving, or removing whatever other materials they wanted. Unless, of course, I was there for recreation. Oh wait, that's why we surf the web!

But surfing on my boss's dime is a little different, don't you think? If newer and newer technology is going to bring about maturity in new-wave KM, the technology is going to have to get primarily focussed on making management processes better, and only secondarily on making more and more spontaneous content sources continuously reachable. In a business, the purpose of KM is to integrate two proceses, content management and work management , in order to improve the content of work! Until then, the convergence of the technology innovations is going to continue increasing the dissonance instead of the harmony, the noise instead of the signal.

Posted by Malcolm Ryder at 9:08 AM | Comments (0) | TrackBack

October 9, 2006

The Knowledge Tax

Here in the knowledge economy, life can be very taxing.

Doing research involves looking for:
- things that you don't know exist,
- to get reliable information that is new to you
- about things that you want to know.

So from the start, you have pretty significant uncertainty at the basis of your effort. Moreso, when researching concepts, it's often unclear as to whether the information, terminology, context, etc. that other people have used will allow you to readily recognize the same thing that you were looking for, when it is right under your nose.

So some kind of map is needed to guide you to the right needles in the haystack of research.

A taxonomy is a "custom dictionary" of categories. It tells you which particular terms are going to be used as the "working labels" for certain groups of ideas, for how those groups are related to each other, and therefore for how you might confidently categorize examples of those ideas. So we use the taxonomy (categories) to zero in on examples. Taxonomies create the aisles and shelves in the grocery store of knowledge.

But then there is also ontology. An ontology is more like a belief system -- in this case a set of beliefs about how things "really are" and why they are that way. Ontologies are heavy duty because they do a lot of editing in the same way that we think of "design" shaping things up.

What's interesting about ontologies versus taxonomies is that when a professional taxonomy gets imposed on a cultural ontology, there's a big struggle to see which one of them is going to re-arrange the other more. You don't get arguments about whether a chair is a chair, but you get arguments of another kind.

A taxonomy might look at a space and say "You know, this could easily include, or could be, a playroom."
In the same space, an ontology might not say "there's no such thing as a playroom," BUT it might say "this is a chapel; we don't acknowledge playrooms here; there is no playroom."

Brutally oversimplified, and relative to each other, taxonomies are more data-based, and ontologies are more point-of-view-based. Taxonomies don't care who is looking; ontologies do.

The Free On-line Dictionary of Computing (Denis Howe) says, "Formally, an ontology is the statement of a logical theory..." but it goes on to emphasize that the logic is something shared, like the shorthand lingo of an established social group, which has decided what qualities of something matter the most and can categorize them that way. Our favorite example of this is from an essay by Jorge Luis Borges, cited by Joe Celko in Intelligent Enterprise magazine, called "The Analytical Language of John Wilkins. In it, Borges presents a Chinese Encyclopaedia named "Celestial Emporium of Benevolent Knowledge", which categorized all animals in this way (note various copyrights for Borges and Intelligent Enterprise):

- those that belong to the Emperor
- embalmed ones
- those that are trained
- suckling pigs
- mermaids
- fabulous ones
- those drawn with a very fine camel's hair brush
- others
- those that have just broken a flower vase, and
- those that resemble flies from a distance.

On the other hand, in a taxonomy, there is some presumed (and presumably demonstrable) set of what everyone insists on calling "natural" relationships. More surely, the main distinction is that the relationships respected are "scientifically systematic". The facts in question are the ones that dispassionately glue the classifications to each other and to their sub and sub-sub classes, and would be seen the same way by all scientifically careful eyes.

Oh well, imagine trying to get credit for proving anything, without a taxonomy to stick up for you. It's the price you pay for a better job in the knowledge economy. But cheer up: there's always marketing and its genius of turning taxonomy into ontology... a well-tested way to try to get your money's worth.

Posted by Malcolm Ryder at 4:05 PM | Comments (0) | TrackBack

May 28, 2006

Web What.dot.ever

I hadn't been able to put my finger on what has aggravated me so much about the phrase "Web 2.0". But the May 26 posting on Boing Boing by Cory Doctorow nailed it.

Usually, the nature of my annoyance with phrases like that is easy to pinpoint: namely, that I didn't think of them first. This aggravation is a healthy Stage 1 denial that is not too hard to flip into grudging respect for someone else while still being entertainingly pissed off in private. But let's face it, grudging respect only gets you points if the subject of the grudge gives a hoot about whether you do or don't come up with it. As Woody Allen riffed so long ago, what's the point of self-awareness if no one else notices that you have it? Although he explained it in the perverse ("I would never join a club that would have me as a member..."), he got right to the point.

Stage 2 denial is more like self-defense. Sometimes the target phrase of my distaste seems like a gratuitous dare, tossed out on the table like casual porn to see who in the room is either dumb enough to drop their cover of propriety and pick it up, or stupid enough to be manipulated into showing their low brow by dwelling on it even when something better was readily available. Resistance to being manipulated like this is identical to my rehearsed disdain of most (but nowhere near all) junk food: if it was my idea to have some, I still wouldn't tell anyone that it was my idea even if they caught me having it. Briefly, I had thought my initial bristling at the phrase "Web 2.0" was mostly of this sort.

But now, thanks to the posting on Boing Boing by Cory Doctorow, I'm comfortable with acknowledging a Stage 3 denial of the phrase, in which (this time) it is necessary to proactively ward off intellectual colonialism by fashionistas parading as "thought leaders". Truthfully, even at Stage 3 Denial, where you're blowing energy that could have been spent better elsewhere, there is normally still some entertainment to be had. The way you have fun with it is, for example, to choose a team and root like hell for it -- even though you know another team is probably better. The fun in this is all in the choice being willing, so much so that underdogs are actually more appealing than smug habitual winners. And the point is to not be told how to think. Furthermore, what's fun about rooting for teams whose winning just makes them smug? They're not more right for being winners, they're obnoxious. Ya just wanna smack 'em. The 1997 NY Yankees: "We want you to crave baseball all the time, but only if you're watching us." Whiners.

Parkinson's Law says that "buzz" will always expand to fill the volume of any container it is put in -- including the one between your ears. Insidious. Bad. Like millions of other folks, I just didn't know who coined the phrase "Web 2.0" ... Nor did I care, because, well, I hoped it would soon enough auto-inflate beyond the point of any gravitas. Yet more importantly, right at the beginning I sensed it trying to crowd out other thoughts and airtime around me. Then, Doctorow's Boing Boing post named names. Now I know that O'Reilly Media birthed the beast, and because they chose to be obnoxious about sharing it by handcuffing it to their lawyers, I can't retroactively grant them mere Stage 1 or Stage 2 denial. O'Reilly: "We want you to always be thinking about this as much as possible, but only if we tell you to!" Whiners.

The question we should ask is, if no one ever again said "Web 2.0", would there be even the slightest significant dip in the ability to talk about or understand what might happen next between the environment of the internet and the environment of consumer mentalities profit and non?

Duh, no. For starters, the idea of "the web" is not nearly as interesting now as "the channel", and even monetizing personalization is old news. In fact, the more interesting shift is not from Internetworking 1.0 to Internetworking 2.0 (which probably happened eight years ago), but instead from content personalization to access personalization. Gimme streaming hi-res Tivo'd podcasts of "Lost" and grad-school courses, with voice-activated search -- and no, I do not want to screw around with the plotlines. I do want really thin fold-out widescreens on the iPod, though. And/or a projector button, good enough to size and throw the image on an 8.5x11 piece of white paper.

And here's another "no". Is there any chance that only O'Reilly can explain what O'Reilly calls Web 2.0 as well as O'Reilly can? Uhh, no. Further, is there something I now understand better about Web 2.0 than I did yesterday before I knew O'Reilly had anything to do with it? No.

Really, the irony is that because the web 1.0 works pretty well it is much more likely that I could continue to go far not knowing or needing that O'Reilly be involved. Nonetheless, does O'Reilly have a vested interest in the fruits of promoting the attention to the future of cyberspace under the Web 2.0 banner? Sure. But giving them credit for the phrase is way different from giving them cash for it. Not only do I refuse to use the phrase Web 2.0 with anti-litigative quotes around it, I'm basically disinclined to use the phrase at all. So there.

Bonus Beats: For more fatiguing commercialism that makes you crabby, let's dwell on the stupidity of the Beatles suing Steve Jobs. I mean, really. Although, now we have a new twist on the "apples to apples comparison" idea. (What? You mean all this time, they're not alike?) Where we need this one to go is to have Jobs sign up Pez to do Paul McCartney bobblehead iPods, in time for the Christmas rush.

Boing.

Posted by Malcolm Ryder at 11:10 PM | Comments (1) | TrackBack

May 5, 2006

Does IP Matter?

When information of all kinds is so continuously ubiquitous, then what difference does it make who it originally belonged to?

With just the slightest yet obvious nod to one Nicholas Carr and the raw nerves he plucked with his essays on "Does I.T. Matter?", we lean onto the parallel slippery slope of I.P. or "intellectual property".

Topic: we know what the point of being "intellectual" is. But what is the point of the "property"? What difference does it make, and why should it?

With the internet making re-production of textual and visual statements such a "no brainer" effort, it's worth noting that a lot of what has ever been stated is just junk, about which in turn rears the question "who cares, anyway?"

This relative circumstantial worth, dependent on who cares, is the most interesting test for framing the value of so-called intellectual property. But it doesn't explain where the value comes from, which is the bigger part of the story.

That is, where the notion of "value" is involved, It's not that the statement in an intellectual property is smart; rather, it's that someone had to make it make a difference:
1 - the statement is a produced artifact; and,
2 - the artifact risks exposure; and,
3 - the exposure risks usage; and,
4 - the usage risks generating benefit or liability.

Each of those four conditions is a point that someone may care about quite anxiously but perhaps not a whit. Regardless, each point offers an opportunity for some kind of claim on merit to be credited to someone.

In effect, each offers a type of value -- which makes people want ownership of what they did. Respectively, they would be:
1 - producers,
2 - promoters,
3 - providers and
4 - sponsors (investors).

Normally, what looks lke fighting over property is really fighting over the credits. Why? Because the credits are what is supposed to justify a claim to any benefits. The trick is to understand which benefits ought to be claimable due to the different credits.

I.

Starting with the notion of having an "artifact" goes hugely towards dividing sense from non-sense about I.P.

By definition, an artifact is a product of labor. For those of us who take thinking to be an act of labor, it's easy to take even thoughts as artifacts; we save and store them as "ideas", and we really appreciate the mystique of solo originality attached to them. After all, that is the initial basis of making claims of artifact ownership. But on close inspection...
- "Solo" need not mean only an individual person, but instead just a singular distinctive workgroup of any size. The basis of the group's distinction is the most critical point of reckoning!
- And, in an unrestricted environment of information exchange, "original" thinking (i.e., idiosyncracy) does not necessarily result in "original" (i.e., new and unique) ideas. There are just too many thinkers. Nor must original ideas come from original thinking -- since sometimes they come instead from luck, mere observation, or someone crafting the same thing as someone else before but better enough to finally be notable.

This deflation of mystique points out two things:
- our voluntary labor may or may not hold the slightest bit of anyone else's interest, although we may lay claim to the labor regardless; and that...
- the product of our labor might be interesting more due to its availability than to its origin.

So if we will next desire compensation for exposing the artifact, there are those two issues to consider. What is not supported, yet, is getting beyond desire -- to the notion of having a "right" to be compensated. At this point in things, unless there is a contract that says the labor or the availability must be paid for, then in fact there is no requirement for anyone to offer any compensation.

So this starting set of "artifact" issues sets the general tone of "Who Cares?" ... That is, we might go through the motions of formalizing some labor product as an "artifact" in order to give its distinctive identity some external recognition, but even if we do, who cares?

II.

The next step, risking exposure of the artifact, often kicks in when we decide that we either want to package the artifact or distribute it. Aiming at determining value, the defining questions here are also pretty basic:
- who is the packaging and/or distribution intended for? And...
- who is doing the packaging and/or distribution?

In both cases, the answer can be "no one". That is, as the baseline scenario, let's imagine first of all that there was no intent by the producer of the artifact to package it, nor to distribute it, to anyone. Exposure of the artifact could still occur due to chance or exploration. The worst case of exposure would be from illegal surveillance or in a sense "trespassing" -- but to stress the key point here, avoiding such visibility and access starts with recognizing whether a venue is "exposing" and it continues with not putting or leaving the artifact in a place like that. So, think of it as privacy, prudence, or whatever: if exposure is unintended by the producer, what if a second party discovers the artifact and decides to do something with it -- namely, to package and/or distribute it? What value is about to be created or destroyed? And why do they need permission?

First, distribution. Distributing the artifact can be done with or without packaging, but let's ask whether there is value to distribution without packaging. If availability of the artifact to broader discovery (exposure) is important, the answer is "yes"... That judgement of "importance" immediately points to the influence of a context (again!). Exposure is a possible outcome of distribution, but again, who cares? Distribution per se may have no discernable value. But discovery is the flip side of exposure, and the value of distribution is not derived from the artifact itself but instead from the occasion that a discoverer gets something from the experience of discovery.

Meanwhile, there's packaging. An argument clearly exists for assigning new merit (however slight or substantial) to the labor of the packaging; the packaging also contextualizes the artifact and, by definition, generates a value in terms of that context. The issue is not whether the packager should be credited with that value creation, because obviously the answer there is "yes".

But should that packaging credit mean anything contentious about the claim to the artifact which is made by the originator of the artifact? There is no logical reason why it should. The roles here are distinctive. The reality is that the artifact's originator may or may not be valuable to the packager, but the value of the packager's packaging is not dependent on, derived from, nor part of the originator's claim to merit. What is clearly possible, however, is that an originator who has also done packaging might contest a second packager's claim to credit for the packaging, if the second packager's packaging is too similar to that of the originator's first.

This is the right moment to bring up an interesting and usually overlooked fact: value and worth are different. Let's say that similar packaging by two parties has approximately the same value in a given context. It might still be true that the level of value -- as opposed to the fact of having value -- might be either extremely low or might be better. Two parties might fight over who should get the credit for the value, but fighting over the value is not the same as fighting over the worth. One party might be able to use the packaging's distinctiveness (value) much more effectively than another to achieve greater worth from the value.

So that gets us to the usage issue, which is the third key aspect after the production of the artifact and the exposure of it. However, note that what is now in question is the usage of the artifact's exposure -- not the usage of the artifact itself.

III.

Espionage, gossip, or "intelligence" tries to make hay with what it discovers, just like newspapers. That is, for its value, It pursues a certain effect from its uses of the exposure of the artifact -- regardless of what exactly was discovered. Since the "haymaking" is possible independently of the particular discovery (which, after all, may have been pulled off by someone else), being credited with the effects of using the discovery is not inherently contentious with other credits elsewhere for production and exposure.

IV.

Ultimately, the effects of using the exposure have potential benefits and liabilites. Circumstantially, a party may have "rights" of some kind to be the provider of benefits or "obligations" to be the responsible party for liabilities. The question is how these circumstances are governed, and who agrees to honor those controls. For example, we know that customers pay vendors to be rsponsible for the quality of products offered, and they pay contractors to be responsible for what their subcontractors do. But those vendors and contractors may hold a disclaimer or waiver instead, which just points out that their role is not to create the effectiveness (as was the role in the previous step) but instead to capture it for the customer.

V.

Those descriptions distinguish the four different roles played in the availability and effect of the artifact. In each role, there is a sense of ownership to be understood, but what is evident is that the ownership pertains to the responsibility for certain kinds of action.

Claims to credit for the actions can readily be distinguished, which in effect distinguishes different kinds of value created. But the worth of the value(s) is typically circumstantial, and the claim to part of the worth makes sense only when the particular type of value has demonstrably created the worth in question.

Any time that some type of value can be eliminated from the ability to generate the given level of worth in question, the party claiming credit for that type of value cannot use it to lay claim on the worth. By process of elimination, only the type of value critical to the worth points at the rightful claim on the worth.

The other big issue usually at hand, though, is whether a party that created some value had permission to do so. This should be established by the explicit publication of enforceable rules that withhold or deliver the effects of one party's labor to other parties. As opposed to credit (in the way that was just discussed), the boundary established by permission is externally granted -- i.e., virtual, not inherently factual. In the end, the significance of the notion of "property" lies in understanding that this permission boundary is a convention.

Posted by Malcolm Ryder at 7:12 AM | Comments (0) | TrackBack

April 29, 2006

KM, and Measuring the Value of Change

We normally perceive change in terms of "good" change or "bad" change. That is, usually, the value of change seems readily measurable. But why is this? The answer is, because we have a preference before we notice the change, which gives us a reason to notice it.

The usual approach is to first define "value" -- namely, the difference that we want the future state of affairs to have from the current state -- and then to go about measuring the progress that action and time make towards achieving the desired difference. Here, the issue is that although actions and time are both highly various, we usually decide (prescriptively) which actions and timing we will watch.

Because that approach is such a routine for managers, it is all the more baffling to go about it the opposite and less frequent way -- defining the changes that action and time make, and afterwards figuring out what is the meaning of the changes to the current state of affairs. That is, in what sense are the changes recognizable, post facto, as "progress"? What, exactly, is progressing, and do we want it to?

Said that way, we might conclude that, as in the former approach, the majority of management's attention to the phenomenon of change is "regular" and pragmatic, concerned with oversight and with assigning old or current meaning to new observations.

Yet that passes up the home territory of insight -- or, as in the less frequent latter approach, assigning new meaning to old or current observations.

Put more precisely, the distinction is one of being practical versus theoretical. For most business concerns, the problem with theoretical value is that it's either too slow or too speculative to realize -- which makes it expensive to sustain.

Case in point: the influence of knowledge in the organization is often seen as stealthy or unmanaged, provoking changes of unknown value. But harnessing it for managed value frequently appears to lean towards the expensively hypothetical.

This is where many KM efforts get stranded today. Yet meanwhile, that makes it similar to the issue of R&D. In R&D, there is normally some investment justified by the expectation that significant future value will come from new products -- or said more forcefully, justified by the belief that innovation in production is necessary.

Justifications specifically call out the connection between motivation and measurement -- which indicates the importance of thinking about why to measure -- not just what to measure.

Given the example of R&D, the question in most organizations is whether innovation can also be culturally accommodated as a normal and important phase of the ongoing "production lifecycle" of adopted operational knowledge.

The way most organizations recognize their adopted operational knowledge is as "competency". Thereafter, the way they measure the value associated with changes in competency is by measuring the before-and-after difference observed in what looks like a capability: predictably achieving progress through selected modes of action in given situations. At least casually, everyone sees that as "performance", and thinks about performance improvement.

Of course, one of the practical approaches to incorporating changes of competency is simply to buy the already proved "better" competency -- as in hiring "experience". The catch here is not in the difficulty of finding such talent, but instead in correctly defining what it is about the talent that demonstrates the greater likelihood of providing greater predictability of progress. Ordinarily we look for that demonstration in proof provided by prior known situations, or "performance histories"...

But as we know, all workers must adjust to the complexity of the organizational environment, and those who might have seemed to be the most experienced people coming in do not always prove to be the most "effective" people later. For example, struggles with the current work environment (context!) can strongly frustrate the promise of previous experience.

In fact, the most distinguishing problem to solve through knowledge management -- the most challenging "given situation" to address with competency -- is to enable us to know what to do about what we don't know. The main example of this is an ability to solve new problems brought on by dynamics that currently lie outside of our control. (Politics, competition, economics, or whatever.)

Operationally, we can think of the level of that ability as a demonstration of "intellectual productivity"... the degree to which knowledge inputs generate situational effectiveness. But explaining that productivity puts a premium on recognizing improvements in problem-solving capability, instead of on the historical outcomes of solution efforts. Outcomes may indicate improvement, but managerially, the emphasis must be on the mechanism that produces the outcome.

Articulating the features of "successful problem solving" gives a list of (mainly behavioral) characteristics. Those characteristics are really the desired direct results (i.e., differences achieved) of applying knowledge management as an approach to changing operations.

Bluntly summarized, the main goal of knowledge management is to change how things are done, not to change what the doing delivers. The deliverables may or may not subsequently change because the production changed -- but the primary importance is in transforming the production itself in "necessary" ways, so that deliverables can change.

That gets us back to the motivational aspect: the challenge is to define what it is about the production that is necessary to change and why. If successfully articulated and agreed, that particular notion of "necessity" puts pragmatism into the overall KM effort -- easing justification of sustaining investment in the effort.

In re-engineering operations with KM, two broad categories of response to the necessities are: the type of knowledge to develop and incorporate; and, the mode of incorporating the knowledge in the real-time of operations. Aligning things across the two categories can happen as a matter of determining a best practice (process optimization), or as pursuit of an innovation (R&D), but the point is to ensure that this alignment actually occurs. The difference between the current degree of alignment and the target degree is the value of change to be observed.

Posted by Malcolm Ryder at 6:26 AM | Comments (0) | TrackBack

March 10, 2006

How Not To K.O. KM

Knowledge Management (KM) initiatives need not buckle under the weight of uncertain value. The key is to use it to solve the right problem, and to handle it as a characteristic to acquire, instead of as a system to install.

I.

The transportation of knowledge from personal to public, human to machine, and domain to event already occurs continuously throughout the organization. But to optimize how it composes the operational environment, the appropriate aspect of concern to investigate is capacity development, not process development. That is, the availability of the right knowledge in the right circumstance is a different problem from the delivery of at-large knowledge supplies.

Determining the "rightness" of the knowledge and of the circumstance is not about inherently "correct" content. Instead, it involves the use of models that connect expertise to outcomes, not just requestors to information.

That effort needs to be systematic, but in the main conceptually so, not technologically. The biggest practical challenge is to shape a worker's analysis and judgement during a task, by exposing enough of a relevant model to present, guide and validate choices -- while also capturing feedback on the effectiveness of the model's influence on the worker and on the outcome. The problem causing the challenge is that two unlike workers may be different primarily due to their respective individual mental models -- which for starters may also differ from the common model being presented. The payoff comes when dissimilar workers use the same model to derive equally effective individual execution.

A key related factor is that knowledge is carried into production by workers. Knowledge is quite variably embedded into production through a range of techniques utilized by the workers. Managing their techniques becomes a fundamental task of production management. But likewise, the right knowledge must be put into those workers, and the variety of techniques for doing that must also be managed.

Interestingly, there is a very well-known general precedent for just this kind of effective knowledge application: consulting. This shows KM to be generally in pursuit of embedding a consultative capability within the workflow of operations. In that way the capacity for effective knowledge usage is enhanced for all other aspects.

KM's most significant difference is that it establishes an environment in which individual workers can more readily achieve their personal performance objectives. From the perspective of environmental engineering, it is more clear that KM's "customer" is the inhabitant worker, and that the key thing KM must give that customer is an improved experience of managing their resources under pressure of corporate priorities.

Personal management of resources is not exactly obscured by job descriptions, roles, or performance evaluation criteria -- but the fact is that all of those representations derive from a deeper set of assumptions about individual execution.

Here, it is important to distinguish the idea of execution from that of conduct and of behavior. Put simply:
- Behavior generally describes activity and especially activity patterns, in a way that is unconcerned with any imposed or external requirements.
- Conduct describes behavior in the context of situational propriety.
- Execution, finally, describes either behavior or conduct, but only from the concern of whether their impacts have motivated progress towards a certain goal.

How should KM be related to those distinctions?

II.

One of the most important background principles is that the individual should be self-directed yet in alignment with the direction of the business circumstance. Here, the "business direction" means both trajectory and guidance. For this alignment to happen, the individual needs high awareness of the particular important goal, the business significance of the goal, and the implications of various means for meeting it.

A second major principle is that leveraging knowledge requires structured interactions between knowledge providers and users. This is at minimum analogous to the existence of markets instead of merely supplies. For the "leverage" to occur, the user must be in a position to change something with the obtained knowledge. The value of the knowledge is logically associated with the value of the change, so the promotion of the knowledge is organized around that value of change.

Those principles make it apparent that KM, as a business practice, should focus on two high-level outcomes: worker position and worker leverage. That is, if KM does not beneficially contribute to those two things, it is not really adding critical value to the environment or to the business.

Most organizations regard position through worker participation in processes, with participation evaluated by the business at the conduct level. In the case of the leverage, most organizations feature prescribed business functions, such as R&D or production or scorekeeping, that are applied in operations areas like sales, services or manufacturing.

As a result of the operational mindset, "methods" and "assignments" are thought to be the initial targets of KM's top-down influence on individual execution. That is, KM is first sought to make people "do better at what they are supposed to do." That execution is an important business goal, but this goal is "point C" and you can't reach it directly from "point A" where KM needs to start.

Here, we're aimed at improving personal management of resources under corporate priorities-- for which the critical operational success factors are not methods and assignments but instead awareness and alignment -- the drivers of voluntary interaction . These are the direct touchpoints that the worker has, anchoring behavior which we can then project across their conduct and execution.

III.

KM makes the assumption that talent in the organization can generate greater productivity through synergies and/or optimizations offered by dynamic collaboration on key objectives. It therefore intends to practically influence the real-time organization of the community of talent.

But we must remember that a "community" is actually the result of individuals electing themselves to the membership. Let's look at the real structure of the knowledgeworker community targeted by KM. Finding the structure means identifying the major dynamics, "benefit vs. risk" style, that surround and involve the individual member of the community at each opportunity for awareness and interaction. KM's affects on these dynamics stage its ability to shape the individual's execution.

Talent versus Internal Competition: the person's predisposition must be compatible with the organization's need for their skills. In effect, "hold-outs" dramatically increase the opportunity costs of operations by forcing a shift of other resources away from more optimal pursuits of advantage and towards what are essentially operational defenses like contingency coverage or repairs. Here, "talent" is a practical idea representing "appropriate skills". Since talent is valued in association with the efficiency of its use, any challenges to that efficiency will virtually devalue the talent; therefore, managers should target removing those challenges -- but meanwhile the talented individual will naturally seek low-resistance opportunities to being prominently employed.
For that, the individual's own tactics to preempt, avoid or reduce challenge need to be simultaneously channeled away from unproductive self-protection and towards opportunity.

Collaboration versus Co-Opting: the person's presence must be highly valued specifically for the purpose of the collaboration. This means that the person's identity needs to be noted much more for their role as a giver or enabler than as a taker.
- Being explicitly associated with successful collaborations must be equally important as, if not more important than, individual credit.

Opportunity versus Confusion: the person's preference must focus on the objectives for which their support is well rewarded. Otherwise, their personal priorities can too easily challenge the priorities behind the deployment of the KM channels. Behaviors themselves must be an objective, not just certain projects or subject matters.
- The individual needs to be able to see, continuously, which personal behaviors are currently being perceived as business benefits.

Those points advocate systematic coordination of:
- the security of the individual's ongoing opportunity
- the public visibility of the individual's expertise
- the pre-approved recruitment of the individual into high-priority areas of business need

But where coordination is concerned, companies typically look at processes and functions to generate the value they ultimately seek from their resources. Less well understood, and less accounted-for, is the ecological effect that the quality of resources has on the environment hosting the processing.

Usually, the connection of resource-quality to operational progress gets most of its attention during a phase of resource-selection and process design. But except when problems break out, the attention to the subsequent execution-quality often overlooks many of the ways that resources constrain, improve, or modify production in tasks and processes. In correcting this visibility, the essential issue to grasp is how (and why) workers apply knowledge in real time to production.

In the table below, examples are shown for how the dynamics in the community can be influenced through cultivating individual persons' adoption of more knowledge-based objectives. Such examples stage opportunities to track influences in terms of an ecology. In short, this suggests how to execute KM, and shows it as being more of a practice than a process.

IV.

In a very important sense, the difference between KM and process management parallels the difference between coaching and supervising.
- Supervision focuses on reliable compliance of activity to requirements.
- In comparison, coaching increases resource readiness and confidence by concentrating on the alignment of capabilities and opportunities.

Looked at that way, it makes sense to ask how an individual's "profile" of predisposition, presence and preference makes them more or less "coachable" through a consultative facility. The more coachable they are, the more chance exists that their personal performance objectives can be coordinated with business priorities.

A view of this might be developed by auditing the profile in terms of awareness and alignment. In turn we can anticipate how KM mechanisms can support improvement in the profile, and thereby set better expectations about how KM will enable the individual.

Along with coaching, support completes the enablement scenario. In particular, various tools can provide KM-support for each row in the main chart above. For example:
- In the Expectations row, tools that generate topologies and ontologies for aggregated information stores are applicable, helping to coordinate vocabularies and ideas around shared standards.
- In the Experience row, Wikis, blogs and knowledgebases effectively promote the link between specified authors and content.
- And in the Expertise row, search engines and dashboards help expose and promote the relative importance of behaviors and ideas to each other and to production.

V.

Finally, a practical expectation of synergies and optimization needs to be established, and supported in an uncomplicated way:
- For synergies, the point is to show that new or unexpected collaborations yield important results on demand.
- For optimizations, the point is to show that knowledge re-use increases the number of instances of benefit obtained from one developed item or source of knowledge.

Having those working definitions, rewarding initiatives related to them, and tracking their example success stories, is the most straightforward way to focus attention on when and how value comes from them -- making them practical instead of just theoretical.

Furthermore, the extent of opportunities to pursue them should be taught. When a collaboration yields an unconventional or unexpected benefit from a given source, that source is contributing to optimization by announcing that its potential as a resource is greater than previously acknowledged -- offering agility and the possibility of eliminating some redundancy. Thus, synergy and optimization can be flip sides of the same coin, and an increase in one might also spur some degree of increase in the other. This should be looked for both in the design of operations and in the evaluation of outcomes.

Posted by Malcolm Ryder at 8:12 AM | Comments (0) | TrackBack

February 23, 2006

KM for productivity - driving Decisions versus Recommendations

Does knowledge improve performance?

The default answer should be "Yes". But this makes sense only if certain other things are true.

The fast explanation is that knowledge improves the decision-making that shapes activity -- and with higher-quality activity the intended outputs should be more influential, as planned, on the conditions prerequisite to desired outcomes.

But let's drill deeper. If the shape of the activity is what powers its ability to produce influential output, we seek certain outputs that have explicitly demonstrated their powers to either support or cause the outcomes we want.

That is, we are logically connecting methods to impacts to effects. Indeed, when we pursue high performance, it is the entire set of connections that we need to either design or select... build or buy. Those are the decisions, the ones about what connections to make and what to connect, that are most affected by knowledge.

More specifically, how does knowledge affect those decisions?

An important attitude towards discussing this question is to appreciate the difference between recommendations that are transferrable (aka, content) versus decisions that are knowledgeable (aka, expertise).

In both cases, we have a goal of gaining greater awareness of states, options, implications and consequences. The operational contrast is interesting, however.
- With content, which we procure, we wind up mainly dealing with facts and recommendations.
- With expertise, which we produce, we mainly deal with insights and decisions.

Intuitively and empirically, we know that to get from facts to recommendations might require the intermediary steps of having insights and making decisions -- which is why we think of content as having "embedded expertise". But this just emphasizes that understanding expertise is the starting point for determining where value originates. Thereafter, the value has to be successfully exploited in the work procedure.

To start with, all decisions are choices. Focusing on expertise, the point is that awareness allows subsequent choices to be more logically and accurately indicative of the expectations (e.g. performance) we attach to them.

This awareness may become available before and/or during the effort to make choices. But either way, when we say "better decisions" we are really saying "smarter choices" -- while not yet saying "most desirable outcomes". The fact is that the most desirable outcome (a goal) might not be one to which currently recognizable choices exhibit a very well-founded ("smartest") path. Now if the intent is to have the desired outcome through hell or high water, then the primary challenge is to be more knowledgeable -- literally, to generate more awareness -- so as to further substantiate the choices.

That is, being knowledgeable is a certain kind of behavior that works mainly on information processing -- the kind of thing represented by what is called "business intelligence"... And in that sense, managing "knowledgeability" is a whopping big business, focused on creating timely (and even just-in-time) expertise. Driving it all is the talent for determining what needs to be discovered and then to discover it.

But given that, it's difficult to avoid also positioning knowledgeability as a source of knowledge, and we wind up seeing decisions as a form of knowledge. We communicate them and we repeat them in practice, meaning that they migrate to being recommendations, credible as long as their effects and side-effects prove not to be too negative.

In line with that, prefabricated knowledge that is procured instead of produced has its most common currency in the form of recommendations. Recommendations basically present thoughtful conclusions whose derivation might be tracked back through the information processing that preceded them. But the main difference here between recommendations and decisions is that recommendations emphasize the context of a decision, while decisions per se emphasize the construct (ingredients) of the decision.

We usually study recommendations for their relevance, and basically start with relevance as the filter for selecting and approving them. In contrast, for selecting and approving decisions, we study them to find out how meaning is generated from facts.

The question is, where do users of decisions and recommendations get their pre-dispositions about meaning and relevance -- and what is the process for evolving those into the most productive positions?

If we see decisions and recommendations as being manageable, it follows that we are concerned with organizing how users of decisions and recommendations are led to meanings and relevance.

That guidance initially happens primarily through the requirements issued by defined business processes and tasks, which are the way that the organization provides dynamic structure to business production. The requirements tell users what to look for and why.

Taking note of that, it is evident that "emerging" or "incoming" knowledge then interprets the requirements -- by comparing known previous decisions and recommendations to available current (and especially new) ones.

The results of this comparison may propose changes -- each change having associated cost, risk and benefit that is to be aligned with the objective of the business process or task.

That alignment will usually be evaluated in terms of whether the proposed inputs (cost, risk and benefit) increase the probability and completeness of meeting the objective. This makes for four general evaluations in terms of productivity:
- more likely, with more complete enablement
- less likely, with more complete enablement
- more likely, with less complete enablement
- less likely, with less complete enablement

Those generic flavors of relative productivity usually get specified as detailed formulas pertinent to the particular type of process or task. But the more important point here is to have the visibility on how interpretation of requirements is the leverage point for knowledge to influence productivity.

Interpretation of requirements can have two outcomes itself.
- On the one hand, various ways to meet the incumbent requirements can be discovered, validated, renovated, and so forth.
- On the other hand, the incumbent requirements themselves may be challenged enough to begin changing, towards better correspondence with the process or task objectives.

Therefore, it is important to distinguish productivity from performance.

Performance emphasizes the actual outcomes and whether they are more or less close to the intended outcomes. Performance doesn't give points for doing the wrong thing well.

Productivity, however, emphasizes the effectiveness of the manner in which the actual outcomes were generated.

High performance is fostered by high productivity, but they are not synonymous. Under a relatively unchanging model of high-performance, productivity may be accomplished in different ways at different times or places. What high performance wants is for an underlying productivity to enjoy agility -- as a way to assure that the high performance might be sustained against changing situations.

To imbue agility in the productivity, knowledge has a key role to play -- namely, finding alternative effective manners, on a timely basis, for fostering and generating desired outcomes. As the business need for agility increases, the role of knowledge becomes more and more critical and valuable. Making that role effective is what knowledge management is all about.

Posted by Malcolm Ryder at 9:21 AM | Comments (0) | TrackBack

January 29, 2006

Business Intelligence versus Business Knowledge: Who Cares?

How often is it said that "information is the lifeblood of the business!"...?

No one dwells on whether it is a true statement or not. Everyone dwells on how to process information so that the business is neither toxic nor anemic.

It's a telling fact that the initial assumption is always the same: information must be processed. It simply means that either the info isn't "good enough" when it first arrives, or that there is no point in having it unless it is going to immediately be transformed somehow into something else (namely, a decision or a directive).

Ironically, it is processing itself that makes using information so complicated. The evidence? Pick, from the following, only the one item that most clearly represents the primary reason why your company can keep its operations attuned to the business goals:

- Performance Management
- Business Intelligence
- Knowledge Management
- Content Management
- On Line Analytic Processing
- Database Management

Now, explain your choice by explaining how you ruled out the others.

That should be enough to make a couple of aspirin and the following picture worthwhile.

The key points of the picture, both explicit and implicit, are variously familiar or unsuspected.

One aspect reminds us about Garbage In/Garbage Out:
- Data and Knowledge are both "inputs" that can be taken prima facie and virtually from anywhere.
- Intelligence and Insight are business goals of information processing

Here's another interesting aspect to chew on. From the point of view of a business process:
- Supplied information (left side: data, intelligence) is not the same as Applied information (right side: knowledge, insight)
- Intelligence is not directly "parallel" to Knowledge and cannot substitute for it. Being intelligent is not the same as being knowledgeable.
- Likewise, although "information may be power", having Data in no way assures an advantageous (Insightful) use of it.

And additional annotation offers this:
- The most obvious connection between data and intelligence is Cognition
- The most obvious connection between intelligence and knowledge is Learning
- The most obvious connection between knowledge and insight is Experience

In those relationships, we can see another situation in which, as with so many aspects of goal-seeking, the difference between a cause and a prerequisite can be quite profound. On the one hand, getting one of these areas up to snuff won't make the other areas happen. On the other hand, working on one of these things without regard to the others is probably not very "smart".

To ultimately gain maximum advantage through information, we'll need our firm to become an intelligent enterprise that is also a learning organization constantly testing and improving its perspective.

Posted by Malcolm Ryder at 2:43 PM | Comments (0)

January 11, 2006

Why Strategists Must Think "IT" Through

Our big challenge with strategy is to tame it -- to translate the alchemies, voodoo and romance of intuitions and insights and intents, into something credible and practical; into capabilities and competencies that make a virtual opportunity real.

We took three shots at this.

(1) One translation is a thought experiment. Surveying the vast inventory of literature on strategy, we took a moment to try to parse its boundless advice into its typical themes -- with results such as: why to pursue execution for value; how to avoid a position of (poor) performance; and so on. Then we looked at the themes for their generic components. It gave us the following table of elements with which to reconstruct and predict themes:

This provides a hope that by mixing the building blocks (left to right) in different ways, we could derive the not-too-many worthwhile starting viewpoints, and thus throw a defensible practical fence around strategy! Each uniquely different combination of elements could be considered a certain known problem to solve -- addressed by strategy literature's various promotional and cautionary tales.

But such high-level problem definitions are mainly conceptual. To get them more specifically in focus, and get their corresponding solutions down to earth and in-house, we also need each element of a problem's definition to be detailed by the additional aspect of "management" vs. "infrastructure". Drilling down into the elements that way, we still "choose and add" the different elements to each other (left to right) to derive the problem statement. Connecting fine-grained elements to each other may actually give a more precise surface description of a particular organization's issue, but at the same time it accounts for how some problems leave us not being able to see the forest for the trees. Our table can help bring the forest into view.

(2) Another translation is already explicitly described in the literatures. Regardless of how many ways strategy stories begin, much of the discussion ultimately drives to the same counsel -- that decisions reshape the organization, after which the organization's operation must be motivated enough and funded enough to stay with the program.

This summary casts long political and cultural shadows over all discussions of any competency and capability that are to be acquired and committed.

(3) In a third and parallel translation, we note that all strategy refers to an opportunity (whether remedial or progressive) -- and opportunity always refers to the perceived characteristics of currently acknowledged conditions. In pursuing strategy, decisions follow the anticipation, observation and analysis of those conditions. Challenged by the conditions, much of this pursuit is competitive.

But the way we see those conditions increasingly finds them loaded with characteristics that exist only because of the impact of information technology. Because IT utilization dominates the shaping of the environment that strategy wants to exploit, strategists must always factor in IT. The way that IT changes things becomes the focus of concern, even moreso than the particular features that have been wrought.

Of special importance, "IT Innovation" means that people can know different things, in different ways, at different times than previously, and furthermore do different things than they have before about what they know. Put so bluntly, it is obvious why strategy cannot be well formulated without factoring in IT -- IT can be the thing that defines the competition -- whether the competition is an environment or another actor.

The question is, will the strategist's own organization manage IT utilization to virtually pick the competition that it wants to have?

Posted by Malcolm Ryder at 8:13 AM | Comments (0)

December 19, 2005

Research, Identity, and the Authority of Desire

"I'm not perfect, but I'm perfect for you." -- Grace Jones

Fulfilling need is the core of a business, and defining need is the key to identifying the customer. But understanding need requires understanding desire, and the role of desire behind the need.

I.

In Truffaut's 1960's film of Ray Bradbury's novel "Farenheit 451", the vision of the future doesn't include a cell phone or a PC. There isn't anything in the future home that looks like it has a Delete key on it -- and even less something with a Find key. Meanwhile, the government perfects "information" by tracking down, confiscating and burning every text that it thinks would make people restless and unhappy. Information programming is pervasive. Of course, the ban on books is because independent reading leads to independent thinking. The "Thought Police" are everywhere. People who read are criminal outcasts.

But at the end of the film, everyone does the same thing -- they adopt identities as expert carriers of the information they chose. And whether they chose to identify with the propaganda or with the banned literature, either way they do what they do, and they know what they know, because they want what they want.

Fast forward to 2005 and increasingly, if you have a PC, you choose your own diet of information. (Is it true that we are what we eat?) Find and Delete are as routine for the individual as it was for the government in Bradbury's nightmare future. This leads to a lot more free thinking and free spirits, but it doesn't necessarily lead to great thinking or communities. Confusion might be the main reward of the escape from power politics. Not to worry, though: herding the cats, we still have Academia and we have Marketing.

What do academia and marketing have in common? Tremendous emphasis on "why you should think what you think." Put that way, we can see them both, like politics, as not mere information management but as instances of practical "knowledge management" in the commerce of ideas.

II.

Given the Web's explosive abundance of circulated intellectual material, shifting our scrutiny from "what" we should choose to "why" would seem to be more necessary than ever. Luckily we also have an unprecedented opportunity to analyze or "understand" the options available within the supply; but in the end, why do we care about what we choose?

Marketing, we know, makes product abundance manageable -- guiding our hand as we sort and select. It has always been interesting particularly because it answers the question of "why" with a picture of our appetites. But when it comes to ideas, Academia has always represented the view point that something more impersonal than appetite -- namely, science -- should provide the filters and orders that do the choosing, and the filters are paradigms. Yet why would a science make any more "important" choices than would a personality?

Bradbury's outcast literate society grew its membership with an unquestioned acceptance that all great texts were equally important, and with a requirement (or at least an explicit expectation) that each member select a great book (text) to commit memory for faithful recitation. Once "in", the member needed to show unflagging commitment to the literary identity that was assumed. But despite a virtually unlimited choice of texts, the society showed no overt selection process for what was "great" other than the discretion of the individual member. The apparently utopian feature of that alternative society -- that everyone had the same benefits of membership -- is an implied incentive or reward for making a good choice, but it's also a great leap of faith. At the end of Truffaut's film, all members have started out "equal" because all of them are impersonating ideas given equal merit. But where do they go from there? Why wouldn't this group disintegrate?

We get past this skepticism only through certain presumptions.
- For starters, the individual's selection of text must not have been problematic. Either the individual demonstrated sufficient critical skills, or the individual was willing to be guided by the reliable decisions of other "wiser" persons.
- Thereafter, the motivation behind commiting to the text was the key adhesive ingredient.
- But fueling the motivation, individual hunger for knowledge was the group's common cohesive principle. Thus, appetite itself is transformed into a paradigm of authority, called desire.

III.

To some extent that recalls Thomas Kuhn, who in his book "The Structure of Scientific Revolutions", digs deeply into how subjectivity drives the rise, influence and fall of paradigms. In doing that, he basically exposes the marketing that takes place within a presumably objective academia. "Community" issues, particularly politics, organize and promote subjectivity, mainly by turning certain ideas into products while rejecting others. These "information products" are cultivated by both providers (supply) and consumers (demand).

On the providers' side, through a diligent rigor, the discipline of the research practice breeds product credibility, and that is the normal focus of observers' attention. But as Kuhn reveals, it turns out that research is essentially dominated by motivation , not discipline. The credibility (pertaining to what it produced) is actually a completely separate issue from the relevance of the research (pertaining to why it produced it).

In the resulting supermarket of ideas, the consumers' side has a reflection of that same separation: the difference between what we should be able to choose from (or what counts) and why we should buy (or what matters).

IV.

Having choices to make comes with an accompanying tension involving who gets the last word and why, or where the authority lies.

Since a consumer's reason for wanting something may not be the same as the reason why the provider produced it, if the two parties are to help each other they must find an agreeable coincidence of their interests. Working out that coincidence, negotiationis what ultimately decides which options survive. But underlying that negotiation, research is the effort to resolve the great contest between what we want to decide and what we ought to decide. That's where the real issue of authority comes in.

The moment when we accept both an idea and its authority is summed up neatly in the phrase, "OK, I'll buy that." If you're a provider, getting the consumer to that moment is the goal. But which authority will win out -- desire or propriety? They are not mutually exclusive: rather, the issue is all about which one is primary, commanding the other to support it.

Propriety typically comes with a fairly explicit formality, making it seem easier to use for engineering the result. But what about desire? The formaility of desire has various models as well, dynamics mainly theorized by psychology; but it is typically and mistakenly assumed to be more subconscious than conscious. Instead, the case is really that it's dynamics are more implicit than explicit; it is not subconscious but rather just unrecognized as an organized whole.

Thanks to internet technology, pertinent information about desire's dynamics surfaces more readily and more regularly. The more intelligent we are about our desire, the more effective is its authority -- and consumers quickly gain huge amounts of this intelligence. Now it is more likely than ever that the consumer's own research competitively intervenes in the process of being influenced by the provider. The consumer gets to define what matters. And increasingly, the consumer's authority is by nature indifferent to the provider. Without the kind of value that matters, the provider's product may not count regardless of its quality.

Because that intervention can have an evolutionary or revolutionary effect on the perception of the provider's product, it becomes a strategically critical planning consideration for the provider.

Meanwhile, on the consumer side, it's increasingly evident that while we usually buy what we need to, with internet technology in hand we usually try to buy what we want to. If you're the consumer, how is it that you are actually intervening?

More importantly, how do you come to want what you want?

V.

Historically, at about the third level up in Maslow's hierarchy, "Marketing" has spent its time helping you to want what you want, mainly by offering you a vendors' choices about what you could be like. Thereafter, "Selling" has spent its time offering you choices about what you want a product to be like in order to please the version of "yourself" that marketing had helped you pick. Together, a vendor's Marketing and Selling has had to be sure that you are agreeing with the vendor's ideas and that you are preferring them.

That makes it look like the vendor is doing all the work; but the consumer is not inactive; the key ingredients in the above issues are selection criteria that qualify any items presented, using :
- information about what's possible (i.e., effectively available),
- information about what works (i.e. effectively correct), and
- information about trade-offs (i.e., effectively compatible).

In each case, there are claims made that must be found relevant. But working down the list from "availability" to "compatibility" -- from what counts, towards what matters -- the issue of credibility is increasingly important. For the consumer, the work here is in gaining confidence that the information being processed is good info. But that's not all.

Against that challenge, the vendor has typically worked hard to be able to ultimately say "Trust me!" The vendor gets some help, because from the buyer's viewpoint, the more we want something, the more likely we are to find reasons to buy it. But crossing the line between attraction and commitment is still hard. To make things happen, the vendor focuses on our desire. For the consumer, the work here is in accurately expressing the desire.

Now, thanks to the internet, the information we as consumers need for deciding whether we "agree and prefer" -- or "trust and desire" -- is much more readily acquired from providers other than the vendor, which has quite significant consequences. With online information, the process of discovery and validation has morphed into consumer-driven processes of search and research; so to get "buy-in" the vendor increasingly has to agree with the consumer's ideas. The age of reasonable alternatives has fully arrived. Thus, the first major strategic concern in managing it all is now about who defines the value of a product.

VI.

We can distinguish the idea of "product" by saying that something is a product when its characteristics are both targeted and promoted for a known set of needs. Having a need, we can even simply find something attractive, and in essence then promote it to ourselves. Thus, a "product" comes about through either invention or discovery. Online Search helps a consumer find, at minimum, anecdotal evidence of more different ways to skin a cat. This expanded perspective allows more of those ways (including competing, unprecedented or unconventional ones) to be recognizable (credible) as legitimate "products". It's not hard to see why this competes with Marketing. In effect, "products" are being "made" online through Search.

Meanwhile, with online Research , highly available critiques make it more likely that a product's true probable kinds of impact can be objectively well-determined on one's own. A provider should see that from that greater certainty it's easier for a potential buyer to commit to the item being considered. Why? Because a product that is explicitly appropriate (relevant) can more easily find its "right" buyer. Here we can see research competing with Sales. In effect, "customers" are being "made" online through Research.

But the parallels are not just that simple. It's not just search replacing marketing and research replacing sales.

The important true difference between search and research is, respectively, the difference between discovery and investigation. Discovery is concerned with "what I should find" (i.e., what counts ) while investigation is concerned with "why I should find it" (i.e., what matters). Both concerns are found within marketing, and both are found within sales.

In wanting what we want and getting what we want, desire is made of both discovery and investigation - of both what counts and what matters.

VII.

As seen below, desire is multifaceted and is managed concurrently by the provider (vertically) and by the consumer (horizontally).

For example, in this picture:
- Marketing's promotional aim is to propose a "correct" option for the consumer's target concern.
- But to buy in, the consumer must also find the option to be "compatible". To get there...
- ... the option must be highly "available". Otherwise it is unlikely to survive as an option.
- Finally, a compatible option must be "convenient": that is, it's accessability, usability, comfort, and so forth must make the option fit the consumer's need, not just the consumer's occasion.

VIII.

As consumers, we use search and research to collect and examine information. We use a marketing search and a sales search to take in both marketing and sales information and find options that have value (i.e., what counts). But in order to sort through the variety of valuable options and get to our preference, we use research, examining search results for their compatibility and convenience, to find worth (i.e., what matters).

This processing is the authority of the consumer. It presents the consumer's desire as a paradigm targeting "preference"... or more specificaly, an unobstructed ability to get what is wanted. Authority represents the consumer's ability to make a decision (namely, to accept or reject the product) independently of the provider's promotion of value. Additionally, because we can understand it as a standard set of interrelated factors (as shown) that can be repeatably exercised, we can see the authority acting the same way whether the consumer's preference exists wholly from self-imagining or, at the other extreme, from the militant influence of other non-provider parties such as peers, supervisors or dependents.

IX.

As just described, authority describes the consumer's ability to act independently in pursuit of preference. Preference will reflect the consumer's goal of having the right thing in hand for the occasion of highest priority.

But the priority of the occasion is not always set by the consumer. Importantly, the consumer commits to the priority because of the priority's associated rewards and risks. This commitment effectively places preference as a proxy for need . Making that circumstantial commitment also means that the consumer actually presents an assumed identity to the provider.

In effect, the consumer's need supercedes the consumer's authority.
Because of that, the consumer's autonomy is an actively critical issue at a level even higher than the consumer's potentially revolutionary authority. That is, does the consumer have the right to set and change the highest priorities as the processes of discovery and investigation carry on?

And regardless of the autonomy, can the provider persuade the consumer to assume an identity that is advantageous for the provider?

For the provider, persuasion must succeed across a spectrum of strategic concerns having at least three major segments.
- It starts with who defines the value of the product (who decides why it counts).
- From there it goes to who defines the worth (who decides why it matters).
- And finally, it reaches the point of who sets the priority of the occasion in which the product is anticipated (who decides the need).

Control of these factors cannot be taken for granted. Consumers' online search and research often finds them actually engaged in an experience of self-discovery as they encounter vastly more information of uncertain quality or importance to any progress towards their goal. They wrestle the information to the ground over a series of refinements and iterations, but during the effort they are making decisions about the identity they will assume as often as about the product they will accept.

To take advantage of that, providers should focus on framing the information and its delivery to assist the consumer's development of their final operative identity. This is, actually, what has always been done in marketing and sales. But now the odds are also much greater that the provider will encounter a consumer that has a far more aggressive capability for self-determination, and/or a more powerful capability to suddenly bring alternative providers into the considerations at any point.

The combination of those consumer capabilities means that "the market" is now more virtual than ever -- having boundaries that rapidly appear and disappear along with the identities that consumers derive and assume for themselves each time they are out and about.

The question is, with online search and research, are consumers also "making themselves into customers" more efficiently than does conventional sales -- and are consumers "discovering products" more efficiently and innovatively than does marketing?

If the answers are "yes", then both marketing and sales as we have known them should change -- and while they will still pursue consumer trust and desire, more evolution of their underlying practice models for knowledge management seems imminent.

X.

As suggested above, the consumer recognition and experience of practical KM has typically gone by another name -- such as "marketing" or "sales". One key point to take from all the preceding discussion is that as more consumers do search and research, the underpinnings of sales and marketing change, so it's logical to expect that the KM practice behind sales and marketing will also change.

But now, beyond mere "customer-centricity" developed at modern providers, the source of the new practice models may be the consumers themselves.

The implications of that are most specially interesting when:
- information or knowledge itself is the product sought by the consumer, and...
- the consumer is busy defining both the product and himself.

The challenge to the consumer is considerable. The internet still has a frontier character because it does not inherently guide the choices it might support or reward. But, that offers unprecedented latitude in exploring and finally deriving the predisposition for agreement and preference that will characterize the consumer's activity. Through trial and error, consumers find out what forms and usage of information and knowledge that they perpetrate are usually underlying what feels like progress in aligning and linking the identity they want with the need that they respect. This frontier represents the R&D environment from which consumers may derive the models of practice that will suit them best. Today, because it is now so much easier to discover and self-serve the uniqueness of one's identity, any given consumer seemingly has a chance of deriving a personal model that is as good as any from elsewhere. The consumer is, in effect, a knowledge worker.

XI.

For providers, the message in that is really important: the future standard benchmark of provider success is consumer productivity -- that is, the ability of the self-defined consumer to use the provider to generate solutions to the consumer's need.

This modus operandi is far from an unusual concept: for example, some IT organizations in corporate enterprises have existed in provider roles under this demand for at least a decade, making technologies into products for enabling prior-defined business tasks.

Paralleling that, some providers are all about making information into products for enabling user tasks. For them, the problem of assessing the worthiness of knowledge management (KM) in the enterprise highlights a similar challenge: "knowledge workers" -- i.e., employees whose primary responsibility is production output from a work toolset of information products -- must generate more enterprise benefits when supported with managed knowledge provision than they do with mainly ad hoc knowledge access. In the enterprise, the knowledge worker is the consumer.

XII.

The uncertainty of dealing with differences (heterogeneity) amongst knowledge consumers is a tremendous problem for the corporate setting, in which standards and economy of scale are functional gateways. For the providers in the enterprise, the necessity is now to standardize and scale individual production instead of mass production.

Whether in IT or KM, the primary tension for operations still exists in the difference between the consumer's preference and the provider's promotion. Specifically, the consumer may want to do things one way while the provider offers a different way. Bilaterally resolving the tension will be the key to productivity, and this is possible only through addressing the issue of why the consumer wants what they want.

On the provider's side: understanding how the knowledgeworker's need and desire are established and defined by the knowledgeworker is crucial to designing knowledge management -- which must remain a vehicle for the development and commerce of information products. It is logical that, just as with IT and information management services, the first baseline of widespread KM success will come with the creation of KM "services" and service level agreements that are incorporated into consumer-recognized operations like marketing, scholarship, resourcing, support, planning, or whatever... (Thus, the Googles, Yahoos, eBays and Amazons are not in the least mysterious as to how they are maturing. In the enterprise, we at least can anticipate corporate versions of those providers.)

On the other side of the coin: in light of the consumer's new capabilities in an online environment, a knowledgeworker is clearly a consumer with a heightened, "open" opportunity to become a source of product (i.e., a provider) as well. "Grass roots", "social networks" and "open source" efforts are examples of increasingly coordinated activity that integrates and elevates self-service, peer-service and collaboration to the status of a complete but alternative channel or environment of intellectual commerce -- not outcast, but exotic... albeit perhaps for only a little while longer.

Posted by Malcolm Ryder at 7:27 AM | Comments (0) | TrackBack

December 13, 2005

The Value of Being In the Know

Imagine trying to create value without being knowledgeable. Not good. But how do we know what value the knowledge creates?

I.

FIrst let's go to a working definition of "value", to tell us how to consistently recognize when value, instead of something else, has been created.

- value: the significant difference that is made by a distinction.

This generic definition is important because it is portable and unchanging across different kinds of situations. However...

In any particular situation, value might be created in a variety of ways. Its two key parts -- significance, and distinction -- can exist independently of, and prior to, each other. This allows some complexity:

- a single distinction can be significant in multiple ways, but not all of those ways are necessarily relevant to a given stakeholder. And...

- there can be more than one way to get to the given significant difference; not all ways are necessarily tolerable or practical at a given time and place.

Thus, the two parts can have a many-to-many relationship with each other, which means their combinations can vary and thus generate value in many diferent ways.

We'll have to sort through that variety when assessments roll around. We should objectively identify different kinds of values. Then, based on relevance and practicality, we can determine what kind of value might be most within our grasp, but finally we also have to decide how much that kind of value means to us and why. This separation of "value" from "worth" is the precision awareness provided by an assessment. The assessment helps us think through potential values in terms of worth, and ultimately we'll commit to the most worthy values.

As an example of concern about "what value is meaningful", companies considering taking on knowledge management (KM) are commonly concerned about the economic impact of KM's value. If KM is valuable, they want to know how and why, with regard to that specific impact.

In figuring it out, we have to start with "how" the value of knowledge can be recognized.

II.

One approach to identifying what value knowledge creates is to first state the desired type of value and then apply knowledge in situations that logically should drive that type of value creation. If applying knowledge produces a measurable change towards the desired value then we attribute that value to that knowledge. An example situation would be "problem-solving". Here, we know that we want a solution and that getting to a solution is a multi-faceted issue. Measuring the effects of applying knowledge might yield findings such as:
- solution obtained much sooner than otherwise has been the case
- solution obtained with greater efficiency of required resource consumption
- solution obtained where previously there hadn't been one obtainable

In fact, "faster, cheaper, and prettier" are very reasonable terms by which to measure the effects of applying knowledge. They typify agreed notions of value (i.e., significant difference) that people already know what to do with.

This is an approach that is compatible with "accounting" -- at least in the sense that it describes tangible results correlated with the level of effort invested and consumed in the situation.

An approach wholly different from that, however, is from the other direction -- where applying knowledge appears to predictably, and even reliably, cause changes, but the significance of the changes is undetermined. Here, the problem lies in not understanding what to (literally) "make of the change"...

When applying knowledge has effects of indeterminate usefulness, the accounting perspective does not help to identify and manage a recognizable value. Accordingly, we need another view -- one that perhaps introduces previously unseen useful effects to accounting, but at minimum discovers the usefulness of previously unobserved effects.

III.

In the latter case above of knowledge-driven changes, management has a special problem: we need to determine whether applied knowledge has re-organized conditions in a way that provides a different set of opportunities and risks than what had previously been established -- not just a different level of preconceived value. The more important the new opportunities and risks are, the more valuable we can say was the knowledge involved. But as with any change management, we need to determine whether the knowledge-driven changes are the "right" ones -- and whether the value is a kind that we really want.

One practical way to recognize this issue of reorganization is through the idea of "technique". Technique organizes the way things are used in action. In practice, acquiring good technique is the same issue as being "trained" (reorganized) to a point of better functional capability. The two most important aspects of technique, making it a target for adoption and improvement, are that (1) it provides an operational advantage against stress, and (2) the means of that provision are sustainable. These are compelling differences to attribute as value.

Technique organizes the way things are used in action -- but so does a "process". So what's the distinction there?

Technique is to "process" as Policy is to "approvals". Approvals define the selection of permissions, but policy defines the logic of permissions according to prevailing conditions. Likewise, where process defines the selection of connecting actions, technique defines the logic of actions according to prevailing conditions. A process that amounts to bad technique is no more tolerable than approvals that amount to bad policy.

Most oganizations today can think about technique by thinking about "best practices", contrasting that against what might be considered the "best procedures" world of processes and rules.

But if we take the example of best practices and investigate it for its contribution to value, much of what immediately comes to mind is the view from the opposite direction -- that is, practices which are not "best" are inhibitors or liabilities that we want to remove. This helps to focus our attention more on the aspect of protecting "opportunity" and on how opportunity is maximized or minimized under the pressure of demand.

Now, we see that Opportunity can be set alongside Operation as a second critical perspective in assessment. Where assessment of operations deals with progress, assessment of opportunity deals with potential.

- Potential represents the degree of protection provided for an opportunity to obtain the desired impact.
- Progress represents the degree of achievement in realizing the potential.

Accounting typically examines Operations for progress; but value assessment also needs a mechanism that examines Opportunity for potential.

IV.

Before beginning that opportunity examination, we must be careful to furthermore separate "opportunity" from "objective"...

In practice, objectives are usually identified and promoted specifically to represent the perceived or desired endpoints of paths -- paths seen as "opportunities" that describe the potential for reaching a goal. The paths have been conceived for the purpose of meeting the objectives.

Managing operations focuses on moving things along those paths; but covering the known paths is more about performance than it is about value. Meanwhile, accounting is heavily performance-oriented. It wants to discover and explain "progress." It expects knowledge to stage and promote progress by changing operations to realize the potential.

In contrast, managing opportunity means path-finding and path-determination, which comes from strategy. Strategy is heavily value-oriented. It is mainly about finding and validating the paths where potential is first created. It expects knowledge to stage and promote potential by changing opportunities to realize the desired impacts.

Thus, in the defined opportunity produced by the strategy, we see the definition itself as the "significant difference" and therefore attach value to it (separately from any pursuit). Then, we have to weigh the opportunity's significance to the objective, independently of weighing the importance of the objective itself.

For example, we may see the strategy as the map to success. Following the map will still be a critical constraint on achieving the goal, but the requirements for following it (i.e., progress) should not be mistaken as the criteria for weighing the importance of the strategy's value (i.e., potential).
- Instead, the strategic opportunity must be relevant and viable, and considered against alternatives.
- Meanwhile, regardless of the importance of the objective itself, if the opportunity is critical to the objective then by definition the opportunity has great weight.

V.

The map that strategy creates is a highly valuable asset even before we start to actually follow it. We want knowledge to do two things: to make us better map-makers; and, to help us make better maps.

Those differences indicate yet another key to assessing the value of knowledge -- namely, to distinguish "intellectual assets" from intellectual behavior. Knowledge changes both things, so they each are dimensions of knowledge influence, affecting both operaions and opportunity. Additionally, they affect each other.

Managing assets and managing behavior are not the same activity, but with valuable assets such as distinctive ideas (like strategy or procedure), we naturally also want behavior that improves and leverages their value.

For example, we want high performance in compliance to a valuable procedure -- which makes that behavior itself valuable. But that sense of behavior should be understood as "skill".

Intellectual behaviors such as analysis, decision-making, and invention are also coveted skills -- but they make their distinction, and ultimately their value, in their ability to create and modify important circumstances and intellectual assets.

If we say that we can apply intellectual behaviors and intellectual assets to a situation, have we covered the bases for saying that we have applied "knowledge"? Not quite.

Under the pressures of demand, an organization's assets primarily represent its capacity while its behaviors represent its competency. But in our overview of knowledge, a third and final dimension, joining intellectual assets and intellectual behaviors, is what we might call "intellectual predispositions" -- which brings preferences to join capacity and competency.

Now, with those three dimensions of knowledge influence, we can begin to catalog the types of differences that we want assets, behaviors and predispositions to make, and in that way list key terms of assessment. We can cover opportunity comprehensively, and we can also "backfill" issues frequently ignored about operations.

Amongst our catalog of differences, we must also have clarity and confidence about what final impacts we really need, and then about whether the contributions of the assets and behaviors (capacity and competency) are actually supporting both the progress and potential towards the target impact.

If our key objective is maximum positive economic impact, the challenge will be to distinguish how knowledge drives economically significant progress, and how it drives economically significant potentials, related to the desired ultimate impact.

We'll especially want to understand how knowledge helps our progress, potential and desired impact to align with each other. Or else!

The fact is, we could do a bang-up job of executing on differences that don't really matter amongst our goals and priorities, yet still affects our economies -- for example, perfecting compliance to standards that don't solve our problems.

And highly potent value can be created that doesn't have much economic impact -- for example, a well-executed product perfect for only a very tiny market.

What will emerge, though, is that the interrelationship of these issues is not strictly linear but instead is interwoven -- more of a network of influences than of a chain. Managing assets, managing behaviors and managing predispositions each have their own way of affecting progress, potential and desired impacts. But the way that knowledge affects one dimension also affects the others, which changes their alignment. In that way, managing knowledge value is a lot like managing a network.

VI.

To envision the scope of interrelationships in the alignment, consider the following.

This matrix is one way to describe how knowledge influences alignment. Here we see the representations of numerous familiar business instruments that are directly related to knowledge and that in turn are distributed to shape operations, opportunity and objectives. Our familiarity with the items in this view also lets us see more readily that changes in one place can alter the support, status or direction of another place in the picture.

Managing knowledge will include managing the making, certification and purposeful utilization of it at each point in the matrix. But through our familiarity with these instruments, we already recognize that the point-to-point connections are vital to the health of the business effort. Given that, managing knowledge value comes in when we know what difference we want the knowledge to make at each point, and how those differences relate to each other.

With things put that way, it's easy to say that at all points we just want knowledge to make things "better".

But better should mean that they become more reflective of the target impact while improving the way they interrelate. For example, a faster, cheaper or prettier way to do something is better if it keeps or increases the level of support it offers to other factors that depend on it. Otherwise, diminished support can easily make the other factors riskier and likely more costly. The sensitivity to this is typical of taking a portfolio management approach rather than an accounting approach. What we're working with is the "knowledge portfolio"...

VII.
From here we can begin to sum up how knowledge is valuable.

Our matrix has a left-to-right connection of three perspectives: operations, opportunity and objectives. As management modes, what forwards knowledge influences from operations through to objectives and beyond is technique, strategy and purpose. We readily recognize this in certain management artifacts:

- Earlier, Best Practices (through technique) was an example in which the influence of knowledge on operations was directed in support of opportunity.

- In like manner, Planning represents strategy's bringing knowledge influence on opportunity, with which we would likely support objectives.

- To that, we can add that an organization's Positioning represents the knowledge influence that purpose has on objectives, which we use for supporting stakeholders.

Together, the three things illustrate the organization's competency, capacity and preferences systemically establishing themselves -- three characteristics that we already know are criteria in economic justifications. These characteristics are also recognizable thematically as in the examples within the picture below:

Meanwhile, vertical linkage in the matrix connects the three knowledge dimensions. Looking back at the cycle of leveraging knowledge value under demand, we saw a picture that corresponds to these dimensional links: predispositions should direct appropriate behaviors; and in turn, behaviors should produce relevant assets that communicate and transport capacity from one time and place to another in the organization's experience.

In that picture:
- intent is a source of conditions;
- form is a source of content; and
- function is a source of capability.

Knowledge affects the measurable conditions, content and capability of the organization -- characteristics that we already know are monitored for the economic impact of their use. Overall, the cycle addresses the question, "of the things that we want to do, how do we get them done?" This explains why improvement initiatives focus on investment, refinement, and redeployment in those three areas. While those initiatives typically look to business "intelligence" as a primary means of gauging the importance and progress of the efforts, we saw that "knowledge" is more instrumental to shaping the actual changes that the efforts make. In other words, that is why knowledge is valuable.

VIII.

One of the key challenges to working on improving the value of knowledge is to assure visibility of why certain kinds of knowledge is appropriate in given situations. In general this is thought about as "expertise", but in an important way that misses the point. Along with information overload, an organization also has a degree of complexity that often obscures the reasons why knowledge is available or not in given circumstances. Automation certainly tries to address this problem by minimizing it risks. But behind that automation should be a visible logic of knowledge management that corresponds with the assessment matrix and alignment cycle we have now seen.

As a closing explanation, but one that is a work in progress, the following picture identifies that knowledge is more likely manageable when its form and function aspects are more visible. This visibility helps to begin the process of optimizing the current knowledge deployments into a configuration that, as outlined by the discussion above, will more systematically support programs for increasing their value.

Posted by Malcolm Ryder at 12:18 PM | Comments (0) | TrackBack

December 7, 2005

Just what's so manageable about Knowledge Management?

Knowledge Management (KM) is an idea that has been stretched into a gigantic umbrella term, under which a vast range of items are crowded together by a common theme: getting the right knowledge to the right person at the right time.

The attention to personal use of knowledge (instead of data) is a great development in the way managers attend to work being done within the organization -- especially when the work is either required (where the pressure is to drive high performance) or exploratory (where the pressure is to create new value). Recognizing the distinctive role of knowledge is easier now, because we have enough experiences of competitive advantage being attributed to a superior organization's "knowing something that the competitor did not".

The motivation to reach "knowledge parity" is more than sufficient to drive adoption of a KM goal and capability, but it often confuses the issue of what to know and how to know. Worse, the issue of "how to know" is even further confused with how to get what is 'known'...

Consequently, the idea of managing knowledge is often implemented in incomplete, misdirected, or over-complicated ways.

Despite usually seeking integration of knowledge resources, KM implementations make changes in the organization that risk dis-organizing established objectives and tasks relating to:
- developing concepts,
- processing information, and
- delivering content.

Linking incompatible systems, or using a system on the wrong thing, can quickly misplace, bottleneck or misroute the supply of concepts, information or content versus requests. Production, maintenance and delivery of these things may all be subject to different cycles, attendants, costs and maturity levels -- so blending them presents a lot of reconciliation to be discovered and executed beforehand.

The first step in preventing or repairing the confusion is to identify how the differences between concepts, information and content are important, which is what generates demand for them.

- Concepts represent developed knowledge. However, because concepts can be hypothetical, it's important to realize that they are not necessarily "facts" -- but instead are ideas.

- Information represents facts that are available. Because facts are the result of agreements about observations, it's important to realize that context and perspective have a lot to do with whether facts are useful beyond the time and place of their initial creation.

- Content represents the result of packaging ideas. Because packaging is driven by utilization requirements, content makes ideas suitable for specified types of occasions, leaving the same ideas less suitable for other occasions except in different packaging.

Because of those three conditions, it is unsatisfactory and unwise to simply respond to the blanket demand for "knowledge" by distributing all information through every potential delivery channel. Each of the three issues above is a different facet of providing for the quality and availability of knowledge.

I.

Instead, the first move is to start organizing the recognition of how knowledge is created, so that its sources and arrivals in the organization can be logically anticipated from different activities, systems and contributors.

To begin with, there are always events occurring around us, whether intentional or not. Knowledge development begins with observation of an event; then the observation is progressively transformed for relevance to our known purposes. The progression begins with confirming and classifying the observation, to create "data".

This immediately points out that, contrary to popular belief, data is not actually "neutral" -- instead it is simply vulnerable to being handled indifferently. However, when the data is deliberately served to a given occasion (such as a task), it is next used to describe and diagnose the occasion's subject, which creates information. (For example, the "subject" could be an expense authorization, or it could be a sales transaction, even though they could be two different views of the same thing.)

This points out that different occasions can produce different kinds of information from the same data. (In most organizations, an "occasion" is most often identifiable as a particular moment blending people, process and technology.) So, occasions are not neutral either. In most organizations, management directsoccasions more than anything else -- creating and manipulating them in order to focus the activity within them on any number of requirements. This level of supervision later typically treats the activity as "behavior" and diligently reports on the behavior. Similarly, the activity seen elsewhere, in other external settings, is also thought of as behavior -- whether it is systematic or not, and whether programmed or ad hoc. In that sense, reports on behaviors make up a huge proportion of the "information" recognized in an organization.

But management needs to take a further step-- of determining the significance of the report (i.e., the characterization of the behavior). Ordinarily, formally established operational requirements provide the perspective or context within which the significance of the information is evaluated. That context drives selection and prioritization of the available information, looking for relevance. When the relationship of the information to the requirements is understood (or agreed), "knowledge" has been produced.

II.

It's exactly at the stage where information must be processed that organizations are pulled into different directions -- by lack of planning (including opportunism), or by apparent competition between different ways to proceed. However, most organizations have chosen to tackle the urgencies of competing accountably, by emphasizing better awareness of cause-and-effect. This effort has evolved into "business intelligence", which greatly improves the feasibility of competition. But the other problem of equal strategic importance is the need for effective responses to sudden and ongoing change. Changing effectively is the capability that offers the organization continued viability as a competitor. This is what drives the evolution of information management into knowledge management.

But what drives the goal of doing knowledge management into practice? Individual members of the organization must also shift from "accountable competing" to "effective change" -- and they must identify the opportunity and appropriateness of being agents of change when it can matter the most.

To have that happen, the minimum implementation requirement is that the members have great visibility on the organization's resources for developing and leveraging knowledge -- and the organization's managers must configure those resources for efficient access and maximum relevance to the members' functional requirements.

III.

Getting an implementation to that point will mean transforming a challenging amount of legacy resources and dependencies -- not just installing new things in a "greenfield" environment. In the organization, persons already significantly "self-service" their knowledge needs through a combination of automation technology and intuition. Configuring the technology is a major issue, but even bigger is the challenge of changing personal behaviors.

The picture below illustrates how knowledge-availability is organized behaviorally within the organization's operations...

The key observation is that from the individual's personal perspective, relevant functional "knowledge" tends to fall within three general categories: expectations, experience, and expertise. Most individuals, in most instances, will call on some blend of those things, from whatever reserves or sources they are conscious of being able to access. What is less apparent is that the different types of knowledge have a distinctive bearing on different types of organizational requirements. The availability of various "information systems" tends to make people think in terms of the kinds of information delivered by dedicated tools, instead of thinking about the kinds of knowledge most appropriate to requirements. Putting the cart in front of the horse that way leads to disorganization and waste.

The other typical point of reference for individuals is the collection of explicit instructions that make up what is often considered to be the "official" knowledge of the company -- namely, its practices, rules and skills.

But over time, a major counterpoint to the reliance on instructions becomes apparent -- already indicated in the above picture.

The organization's formal codifications of practices, rules and skills do not simply "overlay" the three types of knowledge, but instead are products of the way knowledge is combined. For example, experience and expertise together generate rules.

In fact, the three types of knowledge (expectations, experience, expertise) align more to the contexts (operational, cultural, environmental) of the company's requirements than they do to the practices, rules and skills.

In effect, this leaves the practices, rules and skills -- as "products" -- more variable than the underlying knowledge factory. This variability is a reality that we already recognize, based on such normal "managed" situations like: personnel changes; practice additions or alterations to accomodate customer or partner segments; and of course, new rules from new bosses or processes. In turn, it shows that overreliance on those shifting sands is risky. Instructions are really just a form of content.

IV.

Because of that difference between the knowledge and the instructions, it is more obvious that "knowledge management" per se has to do with the way knowledge users leverage their knowledge reserves and resources -- not about how familiar they become with the definition and implementation of practices, rules and skills.

We can map out how this leverage already naturally occurs. Knowledge users satisfy their needs for knowledge by reaching out to preferred suppliers. In this dynamic, each of the key contexts -- operational, cultural and environmental -- features a knowledge "persona" that the knowledge user consults and/or becomes. The dynamic is about why the user prefers one persona or the other.
- Operational persona: the "Master"
- Cultural persona: the "Hero"
- Environmental persona: the "Wizard"

The personae have practical roles that show off their respective strengths.

Operational Masters combine skills and practices. Highly sensitive to the perspective of the corporate owners, they exert tremendous influence on quality issues, in alignment with setting and meeting expectations. Masters can address the question, "Is this really going to work?"

Cultural Heros combine practices and rules. Highly sensitive to the perspective of corporate customers, they have outstanding impact on how advantage is derived by negotiating demand, drawing insight from their broad experience. Heros can tackle the question, "What do they really want?"

Environmental Wizards combine rules and skills. Highly sensitive to the perspective of competitors and/or the nature of adverse conditions, they have the driver's seat when it comes to managing change, reflecting capability drawn mainly from expertise about how things can work. Wizards prove their mettle answering the question, "how can we beat those guys?"

Those are practical assignments, which historically have been opportunties for the personae to generate success stories. But those circumstantial distinctions are less important than is the general availability of these personae as resources for multiple modes of knowledge. The three personae are not mutually exclusive but rather represent three fundamental points of view on any given situation.

This stages a wide variety in knowledge availability within the organization, which challenges manageability.
- In practice, a given individual may consult, and/or perform as, one or more of the personae.
- Performers in one persona may consult a different persona.
- Meanwhile, at the given time, the availability of support offered, and/or the level of accomplishment achieved, may be different from one persona to other.

Because of all these possible variations in knowledge types and knowledge levels, it is not always evident that the knowledge source chosen and used by an individual (to give or get knowledge) is the best one for the occasion at hand -- and this particularly includes occasions where the person's knowledge source is himself.

But while each persona is significant independently, what is finally most interesting about them is their collaboration.

In the above diagram, the strategic importance of their cooperation shows up as the company's issues regarding position, innovation, and agility. For example, when a Master and a Wizard combine their respective strengths in "quality" and "change", they can develop solutions that produce safe, effective agility. The corporate owners particularly enjoy this agility as a competitive capability. In like manner, Masters and Heroes combine strengths to fortify the company's (market) position through advantages derived from quality. And, Wizards and Heroes together support or even drive effective innovation.

V.

KM implementation can proceed based on objectives and priorities supported by the considerations above. The key is to identify organizational roles that can or should take advantage of knowledge-provisionroles to exert influence on corporate goals. For example:

Then, those organizational roles should be enabled with an infrastructure of tools, policy and incentives to mature and exploit the knowledge roles.

Another critical part of that infrastructure is content. Here, the function of content is to make knowledge more accessible, portable, and certifiable. Knowledge-users should be able to rely on content to help them see, develop and utilize the balanced, integrated range of key knowledge providers. Content also has the responsibility to indicate the strategic options available from the influence of various roles. As shown in the following table, content typically offers documentation of the model we have examined above. We can usually find three major categories of documentation, that add up to effective support of the worker and organization:

All together, this content offers a corporate knowledgebase -- strictly meaning a repository of current explicit guidance based on knowledge.

Using the knowledgebase is not simply a matter of exploring the table of contents and making "deposits or withdrawals"... To get value from the knowledgebase, the company must invest what is in it against some purpose.

The most important general use of knowledge is to create or fortify an opportunity.
Above, we looked at three flavors of opportunity -- position, innovation and agility -- as generated by attention to quality, advantage, and change. In adapting the organization to pursue the opportunities, what we find is a need to attend to a set of related performance success factors or constraints.

This points to a crucial revision of what we think makes "knowledgeable" organizations competitively superior: it's not that they "know something that the other company doesn't", but more fundamentally, that they are more capable of effectively using the knowledge that they have. Their success factors for utilization are seen in:

- Communications (providing ideas);
- Collaboration (providing structure); and
- Compliance (providing permission); adding up in support of...
- Competency (providing ability).

KM keeps an eye on those success factors by mobilizing tools, policy and incentives to "configure" the use of knowledge in terms of those factors. A planning chart like the following helps to identify existing and potential requirements and components for this configuration.

This should amount to support of a highly visible and available virtual knowledgebase. (The "knowledgebase" exists because of strategically managed uninterrupted on-demand access to relevant knowledge.)

Then we want to assure that the knowledgebase content, in the way that it was developed, also incorporates the success factors of knowledge use. As we'd said in the beginning, content makes ideas suitable for specified types of occasions, leaving the same ideas less suitable for other occasions except in different packaging. What we finally want from content (whether the content is solutions, standards, or priorities) is to have those success factors incorporated in the knowledge-user's work -- through the handling and purpose of the content.

[To be continued.]

Posted by Malcolm Ryder at 8:35 AM | Comments (0) | TrackBack

November 29, 2005

Smart vs. Dumb

Here's a thought: what's the difference between dumb and stupid? Dumb is when you're wrong and you don't know it. Stupid is when you're wrong and you do know it. If you're right and you don't know it, are you smart?

This looks like it leaves organizations with only one out of four options to deal with reality: when you're right and you do know it.

Managing knowledge has a lot of sex appeal now, but managing dumbness has been around for a while.

There's the infamous "Need to Know Basis" -- applied to the occasions where for the thinking done by the audience in question, more is less! It features the speech, "Take my word for it, you don't want to know!" This cool bit of judo, or Enlightened Dumbness, is a vital tool to have when the smart thing to do is to lower the risk of increasing the risk. How parental!

Back out on the streets, there's the ecstatic expletive "Stoopid!" -- applied to something so self-evidently excellent that in order to not notice, you'd have to be unconscious or ... stupid. (Although, you wouldn't be "Dope!" because when you're Dope you are pretty much Stoopid, only probably just for the moment instead of endlessly like Stoopid things are.) This is the label on that box that those "best practices" keep arriving in from all those other companies... The fine print says, "Take my word for it!" Admittedly a weak form of self-evidence, but what a great excuse to not have to know something else.

Enter "knowledge management." A discipline dedicated to the twin goals of enlightened dumbness and informed ecstacy. An environment where most of what gets known is the things that are the best to know. An important new model of organizational execution. A rave.

A rave? Spontaneous formations of virtual communities... built around certain ways of expressing or celebrating a theme, counting on targeted just-in-time communication of information from sources whose credibility is based on the channel they use to transmit -- but whose channels are spontaneously formed through the content itself.

Gossip.

This is a good thing?

The conventional organization is based on distributing (pushing) responsibility for what you're aware that you know. But how are you aware of what you know? Well, you're told.

Ironically, the knowledge-based organization is based on taking (pulling) responsibility for what you're aware that you don't know.

Oh! You mean Research.

Does this make an organization smarter?

It probably doesn't make the organization smarter unless the research itself is well organized.

A perfect example of what organizes research is requirements. As with a rave or a community of gossip, a knowledge-managed organization has a characteristic feature of the requirements already being globally acknowledged. The problem for most organizations is to communicate requirements globally without them losing their context. This communication often can be accomplished only just-in-time, so pending that the organization has only latent knowledge. In responding (with research) to requirements, the organization discovers what it knows.

In this way we can see that the distinctive contribution of KM to the organization is that is helps the conversion from being unaware of what you know to being aware of what you know. The key to making the organization smarter, though, is to have better requirements established.

The complementary problem to solve is the one of moving from being unaware of what you don't know to being aware of what you don't know. But assuming this is accomplished, ending with requirements being established, its value quickly drains away unless KM follows up by driving response to the requirements.

A final observation to make about knowledge management is this: management is a discipline that cycles attention to something from a concept and design (i.e., research) stage to development, deployment, control and assessment stages. Over extended periods of time, the most competitive advantage of leveraging knowledge progressively moves from the control point in the general management cycle of attention backwards towards the concept point.

(To be continued.)

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October 31, 2005

The Latest and the Greatest

What's the value proposition for your knowledge management initiative? Our colleague Bruce MacEwen offers a fast situational analysis that reminds us why we need to convert knowledge from being an asset to a resource -- in order to get value.

Archestra's common ten cent definition of a resource versus an asset is that a resource is an asset with a job. From there, one view on value is that the asset utilization is more-or-less "productive", stimulating a reward greater than the cost of its utilization. But another view of value begins with the importance of the utilization --as opposed to the importance of the asset (in this case, knowledge) or the utilization's cost.

In Bruce's example, a premium is placed on the ability to access and process preferred knowledge on customer demand. He offers at least two ways of thinking about that preference: immediate availability and proven quality.

In the actual practice of offering knowledge, communications and propositions surround the notions of availability and quality so thoroughly that when it comes to establishing "value" most of our energies are dedicated to closing the gap between perceptions (what we think the knowledge is doing) and prescriptions (what we want the knowledge to do).

Another colleague used to say to me that his number one fear was The Bad Client, who revealed themselves with the persistent position of "I don't know what I want but I'm not gettin' it..." If a target user's perceptions devalue a knowledge offering, the culprits might be the way related information is communicated and the way proposed concepts are familiarized. The idea of "applied knowledge" is a standard way of aiming at generating value, but it takes a pretty good hit when communications and proposals are failing.

Put that way, the challenge of extracting value from knowledge seems inevitably to call for training. Let's not forget that training actually tunes the provider of knowledge and the recipient to each other... But with the intensive business focus on converting the "resourcefulness" of knowledge instantly into gain, two related notions take the foreground: just-in-time learning, and knowledge as the in-the-moment experience of "understanding".

Let's assume that the first notion requires the second. What is mostly interesting about the second notion is how it might parallel the experience of language, in which a seemingly infinite and uncategorized variety of statements may be constructed on the fly.

If, instead of utterances, "understandings" can likewise proliferate in our community, with spontaneous uncataloged diversity from some fundamental common competency, the most important target of our effort to manage knowledge could be more akin to achieving "fluency" than to profit. It should simply be a case of putting the horse in front of the cart. Fluency would explain how and why so many on-demand knowledge deliveries would be successful. So as we figure out ways to cultivate successful on-demand knowledge, we should try to maintain the objective of increasing fluency instead of episodic gain.

Posted by Malcolm Ryder at 10:48 PM | Comments (0)

October 8, 2005

Conceptual Capital versus Intellectual Property

Innovation continues to gather more momentum as a primary economic "performance" improvement objective in the post-cost-cutting enterprise. But if innovation is a new top gun in the "competitive advantage" arsenal, then what does it mean that big companies are starting to give away their innovations?

The most interesting choice for breeders of innovation is to decide whether the innovation is more beneficial as conceptual capital to spread around like investments, or as intellectual property to spread around like products.

I.

With today's web-based content discovery tools, there is much more often the case where as a matter of historical fact we find that some great ideas have occurred in more than one point of origin, independently and even concurrently. Under examination, any particular source of the concept might truthfully claim "originality" -- so what does this mean?

It means that a concept is simply not necessarily unique. In such cases where one idea evidently has multiple origins, in what way is it important that the concept has "owners"? Unless something would prevent yet more "original" (not "unprecedented") occurrences of the concept in yet other locations, then there is no obvious reason why the concept itself should be considered "property" although the rights to certain versions of it might be. This shifts attention to the mechanism that controls and distinguishes the versions.

Consider this from The Idea Economy: Battle Over Right to Sell Knowledge, James Kantner's October 3, 2005 article in the International Herald Tribune (reprint via the NY Times):

"Like any other form of property or asset, patents can be bought, sold, leased or mortgaged. Businesses even give patents back to the government in exchange for tax breaks. Start-up companies use patents -- often their only collateral -- to lure investment from venture capitalists... IBM's patent strategy helped make research into 'a profit center rather than a cost center,' said Dam, now an emeritus professor at University of Chicago Law School."

These cases involve an issue of "ownership" -- which we can break down for examination in several different perspectives including:
- authorship;
- usage rights; and
- asset claims.

Using those three factors, companies find various ways to charge for access to the ideas.

But the main thought that crosses my mind is that knowledge is essentially more like capital than it is like product. For that matter, most conceptual innovation, whether given away or not, has never become recognized as intellectual property, and most intellectual property has never become a significant commercial asset.

Why not? Because, most conceptual innovations are not practically applied strongly enough to develop visibility as a coveted proprietary item. As any serious art student who went "professional" knows, the amount of great art never finished and never circulated far exceeds the amount ever known and bought by parties other than the work's creator.

The flip side of that coin is that because artists study the work of other artists, the influence of the larger group of under-the-radar art is easily as strong as the influence of that which was sold -- if not stronger. That brings up the prospect of capturing value from the influence (communicability) instead of just from the sale (transferability of ownership).

II.

For a competing enterprise, circulating concepts is a sensitive issue. On the one hand, giving away ideas is neither very risky nor helpful if those ideas can't be used by others in a practical way. Practicality calls for having additional ideas about how to use the ideas received -- whether that results in something beneficial or harmful to the donor. If the innovation in question is too difficult for other parties to handle, you might see giving it away as being more of a gesture than anything else. But that shifts attention to whatever mechanism controls the circulation and directs the ideas to wind up in "capable" hands.

Usually, property is the default perspective on the value of distributing an idea. Making an idea into "property" requires holding its circulation back in some way. Protecting intellectual property typically means controlling an idea's exposure and accessibility for the benefit of predesignated parties who pay for the privilege. Uncontrolled exposure or distribution contradicts the idea of property.

But on the other hand, due to the web, the cost and difficulty of accessing concepts has dropped so much that the effectively available audience for them is orders of magnitude larger. In turn, that availability of ideas spawns the increased followup occurrence of new and also possibly similar ideas in a wider range of unrelated (i.e., independent) locations. In massively increased distribution, concepts are at least like currency if not obviously like capital. We can't go so far as to say that the web makes companies look like they're printing money, though. However, since concepts cannot be reeled back in after they are released, what makes them into "property" is restrictions on the right to use them and on the effectiveness of those rights. While concepts are inherently more or less communicable, rights to them are artificially more or less transferable.

III.

Importantly for the asset-minded, the new degree of ad hoc exposure/distribution might easily mean that a given concept can now "seed" many more potential properties than before. This makes conceptual innovations clearly more valuable (like capital) as resources, and potentially more valuable than they are as products. But that shifts attention to the mechanism that nurtures the concept to an application and, getting back to the competency issue one might expect that some nurturing mechanisms are more successful than others. Thus, buying stakes in superior developers and donating conceptual innovations to them from the stockpile is a strategy that reduces the risk of wasting cultivated innovations while improving the cost-benefit ratio of generating them.

Companies increasingly recognize that ongoing operations and workforce skills combine to spontaneously generate innovations that were often not solicited or foreseen. Switching to a purposeful cultivation is one major element of "improvement". But the more complex question and philosophical choice is, would the investment-style strategy for lending conceptual capital be more valuable than a vending-style strategy for selling intellectual property?

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August 18, 2005

A Management Support System for IT Service Value

Very recently I received an invitation from a colleague, Eugen Oetringer from EDS in the Netherlands, to study (and share commentary on) an IT Strategy Management Process design.

The most prominent feature of the design, in my first viewing, is the solution that it proposes to the practical problem of just-in-time research that is inherent in conducting service delivery while coping with change and diversity in IT operations. In fact, the design's emphasis on the responsibilities for "development" and "production" anchors its concepts in terminology that is inherently compatible with addressing Business clients in terms of specified quality and value. The noted challenge is that specifications are forwarded into operational environments that are often not built or managed to ensure successful communication. The consequence of that challenge is that alignment is forfeited or damaged between development and actual production, the second link (after specification to development) in the enterprise's value delivery chain.

Also at first reading, it seems equally valid to consider the design as a governance model instead of as a strategy management process. But for the sake of retaining appreciation of the scope of the design's importance, it may be more useful to emphasize that a process for managing the execution of strategy will have:
- a model that guides it,
- a performance objective that relies on compliance, and
- technologies that support the practical implementation of the model.

Eugen's design explicitly details those items in the context of accountability to business needs and policies, thus linking it conceptually with governance.

That said, the design's primary objective of describing how to bridge the gap between development and production winds up exploring how knowledge management supports change management in order to align IT with the business. One of the most important points to take away from the design is that "strategy" is a set of knowledge to be managed, and cultural adoption of the strategy is a result of empowering users to leverage the knowledge in order to adapt.

What does the support of this leverage look like? It is strategy lifecycle management. As the author puts it, "The IT Strategy Management Process takes the strategy from the owner, runs it through an approval workflow, publishes it to the target audience, drives for compliance, takes the feedback from the user communities, provides the feedback to the owner and drives the owner to release an updated version in a central repository."

The whitepaper reviewed above is here, and its parent book from the same author, published by Van Haren Publishing, is titled "The IT Strategy Management Process: Supporting IT Services through Effective Knowledge Management".

Posted by Malcolm Ryder at 7:59 PM | Comments (0) | TrackBack

Blink - Using the Mind's Eye

Malcolm Gladwell's book, Blink, focuses on the adventures of the unconscious mind, in which pattern recognition collapses the timeframe of decision-making from minutes, or even months, to seconds.

But Gladwell cautions that speed kills as easily as it charms. Thus he sets out a few basic problems that should be addressed in the Unconscious Mind Owner's Manual. His cautions are good, but I'll propose these summary orientation notes anyway.

How do we decide when to use the unconscious mind?
- turn it on for events requiring decision-making under psychological time-pressure.
What's old about this? Relying on experts in these instances.
What's new about this? Refusing to replace experts with science.
The takeaway: patterns visible to experts are not the same as hypotheses visible to technicians.

How do we operate the unconscious mind?
- by ignoring extraneous information
What's old about this? Several thousand years of Eastern philosophy.
What's new about this? Analytics as opposed to metrics.
The takeaway: Critical correlations are usually few in number; think of Pareto's Principle, the 80/20 rule.

How do we make the unconscious mind safe for use?
- exposure, education and training
What's old about this? Nearly everything.
What's new about this? The return of the Heisenberg Uncertainty Principle; now available over-the-counter in a package with a warning label.
The takeaway: With great power comes great responsibility.

Gladwell's keynotes point out that patterns living in the unconscious mind develop over time from thousands of observations. This is what makes experts Experts. He also cautions that misapplying a pattern, that is, using it out of context, is a serious mistake. So, since we can't all be experts at lots of things, the most difficult part of our interest in using our unconscious mind is knowing in the heat of the moment whether our confidence in it is really appropriate to the occasion. This problem of "context" immediately suggests some options that many people might consider to be "best practices":
- get multiple experts
- specialize our own range of involvement
- use as much time between decisions to increase exposure to similar situations

What does this all come down to? The influence of mental models is the core of the book. In Blink, the central hypothesis that the Getty Museum used was trounced by a bunch of patterns, but both approaches were mental models. Gladwell just tries to help us understand where the two types come from, so that we can appreciate why one worked better than the other.

Going along with that, one of the truly huge messages from the book is that experience is a great trainer, but not always a great teacher. High-speed decision-making relies on experience, but effectiveness still comes from an accurate sense of where you currently are -- which requires high-quality current information in perspective. Thus, the "success" of high-speed decision-making relies a lot on properly recognizing the problem at hand, and then also having the right exerience for it. In other words, solving the right problem might be even harder than solving the problem right. We need to be wary of the silos that experience can put us in.

Another message that runs throughout the book, under the umbrella issue of "problem-solving", is the contrast between scientific management and intuitive leadership. In the stories in Blink, it appears that the intuitives keep beating the scientists (for better or worse); but it turns out that the leaders keep beating the managers. Perhaps the punchline of Blink is that we want to be "scientific leaders", because our intuition derives from what is essentially a scientific evolution -- observe, test, refine, observe again -- of patterns that live in our unconscious mind and that in the heat of the moment become vibrant and noticable. Meanwhile, our leadership springs, just-in-time, from the intuition and the willingness to use it -- which, simply but profoundly, often means to accept its spontaneous insistence on being noticed.

Where on the bookshelf should we keep Blink? I put it right between Thomas Kuhn's The Structure of Scientific Revolutions and Ian Fleming's James Bond thriller Goldfinger. On the one hand, Kuhn describes a lot about why we have the patterns we have, and why we hold onto them. On the other hand, Fleming describes a lot about the pressure that provokes intuition, whether it's life-and-death, gambling and love, or pride and anger. In all three books we get a good strong blast of the glory and folly of thinking.

Posted by Malcolm Ryder at 6:52 AM | Comments (0) | TrackBack

August 12, 2005

When "ROI" means Return on Insight

Best quote of the week comes from Thomas Davenport, director of research for the executive education program at Babson College, who was interviewed by CIO Insight magazine:

The only way we can get people to use knowledge on the job is to understand how they do their jobs, and then figure out some way to inject knowledge into the course of their day-to-day work, not make it a separate thing [they] have to consult when [they] need knowledge.

In this lengthy interview, Davenport also leaves us with the ironic thought that this might be pretty difficult to do for knowledge workers (!) because so often knowledge workers don't expose or formalize the process(es) that they use to get their work done.

Well, that's gotta hurt. As a group, knowledgeworkers are these days tagged as the source of innovations that are the source of business growth. Growth is good, yes? So...

Setting aside the alchemy of k-worker production, we can still always say that the rate at which innovations prove to drive growth is a performance measure, and the resource efficiency with which k-workers produce effective innovations is another performance measure.

But certainly there can be innovations that, regardless of how efficiently produced, prove not to be growth drivers; and there can be innovations that were "produced" outside of any intentionality other than ultimately acknowledging the effectiveness of something unexpected.

This reminds me to bring up Post-It Notes and Silly Putty, two famous accidents that luckily got seen in a different way, were trademarked (or something just as fierce; please take notice), and went on to revolutionize work and play. They exemplify one of the three types of innovation:

- new solution to new problem;
- new solution to old problem; or,
- old solution to new problem.

But which one? What's so interesting about deciding which type of innovation they represent is that it depends on who the customer was. Let's face it, for some people, being able to temporarily copy a comic strip and bounce the copy across the floor had never been a problem. For them, the discovery of the gooey means to do so was... enlightening? Aggravating? Confusing? I found it Compelling, almost shocking, as did my fellow fourth graders.

Thanks to some guy with insight, when the accidental putty was christened "Silly" and re-purposed, it became an innovation instead of sunk cost. How do we assess the "productivity" of that sequence?

Effort of all kinds involves on the one hand the intended vs. unintended, and on the other hand the expected vs. unexpected. What are the possible outcomes? We actually have names for them that are already pretty conventional:

- Intended and Expected: product
- Intended and Unexpected: experiment
- Unintended and Expected: risk
- Unintended and Unexpected: accident

In hindsight, the lab work that failed its purpose yet output the putty dubbed Silly could be called "research" (experimentation); while in foresight, the intent to "salvage" value from the putty could be called "development" (production)!

Knowledge that was contributing to (or at least consumed by) the research is one thing; knowledge that drove realization of the market potential of the re-purposed putty is quite another. The labwork methodology was likely pretty well prescribed, in an explicit way. The likely tacit and intuitive method of recognizing "Silly Putty" might simply not be practically proceduralized. Is this difference one of being mechanical versus organic? Scientific versus artistic? And/or other dimensions?

This inspires me to list key touchpoints in a dynamic that might account for both the "failed" labwork and the "successful" marketing vision:

inspiration -> improvisation -> insight -> innovation

Inspiration: much of this comes from observation, experience and especially memory; deciding to see or think about something in a certain way.

Improvisation: this is very much like exploration and especially testing, whether it be conceptually and logically as with "thought experiments", or instead materially as in the lab; designing the relationships indicated within the inspiration.

Insight: this is very much like comparison and analysis, especially inference; understanding the implications of the improvisation.

Innovation: on a practical level, this is very much like categorization and especially contextualization; finally deciding what to do with the insight.

In considering modes of injecting knowledge into the "process" of knowledge work, we need to be willing and able to respect the difference between a dynamic and a process. The most important difference is that:

- a dynamic is the behavior of a network of simultaneous influences, whereas

- a process is typically and essentially linear even if it is able to contain detours, shortcuts and sideroads along the way.

It does makes sense that a dynamic can generate a pattern of behaviors that we might finally describe as a process if the pattern is recurring -- or more to the point, intentionally repeatable. But, it might be that the problem of increasing "productivity" in knowledge work is to feed information into the touchpoints of the dynamic in an effectively influential way, rather than to shoot for a process that might not exist.

Posted by Malcolm Ryder at 4:26 PM | Comments (0) | TrackBack

August 2, 2005

Laisse Les Bon Mots Roulez

I still don't know who Kathleen P. Wall is, but her collection of Cool Quotes for With It managers was too good to not pass on -- primarily because one of them is from a hero of mine, Eric Severeid. If you're too young to know who he is, you're still young enough to do something about it and get the credit; and there's always Google/Alta Vista/Teoma/etc.

"The chief cause of problems is solutions..." Eric Sevaried

"It isn't that they can't see the solution. It is that they can't see the problem..." G.K. Chesterton

"A solution is no better than its implementation..." Kepner and Tregoe

If you read her paper, you get a Gandhi quote too, but I didn't like it.

Oh yeah, okay, it turns out that Wall is (or was?):
Kathleen P. Wall, Vice President at CMS Healthcare Solutions, Inc., who has over 18 years experience as a management consultant, specializing in operations and materials management. Her background includes systems analysis, selection, and implementation; workflow optimization; and facilities planning.

Posted by Malcolm Ryder at 9:47 PM | Comments (0) | TrackBack

July 18, 2005

Collaboration and Analytics: driving production with intelligence

Most organizational managers may not admit it, but the myriad complications of managing costs lower in order to increase net operational gains mean that this approach hits a point of diminishing returns much sooner than anyone prefers. Thus, in order to increase value, the approach of growth-oriented management becomes an immediately critical alternative to cost-orientation. Collaboration and analytics are two of the strongest tools for leveraging existing resources towards value-generating growth.

How? Collaboration and analytics are two modes of discovering and synthesizing intelligence for driving production.

As such, they are both decision-support mechanisms that can make a critical difference to the effectiveness of operations within the time-span of the operation's execution.

In decision support:
- Collaboration, using coordination, especially integrates varied expertise to create competencies from at-large communities.
- Analytics, using formulae, especially distinguishes latent patterns to create information from data collections.

How do coordinating expertise and formulating patterns contribute expertise and information, at a level particularly critical to production value?

Actually, Collaboration and Analytics each provide competencies and information, to recognize and productively incorporate new and unexpected influences -- in less time.

One view of this involves seeing them work together.

Collaboration can leverage analytics by using analytical findings to support decisions that adjust or guide the integration within collaboration. An example of this would be to have, based on forecasts, certain links in a supply chain modify their individual current outputs and/or output schedules to preserve the timeliness, cost limits, volume or quality of promised deliveries.

Conversely, larger data collections can be developed more quickly via collaboration; so, analytics can leverage collaboration to explore a wider range of alternative data sooner. This, within a given time period, can produce more patterns and/or perform more validation of given patterns. An example of the former benefit is identification of viable product alternatives that attract new business or contingent actions that reduce risks; an example of the latter is determining from multiple perspectives whether an idea really meets a quality standard for stakeholders, such as through a peer-review process in academia or in business approvals for complex proposals.

In practicing collaboration or analytics, a basic problem is one of providing an underlying model for organizing the activity. However, in collaboration there must be a model for putting things together, and in analytics, a model for taking things apart. For that and other reasons, another view on their potential delivery of benefits must consider the two techniques separately.

Collaboration is a special form of co-operation, in which all participants are adhering to the same goal for the same reason. The model that is needed in collaboration will, in effect, offer operational objectives to be mutually respected by all participants. More importantly, the model, usually called a "policy", will prioritize activity options that are offered by the various participants or that develop as interim possibilities during operations. This sounds very much like how any process is regulated, but the difference is that in collaboration the operation is constantly open to new inputs that were not anticipated before the operation started. Collaboration therefore requires the ability to effectively re-organize the operational integration based on the new inputs. Distinctively, while the operation is already in progress, a collaboration invents the solution to reaching the goal.

Analytics is a special form of de-composition, in which a pool of data is tested for its key contents -- namely, what it might include that is pertinent to a given fact or assumption. The model needed for analysis, usually called a "hypothesis", describes cause-effect relationships behind "factual" events or conditions (states). However, in an attempt to discover and confirm significant relationships, the analysis must isolate and identify the key factors of the relationships -- thereafter looking for clues or evidence of the factors. Sometimes it turns out that the "suspected" factors are not the real ones, or that the factors presumably needing to be investigated are not relating as suspected. This detective work is usually mandated as auditing; but the difference is that in analytics (for example, with weather reports), it is more important to discover possible futures than the confirmed past. As a result, although analytics are typically used to find proof of something, the primary basis of value in analytics is actually an objectivity that is focused on credible explanations agnostic to the data.

In those various ways, collaboration and analytics should bolster management-based effectiveness. But what does that look like? It's fair to look at progress from the "performance" perspective that a business typically brings to measuring effects; progress means both sustained improvements in operational quality and timely development of desired business advantages. Since there are many management techniques for pursuing those outcomes already, what motivates an embrace of collaboration and analytics?

An important issue clearly suggested by collaboration's inventiveness and analytics's neutrality is innovation -- or the ability to take new approaches to problems, due to having freedom from prior restraints such as resources or points-of-view.

Yet "continuity" is no less important to support. Here, collaboration and analytics matter when a breakthrough is needed for progress that is not, so far, being successfully driven by the capacity of solo efforts. Flexibility and objectivity (as supplied by collaboration and analytics) are key to getting the needed breakthrough.

The challenge is that managing operations towards a repetitive sameness is a technique we have fully embraced in the name of process improvement. Yet all processes are constantly confronting the eventuality of change at many different constituent levels including their resources, controls (management) and beneficiaries (perceived value). The danger of protecting "as is" processes is that they will become inflexible or irrelevant over time -- in short, counter-productive. The shift in operational habits that collaboration and analytics both encourage is straightforward but potentially profound. It is nothing less than a different approach to effectiveness -- requiring us to:
- stop protecting (in the name of efficiency and predictability) the "as is" form of operation; and instead,
- work to grow the operation's effectiveness by continually shaping it to broader opportunities that are more extensively qualified.

For some managers, this may throw their dedication to "optimization" under unexpected pressure. But in that case, it becomes appropriate to give the idea of optimization a revised context, by working on it specifically to support operational growth. An example of this approach is the attention many managers give to pursuing optimization mainly within the guidance of maturity models that are growth-oriented, explicitly sensitive to how the manageability of change (i.e. agility) regenerates and multiplies capacity over time.

Posted by Malcolm Ryder at 9:07 AM | Comments (0)

June 24, 2005

Managing Knowledge in the Knowledge-based Business

Although few businesses immediately think of knowledge management as an extension of ERP, many kinds of enterprises have come to see their captive knowledge as a top-priority "enterprise resource" that must be managed.

The path they've travelled to come to this stance has been as varied as the types of operations they use to gain and hold their market positions. But two approaches stand out quite prominently amongst them all -- the "human capital" approach and the "process improvement" approach. Convergence of the two is increasingly dominant, as big companies rediscover what good small companies never forget: the process works because people bring knowledge to it.

As the well-known stories have put it simply, the rediscovery has often been a surprise:
- a business may have learned the hard way that the most valuable "asset" it has actually walks out the door every night at closing time; worse, a competitor stole a key player whose know-how made them the go-to player.
- the implementation of a great idea dissolved in the face of employee resistance; you can take a horse to water, but you can't make 'im drink...

Lessons learned from those experiences promote knowledge to the top of the list of critical success factors for productivity and value, and emphasize a need for coordinating the management of knowledge assets and change. This idea leaves a lot of details to be figured out, and that means a company has to find a motivation for not just starting it but keeping it up and seeing it through. Hopefully, we then can look at the highly motivated ones for a history of trials and errors that can teach us how it should be done.

When knowledge is actually your main product, could there be any greater motivation? Even so, KM can be elusive. This idea is behind the work of some key business analysts such as Bruce MacEwen, whose blog "Adam Smith, Esquire" routinely examines and advises on the problem of recognizing, planning and leveraging knowledge management opportunities and objectives in law firms. Always attentive to the people issues of KM, Bruce surveys KM evolution in articles such as:

KM, Meet "Peer Production" [my vote for the "must read" group]

Knowledge Management & Uncharted Professional Networks

What KM and Legal Outsourcing Have in Common

and...

Who You Know or What You Know: How About Both?

Try this trick at home.

Posted by Malcolm Ryder at 9:49 AM | Comments (0) | TrackBack

June 22, 2005

Managing the Productivity of Knowledge Work

Co-founded by a group of organizations including Accenture, Microsoft and Xerox, the Information Work Productivity Council drives a sustained collaboration intended to build a framework that measures productivity in "the information-centric business environment of the 21st century."

Early research released from the Council stresses the importance of some evolving ideas for understanding productivity in "information work and knowledge work" through a combination of lessons learned from manufacturing and I.T.

However, Accenture's Institute for High Performance Business emphasizes that a definitive reference model for measuring this productivity is still not on the horizon. And the IWPC itself states, "Although recent surges in productivity have been attributed to the use of IT, we still have no effective way of measuring or verifying its impact on information work."

In no small part, according to Accenture, this is due to ongoing debate about what to include in the kind of work being scrutinized for productivity, even including a sense that the popularity of the term "knowledge worker" might be missing the point by arbitrarily discouraging attention to equally important issues of information-based productivity.

But while Accenture makes those comments with a view on the internal needs of a given single business organization, I think it is absolutely necessary to step beyond that and propose that the "industrial" landscape of 2005, compared to the landscape of 1985 or 1965, quite loudly demonstrates increased "productivity" in the form of 2005's awesome diversity of types of viable business attributable in the main to business IT adopted in the last few decades. Proposed more simply, IT productivity really manifests itself at the market level moreso than at the enterprise level. Likewise, "knowledge productivity" manifests itself at a higher level than operations, in the form of a sustainable diversity of fully viable business capabilities. Discuss...

The intensity of the "productivity" investigation is certainly not at all in doubt, but the majority focus is on a somewhat different point, as both executives and academics are going "all out" to credibly factor the business reliance on information work (including knowledge) into the equation for business value and business valuation. That effort (and accompanying debate) would account for how knowledge work affects the conventionally measured productivity of a business's company.

Nothing strikes me as more certain to inhibit the effort as would a failure to unravel semantic confusions that inspire solving the wrong problem. Credit IWPC for stepping on that same stone, but in my view what follows from that point is a brief sprint down a course of resolution different from IWPC's -- not to a necessarily different or further endpoint, but in an alternate direction at least for the time being. My premise: there should be a view of the productivity of the actual work itself, providing a precedent baseline logic establishing why and when the work contributes to the productivity of its consumers and beneficiaries. In particular, I'll focus on knowledge.

1.

To begin, let's presuppose the reason behind our certainty about the criticality of knowledge in the modern business.

The fundamental operational issue for the business is to maximize opportunity at minimal risk, and to convert the opportunity into necessary benefit at minimal cost.

Correspondingly, utilization of knowledge is needed to, and proven to, impact opportunity in three essential ways:
- accelerate its development;
- differentiate it; and
- secure it.

Meanwhile, utilization of knowledge enhances the foresight and awareness of risks and costs pertinent to the opportunity.

The elaborations of that utilization are seemingly infinite, if accounted for by the organizational variations of one company to the next. However, the principles for the utilization do not change from one company to another, which means that there is a common reference regardless of the commonality of practices.

2.

The next presupposition, however, is the most critical one to my direction -- namely, that the term "knowledge worker" is NOT a synonym for "information processor".

IWPC's namesake distinction of information from knowledge is an important precedent for including "information work" beyond "knowledge work", signalling the belief that really meaningful talk about productivity requires an expanded field of terms. But a more fundamentally important observation to make is that "processing" is work, and that knowledge workers are process managers.

The key question is, what processes do knowledge workers characteristically manage? What's necessary here is to answer the question the right way, assessing the activity being conducted instead of the department (e.g., marketing or finance) commissioning the work. And this activity can be assessed in terms of knowledge, without the expansion into "information work", as follows.

This next short list highlights the distinction that is most relevant to the business issue of knowledge work productivity. These processes have outputs, and the business challenge is first to understand the significance of the outputs and second to understand the practical options for optimizing the generative processes:

(1) Strategics: a term coined here as a placeholder, this is mainly the interpretation of projected conditions with the goal of modeling their relationship to objectives.

(2) Heuristics: this is the use of a hypothesis as an instrument of iterative examination.

(3) Diagnostics: this creates and applies systems of identification and classification to distinguish the constituent elements of conditions and entities.

(4) Forensics: this discovers and determines items as relevant elements of a proposition that is a candidate "fact".

Then, the important consideration is the matter of how those activities are proceduralized, such that their respective underlying methodologies become portable to other workers. Logically, this is one of the responsibilities of the individual knowledge worker: initially adapting the activity's methodology to the real environment for operations. This adaptation is the basis of the activity's effectiveness. But the adaptation can also be assisted and formalized, to increase the efficiency of applying the methodology by the given worker. Any external assistance can be considered an "input" to the management of the processes.

Here, another distinguishing point emerges regarding direct measurement of knowledge work's productivity. The person identified as a "knowledge worker" could be evaluated as a "resource cost" -- but that type of evaluation is likely arbitrary without comparative benchmarks that describe the same activities and assists applied to substantially similar circumstances. In effect, the "resource cost" view presents the "knowledge worker" as a kind of function, for which availability and quality are actually the key measurable characteristics. But in that case the productivity issue derives from the management of the worker, not from the worker's own effort. We still want to understand the worker's effort itself.

3.

What really matters to business improvement is the impacts of the knowledge processes. For example, there are two basic categories of significance holding four types of results that should be treated as target business outcomes of the knowledge work:
- (impacts related to liabilities) risk mitigation and lower opportunity cost
- (impacts related to benefit) quality certification and innovation

As the source of these impacts, the knowledge processes managed by the worker thus protect and expand the business's measurable ability to affordably create and capitalize on opportunity. This means that, when successful, they produce a new "resource" of greater value than the business's ingoing investment in acquiring, deploying and maintaining the knowledge worker as a resource. That defacto statement of ROI addresses the motivation behind executive attention to the improvement of knowledge work.

Posted by Malcolm Ryder at 9:33 PM | Comments (0) | TrackBack

June 21, 2005

Harvesting Tacit Knowledge

Most experts in the knowledge management arena have special interest in the problem of "tacit" knowledge. This collection of knowledge, which is the knowledge residing in people's heads and not externally documented, is generally considered to be the "largest amount of knowledge" contained in a company.

Considering that people enter the membership of a company largely due to the knowledge they demonstrated or professed aforehand, this can't be a surprise, and indeed it isn't treated as one.

However, what becomes freshly intriguing about that knowledge is that it has a largely unleveraged lifecycle in the company.

That is, despite hiring practices and process-guided daily operations that drive deployment of an employee's knowledge:
- much of what is initially available for use is not used;
- much of what is then added to it is untracked and unnoticed; and...
- much of where the additions come from is not premeditated as a source.

In fact, this means that we really have little idea as to what the population knows overall, which certainly questions the idea that "most" of the company's knowledge is tacit.

Furthermore, assuming some degree of overlapping (redundant)knowledge, immature knowledge (incomplete), and misinformed knowledge (incorrect), we might wonder how much of the total tacit knowledge is worth keeping and using, and whether in fact the amount that would survive such a vetting is greater than the explicit knowledge collection or not.

We still don't have the magic wand that let's us see the total inventory of tacit knowledge. And let's face it, taking that picture would have to turn into a movie, not a snapshot, akin to filming the waves on the ocean. So how does it make sense to compare the two sets of knowledge?

Obviously, one term of comparison looks at whether the knowledge in question is "effective" knowledge. In order to be effective, the knowledge would have to satisfy some minimum criteria that are probably beyond debate, such as:
- being conceptually relevant to the particular user's task;
- being credible in a way that can be validated; and,
- being obtainable at an expense that does not exceed the value of its usage.

Even those three "tests" pose a significant burden of accountability on a person making the evaluation of effectiveness, since in each case there is potentially huge variety in the characteristics of the situation that qualifies the knowledge. For example, how big is the range of knowledge users when considering the difference in their intellectual proficiencies? What mechanisms can and should be used to validate the qualities of the source of the knowledge? And how is value defined for the application of the knowledge at the time it is applied? While those are issues that have already found numerous important solution approaches, they testify that for the measure of effectiveness, one size solution is unlikely to fit all.

An even more fundamental problem of identifying "effective tacit knowledge" is the problem that the main repository is people -- about whom we can say only one thing for certain: everyone has four conditions related to how they are "knowledgeable", both tacitly and explicitly:

1 - being aware of what you do know;
2 - being aware of what you don't know;
3 - being unaware of what you do know; and,
4 - being unaware of what you don't know.

Right off, we assume that we'd like to go get the knowledge available from conditions #1 and #3. But conditions #2 and #4, which involve missing knowledge (not just tacit) are equally important for knowledge management to address, because the nature of personal involvement in an organization is that we continue to have new experiences that can change us and change what we pay attention to. The related business issue is that so many instances of missing knowledge are tacit instances, escaping notice and therefore having unmeasured impact on processes and decisions.

So overall, the challenge isn't to just circulate things that are not in broad enough circulation yet, but rather to cultivate knowledge availability in a way that promotes both progress and benefits in all four conditions or states of knowledgeability.

What should be happening in each state, to properly manage the potential knowledge utilization of the community?

Without declaring a definitive answer, the following illustration points in the direction of an implementation of knowledge management functions that should be considered.

From left to right: By facilitating 24x7 capability to conduct a relevant action for each state of knowledgeability, processes are fed to evaluate the situation. These processes respond with a function that generates enhanced resourcefulness from the situation by refining the knowledge and directing its flow through key modes of community-wide access featuring references, alerts and coaches. Successful KM will further try to motivate action at the left and market availability at the right.

Posted by Malcolm Ryder at 1:00 PM | Comments (0) | TrackBack

June 16, 2005

KM as a System

Often we define "benefits" quite simply -- as "needs that are to be satisfied". In daily operations, the needs that are perceived to be most challenging often seem so because they require use of assets that, on the occasion, seem to be either hidden or moving targets.

As a critical influencer on the organizational asset we call "knowledge", knowledge management (KM) needs to solve business problems, and it must do so both pragmatically and strategically. In asset management, the most important pragmatic strategy is focused on capacity.

How does capacity management pertain to managing knowledge? We're targeting the robustness of our ability to distribute good ideas effectively against any level of demand. Here, the concern is the marriage of intellectual assets that contain ideas, and digital assets that contain and carry the intellectual assets.

I.

Capacity here needs to be seen in two ways.

- One aspect is about the supply of "knowledge-delivery capability" available on demand. Typically, we want capability to be systematic. So, this looks at all components of what might be considered as, or developed into, the delivery system.

- Another aspect is about the supply of the content being delivered. We're concerned about whether the "right" content is available to deliver, regardless of the probable level of demand.

Consider how wide-ranging the elements might be to help the need . Dramatizing the point, what if an American workgroup needs to bolster a PDF proposal brief with an argument based on the latest concept update or breakthrough, but at that time the latest demonstration of the concept actually exists only in the form of a Shockwave clip in Italian used by the Milan sales office?

II.

Solving such an outrageous problem would be really great, and even circumstantially necessary. It might be a pragmatic motivator for a KM initiative -- but not necessarily sufficient as a basis for enterprise KM. Conducting knowledge-support of a business event such as this one might only be an ad-hoc procedure, a point-solution, or a one-off custom application.

On the other hand, if we look at what accomplishments that support ideally includes, we readily see the catalog of basic benefits from any kind of practical asset management. (Below, simply replace the word "asset" with the word "knowledge"...)

- Avoid unnecessary duplication of asset acquisition costs

- Maximize convenience and effective speed in the search for and discovery of needed assets

- Confidently secure rights to utilization of assets

- Sustain an optimal balance of asset quality vs. asset location

In those cases, we're happy to report that satisfying any one need usually offers a bonus by partially satisfying other needs too...

But to meet any of those needs, it's first necessary to create an infrastructure that supports the efforts for getting those benefits accomplished.

The most important efforts supported by the infrastructure usually sound like "best practices" that need to apply at all organizational departments and locations, and across their functions.

1. Optimize asset storage and retrieval through classification

2. Establish "version control" in the use of similar assets

3. Continuously track asset distribution and asset changes, against type of user and type of usage

4. Proactively manage demand on assets

Overall, these practices sound like a job for a sophisticated system. And they are not the only justification.

III.

The idea that "knowledge is an asset" ckearly makes sense... But this idea deserves some refinement.

For example:
- we can easily appreciate that there is a big difference between data and concepts. The nature of that difference is that concepts are all about "meaning" while data exists happily outside of that.
- Similarly, there is a difference between information (which is a lot like data) and knowledge (which is a lot like concepts).

Now, we're used to the idea that our information systems manipulate our data.

But how about a knowledge system that manipulates our concepts?

The motivation for doing that would not be unusual at all. We attach value to data in the context of the meanings we think the data will help to generate. Attaching value to it is what makes us think of data as an asset. In the same way, we come to think of information as being an asset -- if information supports concepts then it is generating meaning, in the form of knowledge. We attach value to the information, and so we think of the information as an asset.

Treating things as assets is a real sign that we care about them! We tend to build systems to be sure we will take care of them effectively.

Primarily, the reason why we think concepts are important is because they help us get things done, which is a subtle but critical observation. When we say what concepts "mean" to us, we're normally talking about their usefulness, not their intrinsic enlightening qualities. Likewise, the context that makes knowledge valuable, and that makes it an "asset" to manage, is its application.

This emphasizes the need to make knowledge "available for application", which zeros in on the set of practical issues that a KM infrastructure and system must address.

If we have a "knowledge system" to manipulate our concepts, the key manipulations are those very same moves -- i.e, best practices -- that support satisfaction of the needs we initially listed above.

IV.

To enable those manipulations, concepts will have to be "captured" and packaged in portable form. In looking (as we do below) at the range of techniques that meet this requirement, it quickly becomes apparent why so many different kinds of tools are brought to the KM effort.

Meanwhile, it's most important to see this packaging from the "knowledge consumer's" point of view. We refer to the package delivery and acceptance together as "transfer of knowledge" -- which precedes the consumer's application (use) of the knowledge.

In knowledge-transfer, there are three success factors: concepts must be (a.) deliverable; (b.) understandable; and (c.) relevant. Without these factors, the knowledge transfer effort risks simply becoming information exposure.

1. Concept delivery:
- Conversation packages concepts and transports them from one person to another. Memory makes conversation repeatable. Requirement: the ability to engage anyone who remembers the conversation or who originated the concept.

- Documentation provides a "proxy" for engaging the concept originator or other concept holders. Not being interactive, documentation has to be tailored in advance to the presumed interpretive abilities of the recipient. Requirement: the ability to use a medium (language, format, etc.) that offers fidelity to the description of the concept. [Two sidebars here. One, just because something is animated doesn't mean it is interactive. Two, form should follow function, but the medium can definitely hide the message; I own one of the only remaining copies of the Excel Users Manual in Polish: fascinating as a curiosity and, since I never learned Polish, absolutely meaningless to me as instruction.]

2. Concept recognition:
- Categorization allows one concept to be identified in more than one way, and it also allows multiple concepts to be identified in one way. This keeps differences amongst types of users (and their differing points of view)from preventing identification of the potential usefulness of the concept. Requirement: the ability to cross-reference concepts with types of usages.

- Translation allows different types of users to grasp the same concept through different means. Requirement: ability to generate, maintain and identify multiple versions of the same designated concept.

3. Concept incorporation:
- Comparison takes into account the fact that the awareness of how to use a concept may be a sudden and/or unprecedented event, because the usage situation may not have called on the concept before. Although we usually have a good idea of how often previous problems have been addressed with previous concepts, it is relatively mysterious as to when and where a genuinely new problem will occur, demanding research. Here the immediate point is to make the research easy. Requirement: ability to test or certify the relative quality of a concept for the purpose -- including testing concepts against other concepts.

- Protocol governs the communications behavior between two parties, factoring in the known or suspected impacts of certain modes of (as we usually call it) information transfer and knowledge transfer. Requirement: ability to manage users' access rights to concepts by profiling users.

As we step through those three success factors, looking for the combination of concept availability and concept usability, we can imagine everything ranging from teleconferencing and IM, to voicemail/email and blogs/portals, to taxonomic systems and concept matching and XML, to content management and artificial intelligence and business rules. Along with myriad other tools and approaches, these help to construct an infrastructure for KM. Integration of these into a knowledge system is part art, part science and likely to be an ongoing evolutionary effort.

Then, in executing processes that manage knowledge as an asset, the general conversion of ideas into "reusable content" becomes a routine expectation of the population of knowledge-users.

V.

With that expectation in place, management has a couple of even bigger fish to fry.

One, when users see other users as the knowledge provider, there are many issues, particularly of protocol, that social relationships have resolved but that are largely undetermined and unresolved between users who don't know each other. KM requires intervention on a level of cultural norms, changing norms to accomodate successful interactions explicitly independent of social relationships yet compatible with them. Unlike in academia, most companies have not readily organized their protocol around knowledge-peer networks that rival the authority of the org chart...

Two, if the idea of usefulness is not being managed, then the idea of managing knowledge availability loses a lot of its value. The single most hospitable environment for KM is an environment in which the population's common awareness of the organization's strategy is very high, driving the perceptions of resource usefulness. Strategy Management should be assessed as one of the very first steps in planning the development of a Knowledge Management practice in the organization.

Posted by Malcolm Ryder at 7:06 AM | Comments (0)

May 15, 2005

What is "what you know" worth?

It's not what you know that counts; it's how you know it.
Ask any psychic.

I. So, you wanna be a knowledge manager.

What are you, psychic or something?

Ordinarily, you can go down the KM path armed with this:

Data+context = info
info+usage = knowledge
knowledge+history = wisdom

You'd think this would be a good place to have your employees wind up, but that's not what they care about.
Their issue is that they have to go from observing to thinking to deciding to expecting. The path they want you to pave is like this:

Reconnaissance --> Information
Information --> Analysis
Analysis --> Patterns

We're accustomed to leaning on our "information systems" to carry out the reconnaissance and analysis, but do our info systems make us smarter? Only if they interpret the patterns, too. We feel "smarter" when, based on what the patterns mean, we know what to expect.

Why the emphasis on expectation?

Because in business there are two main types of "smarts", both future-oriented -- the kind that reduces risk, and the kind that leads to innovation. By solving problems, and by surprising customers and competitors, the business goes forward and gets ahead. That's where the rewards kick in.

So what do patterns have to do with these benefits?

With the speed of information processing now available, the main problem for a business is not to get enough information on time, but instead to get "the right" information. For the most part, the problem lies in not knowing which information is relevant or "best", and that confusion makes both finding and choosing the right information equally daunting. Result: complexity in the thought process overwhelms confidence in decision-making.

But a pattern exhibits a path that navigates through complexity. This is the kind of knowledge that rates highest, the kind that the business wants.

And who are considered the smart guys in your company? The ones who can either make a path or see one, where others can't or don't.

But how do they do it? More importantly, how do you do it for your folks?

II. Teach a man to fish...

Typically, "business intelligence" comes in with the responsibility of generating patterns from the complexity. This sets the stage for what the business is really after, which is to use the patterns to make decisions.

Thus seeing the affair as having two steps, we can look at what essential challenges the knowledge manager will need to overcome.

The first step, "intelligence", is critically dependent on information discovery. We realize that the diversity of the company's employee and customer population means that there is a lot of information distributed in ways and places that are tended mainly by those people. To aggregate the distributed information, we need them each to contribute what they have. Usually called collaboration, a voluntary aggregation creates a body of information that must be formatted for usability-on-demand. Making contributions voluntary is a tough prerequisite worth solving only if their usability is also known to be within reach. Altogether, this is the heavy lifting that changes the way most people can get things done. Even exceptionally gifted "knowledge workers" or experts like Infoworld's Jon Udell rely mainly on this capability enhancement.

The second step, "interpretation" of patterns developed from business intelligence, is about what people will decide to do. It has most often gone by names that we (except for marketers) don't attach to information systems, names like "wisdom", "insight", and "intuition"... Too often hopelessly confused with each other, they seem unmanageable or evangelically mystical.

Fortunately, each mode of interpretation can be seen generating a distinctive kind of "findings" which have practical value in support of decision-making. But these kinds of findings are something that we need to get our hands on -- and then record, repeat, compare, associate, and so on -- from less than supernatural sources. People, histories and systems can all variously help, but the full value comes from covering all the interpretative modes:

Wisdom --> Probabilities (operations)
Insight --> Implications (tactics)
Intuition --> Foresight (strategy)

III. The Payoff...

This consistently future-oriented perspective on the value of knowledge is naturally where KM needs to bank, strategically empowering risk management and innovation on demand.

Ultimately, what the business wants from knowledge is explanations for "what kind of risk did we decide to take?" and "how is this going to give us a new advantage?" Bottom line: "What makes you think that?"

Managers should have a bird's eye view of the plan for keeping those explanations coming.

- A certain amount of excitement comes with realizing that a description consisting of foresight followed by implications and then probabilities yields... a business case!

- And, accompanying the aggregation that initially supports decision making, critical review finishes off the job.

- Under the umbrella presumption of their "experience", we should look to other people for both the content to aggregate and for the terms of a critique. The manager's challenge is to determine when and how.

In the end, cleared of hype, the business point of actually managing knowledge is to get beyond knowledge per se, and into an accountability of expectations.

It's also clear that management should set expectations of KM's deliverables accordingly.

Posted by Malcolm Ryder at 10:04 PM | Comments (0) | TrackBack