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.

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.

I'm sure that creators of ads would be amused (NOT!) to find out from media professor and consultant Jeff Jarvis that ads are not "content" !

Jarvis's stance, as reported by Stefan Deeran of BNET in the article Who Benefits from the "Link Economy", is summed up as this problem:

"In general, the consensus is that producers of original content that want to put their work behind a paywall or demand payment from linkers, just don’t get the fluidity of web."

The proof of this, they say, is that linkers prosper without paying non-ad content providers; instead, linkers get to charge the ad providers, while non-ad content providers don't get to do that.. Thus the Jarvis claim that we are shifting from a "content economy" to a "links economy".

But obviously, ads are content, and meanwhile, how many linkers actually turn a profit?

So to remain clear, the shift is about what kind of content has the most "economic" value as currency, not as net income that supports a continuation of the cash flows for non-ad content providers or linkers.

Non-ad content, now highly commoditized by the web, is most similar to currency that has suffered inflation beyond any important redemption. The "face value" has stopped being significant.

But while technology has made ad content easier to distribute, and thus magnified its face value, there is no rational proof that people suddenly prefer ads to non-ads. Instead, there is proof that ad-content providers are willing to work harder to deal with the problem of someone's "preference" than are most people willing to work on it for themselves.

As soon as non-ad content providers get people used to paid subscriptions again, the "economy" will rebalance in favor of branding, editorialism and other things that people want with non-ad content to conform to their preference.

 "Non-ad Content" providers must solve the Cost-of-Preference problem. This is already being trial-and-errored with concepts like "MyContent", "Premium Content", "Actionable Content", and so on -- and most of these approaches are long past being "new". 

But if paid "links" are simply today's version of booth rentals at a trade show, it's not the content that dissuades people from buying; rather, it's that the trade show is huge and unmanaged, so people are fatigued by it very quickly.

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.

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.

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.

This is a somewhat romantic notion, best held by facebook's marketing and legal teams but not a plausible or fact-based reality. The concern wouldn't be how social networks behave; rather, it would be how social behaviors are networked.

Interestingly, it brings up the question of how much a given tool can control its users, versus how much design can flex to assure that the tool is fit to its purpose. What's not clear is that there is any cultural "end state" of facebook that represents its purpose. Instead, both on the surface and in theory, facebook is one of multiple grand collaborative experiments to discover what social "connectivity" really includes, with social propriety being a necessary but secondary concern. This experimentation seems likely to show ongoing morphing in what we see being social networking, but it hardly seems likely that a horde of unemployed invaders at one site will change social networking into something it is not already.

The dominant feature of the most popular social networking tools is that they are gateways to fundamentally public environments where privacy policy controls get applied. But the trick is that the policy applications are done based on personal preferences, and the personal preferences reflect many different cultures. It is unlikely that any one culture actually governs a social network unless the network's environment is administered according to some dominant policy model that proxies a culture. The default condition is that public spaces (like facebook) are polycultural, and that the less polycultural the space is made, the more constitutionally private it becomes -- just like a club. Punchline: unless internet economics eliminate the chance for more new "price"-free gateways, it is not social networking that will change, but instead the variety of social network venues.

There is some counter-thought to this that insists on some "critical mass" of members for a social network to be seen as useful -- and therefore in some Darwinian way likely to survive. This presupposes that the "natural" limit on the number of networks is a small number, since most networks won't offer enough richness to be worth the troulble. But I think this oversimplifies things by assuming (arbitrarily) that the "richness" (value) of a member of the network must be measured by the interconnections within that network. Real life shows that assumption to be silly; incredibly valuable people join and use networks on a very limited basis all the time; and, some small networks can be incredibly powerful, like the smoke filled back rooms of old. We'll remember that these smaller ones tend to be more private.

Rather, some members who are not "rich" when they join public networks have the ambition that they can achieve some richness within the network. That is precisely the current sex appeal of the term "networking", as used for painting in broad strokes; well, fine, as long as we don't pretend that social networking is actually hostage to any network.

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.

Listing signature characteristics of "importance", the panel came up with this:

-Impact quality of life
-fulfill a compelling need
-solve a problem
-exhibit a "wow" factor
-change the way business is conducted
-increase efficiency
-spark new innovations
-create a new industry

Like many lists, this is a collection of "notables" that leaves open the matter of which ones may overlap or compete with each other. That might not matter except that the list is one of competitive "qualifiers" or "criteria", so we need to know when to apply them, and when not. It doesn't make sense that all of them would apply to every issue thought of as an innovation, so it's fair to imagine that some kind of categorization is implicit in the list. To investigate that, let's reorganize the list a bit.

1a. Impact quality of life
1b. create a new industry
1c. change the way business is conducted

2a. fulfill a compelling need
2b. solve a problem

3a. spark new innovations
3b. exhibit a "wow" factor

4. increase efficiency

Group 1 clearly shows what we want innovation to affect. Life, industry and business are of course strongly interconnected because they co-exist in a shared environment, and they co-operate in the creation of that environment.

Group 2 clearly shows "how" we want the innovation to affect any of the members of Group 1.

Group 3 clearly, but somewhat abstractly, represents a sense of "why" -- of whether the innovation is compelling due to the "push" of its character (sparking) or the "pull" of its character. (And these would not necessarily exclude each other.)

And Group 4 is a throwaway. The mystical attracton of "efficiency" might be nicely appreciated as a need to avoid waste or resistance; but at best this is a type of micro-problem to be solved, and at best it should be a member of a list of various things dealt with by group member 2b. Additionally, the different members of Group 1 probably have some micro-problems in common, but (for example) surely the idea of inefficiency versus "quality of life" is not the same as inefficiency versus "new industry". So going ahead, we'll drop it (at least until the other worthy micro-problems, from various perspectives, are also identified).

What the new grouping offers is three dimensions of consideration -- the what, how, and why -- that ought to account for the competitive inclusion of each given innovation in the Top 30 list. 3-D space is of course a framework, and with a framework in hand it should also be possible to anticipate (predict), find (detect), and position other issues that would be candidates or actuals of "innovation"...

We don't know exactly how much the panel may have made decisions this way -- whether explicitly by agreed formula, or intuitively. But for the panel, there was also the prior matter of defining an "innovation" in the first place. Their definition was as follows: "It's something new that creates new opportunities for growth and development", which resulted in "a list dominated by technological and medical advancements".

Let's go back to that loose end of "inefficiency", though. With this panel, it seems either clear or feared that inefficiency is a major thorn in the side -- perhaps the single most aggravating barrier to innovation itself? This would be an indicator that innovation is perceived almost entirely in the context of an already known or targeted outcome, objective or goal. What else could the context be?

For one, conspicuously absent from the list is both (a.) specific unprecedented "concepts" and (b.) virtually all "fine art". In other words, nothing having to do with the evolution or revolution of consciousness made the top 30 list. Granted, the initial invitation to compile the list most likely did not try to attract a range of candidates that included those two. However, aside from entertainment value, what is the point or use of a Top 30 list? There will be those who study the list in order to try to understand where innovation comes from. And for that very reason, it is critical to survey as well the growth and development of the mind that we will eventually watch, hire, or follow because we expect innovation from it. It was Einstein, wasn't it, who said that "To raise new questions, new possibilities, to regard old problems from a new angle requires creative imagination and marks real advances in science... The significant problems we face cannot be solved at the same level of thinking we were at when we created them." The most important innovation(s) would be ones that allow, or even force, us to think in a different way than we did before.

And another take on context involves the ability to undertand growth and development not as checkpoints towards a known or certain end, but instead as evidence of new potential and/or capability despite being accompanied by uncertainty. Normally we reserve the term "innovation" for something that we can retrospectively view; but the difference here is that the desired certainty need not be about what comes "next" due to the innovation. Instead, it can be about "what became different" from a past known or shown to be obsolete. In this sense, a surprise encounter with something that already exists, but that is a clear alternative that might then be adopted, makes the adoption itself an innovation, and should be understood alongside our interest in inventions.

Managing change usually means more than applying controls to some different way of doing things. And doing things differently nearly always first means being different from before. It follows that when attempting to get people to "do" different, they will entertain the notion from a point of view that initially reflects how they already "are".

We can describe the points-of-view in four general ways, which derive from the interaction of factors illustrated below. In most cases, for the person being asked, the idea of changing will be "familiar" or not -- and this degree of familiarity is a gating factor in what happens next. Familiarity is based on both recognizing and understanding the idea, so that it is "mentally owned" by the decision-maker. It directs their decision-making along one of four paths of agreement, each of which processes what psychologically appears to have been presented to the decision-maker.

In the four key scenarios, the decision-maker reacts to a suggested change in different ways. Meanwhile, there is no guarantee that, at the end of the path, acceptance will be reached. The change-presenter must determine which paths need to be navigated, and what sequence is called for. With that, the suggested change that is input to their decisioning may finally be output as an agreement.

- The idea of change that is being presented may in effect test the decision-maker's current level of acceptance. This is mostly like marketing for the purpose of highlighting a match between what both parties prefer. Messaging would be important here.

- More challenging than that, for the decision-maker, is being caught by surprise when the suggested change provokes some new or latent realization (discovery) that must be considered. Education would be important here.

- The third possibility is that an already acknowledged option is presented with higher priority, based on the attractiveness of its expected impacts. For the most part, selling is useful here, insofar as it emphasizes and offers the new availability of favorable future positions for the decision-maker.

- If the suggested change is not conceptually new to the decision-maker, but has not previously been acknowledged as an option, then the situation is most likely to initially be about considering trade-offs between the proposition and any personal alternatives believed to exist. Analysis would be important here.

Described more tersely, the factors that "gate" a decision include identity, knowledge, future value, and opportunity cost. Taking those factors as elements of a campaign, and orchestrating them to work with each other, the change-presenter can strategically and proactively design the presentation to the necessary audiences.

The key sub-topic here is about vendors of BI and Analytics allegedly and programmatically prioritizing subjective instinct over objective calculation [my summary labels].

If that characterization of the choices is a left-vs-right choice (x-axis), I find it distracting and not as useful as a top-vs-bottom (y-axis) difference.

Namely, it seems almost always more useful to approach analytics as a way to take things apart, and BI as a way to put things back together. For example, it might really take only 4 (not 4000) data points to spot a trend, etc., but the magic would be in picking the correct four data points first. So wouldn't we expect "analytics" to help us pick the right four, and "BI" to tell us about their effects and co-effects? Do we need an industrial do-over to get tools orientated this way?

This relative difference is far more interesting than the difference between the brain and the gut, since in this view you get to use both organs on both the take-apart and put-together efforts.

Moreover, if the issue is really about "how managers decide what actions to take", then let's consider this real-world observation: actionable decisions and decisive action are not the same thing; the politics of the manager's position in the organization will sway things one way or the other.

Generally, the first decision made is about which evident problems the manager prefers to solve, whereas the first action taken is generally based on opportunity cost.

Those bases change from person to person and from time to time, but nearly all organizations try to implement some kind of policy or other standard(s) to bring about consistency in what is acceptable as "preference" and "cost".

The point is that the tension is not between the head and the gut; rather, it is between responsibility and accountability, each as practiced under the prevailing terms of risk and reward at the management venue.

Off-the-cuff example: a fictitious merger of Neilsen, Harris (polls), and Yahoo would go to market providing interactive services to web users that, within legal constraints, could acquire enough feedback and observation to discover hugely rich profiles of users and groups and offer the profiles in B2B transactions and public service sectors.

Overview: online capabilities in search, collaboration and invention follow each other in a cycle driving the evolution of the "Web" from earlier levels of maturity to later greater levels. This diagram illustrates the interrelated dynamics.

Each of the capabilities continues to increase in functional sophistication and reliability over time. For each respective capability, this change broadens its range of usefulness, which increases the range of user-roles that may adopt it -- as in, adapt tasks to include it in the task. While each of the different basic roles -- Producer, Provider, and Receiver -- will take advantage of enhancements, the roles respectively tend to drive particular rates and types of enhancement of some capabilities more than others. This relative difference is represented by their positioning in the diagram.

Interaction of the roles is selective but continual, as all are active all the time. It is important to accept that much of the "selective" interaction is speculative; however, any person in the role may program the interactions in various ways, such as to cultivate a particular scope of interconnectivity:

- one-to-one

- one-to-many

- many-to-many

- many-to-one

... or perhaps to fulfill responsibilities or special interests that reflect the following dynamics:

- Cultural: especially involving attraction and development; driving and/or driven by identity; strong focus on designing

- Community: esp. involving development and distribution; driving and/or driven by policy; strong focus on building

- Market: esp. involving distribution and attraction; driving and/or driven by economy; strong focus on exchanging

Those three fundamental "interest groups" are not simply points-of-entry into the web; instead, they are dominant perspectives within which web interactions and facilities are discovered, recognized, weighed, formulated, and so forth, by web users. As seen in the diagram, web interaction amongst roles facilitates a point of view and goal (design, build, exchange) that is characteristic of each perspective and has a high priority in the group view of potential web operations. As the web interaction becomes more and more enhanced and reliable, the web as a whole is perceived to evolve to a next generation for the benefitting users (or stakeholders).

The table below gives a closer look at the underlying architecture of an existing facility in use on the web, in generic terms of role and task. As discussed in the companion article Notes 1.0 about Web 3.0, the notion of "web content" is a high-level abstraction signifying what the web user supplies to the web and/or accesses the web to use. The related architecture accounts for what exists on the web as components of content, which may be intermixed, coordinated or integrated across roles to generate a more complex web facility.

The terms in the table below generically label what each role is looking for on the web and why -- with the background assumption that these items are engineered and reengineered over time to fit the particular "type" of player (e.g., student, artist, businessperson, scientist, etc.) within the role. As an example, the end-to-end architecture of acquiring an email, or purchasing an item from Amazon, or manipulating an avatar in Second Life can all be described in terms of the production, provision and reception activity involved, per the different parties that see to the main roles being satisfied. So, for example, while web content such as "stock", "factory" and "platform" is specialized to the involved Producer, the combinations of web content across the Producer, Provider and Receiver ultimately makes up the facility that the receiver may call email, Amazon, or Second Life.

To reiterate a key thought from the earlier Notes 1.0 article, the most interesting thing about the "web", after all, is that the interconnectivity and maturation allows a given participant to play multiple roles -- either concurrently or differing from time to time. The significance of discussing "generations" in web evolution is mainly in the degree to which a generation indicates reliable and adequate support of the user's intended activity. This will derive mainly from the enhancement and maturity of the web content in the web architecture.

In fact, demonstrating the disregard, I've generally completely avoided any semblance of writing anything about it to anyone but an invitational or hypothetical audience. Nonetheless, the popularity of the subject leads one to things said by others that warrant being remembered and shared. In which case, there is an ethical responsibility to give credit where credit is due.

Example: by Googling the phrase "Web 3.0", find a path to Sramana Mitra and more than a year of comments about her Web 3.0 "framework". For latecomers like myself, Mitra seems to already have "celebrity status" -- albeit earned. I mention that only to point out that except for the internet's easy way of cultivating coincidences, I may have never heard of her (as I'm sure she has not heard of me). I think that very fact is one of the main and most simply profound points of having the internet at our disposal -- which is to say that it reflects more about the internet than it does about Mitra, a point about which I hope she would share my appreciation. And it should fit into her greater scope of thinking about the web.

Suffice it to say that her framework for defining Web 3.0, offered as a catchy formula (Web 3.0 = 4C + P + VS... see for yourself), provoked me to say what I have said on her website's comments and again said below. I do not agree with her definition of web 3.0, but what I'll say below is a part of a different framework that can contain the points covered by Mitra's framework or formula.

Web 1.0, 2.0 or 3.0 have different definitions depending on what kind of stakeholder is given top priority amongst the many different kinds.

Let's overgeneralize and start by pointing out that the difference between having the web and not having it is simply that the web (the "internet") is another place a person can go to do something.

The biggest difference in stakeholders is between Producers, Providers and Receivers.
All three types are consumers, but they go to the internet to consume very different classes of "content"...

• Content is simply the material that the receiver needs, that they don't already have, in order to execute individual tasks to a conclusion.
• A task can be anything from self-entertainment to industrial development.
• In every case, the task is executed to conclusion, with the content, within the "workspace" of the web, without leaving the web.

However, a better instrument for understanding the evolutionary dynamics would not restrict itself to debatable examples, but instead would explain why examples fit where they do. This calls for the abstraction of a model.

In web 1.0, the recipient acquired prefabricated content in a closed package.
- Search created a transitional opportunity to web 2.0 by encouraging choice of packages.

In web 2.0, the recipient acquired prefabricated content in a modifiable package.
- Collaboration and personalization created a transitional opportunity to web 3.0 by encouraging comparative and cooperative content sourcing.

In web 3.0, the recipient acquires modifiable content in a modifiable package.
- Lacking any better term so far, invention strikes me as the transitional opportunity to web 4.0, as ontologies and cultures begin to take over a greater percentage of activities *such as* the creation and materialization of new products, outside of (but in addition to) conventional corporate instruments and academia.

What then distinguishes one web "generation" from another is the notion that an adequate level of reliability in the given generation's degree of task support can be taken for granted by most stakeholders.

And what these definitions mean, in reality, is that at any given time, some stakeholders doing some things have already been at a different generational level than others doing other things. Meanwhile, over time, the technologies and practices that emerge and mature in a generation of the internet environment also "level the playing field" across different stakeholders.

This ongoing leveling (or maturing) allows any individual participant to go to the web for more and more of the various things that constitute the individual's range of interests. As a result, the participant inhabits the internet environment more and more.

Turn off the internet, and they go somewhere else to do all of the same things, with a lot less affordable speed and range at their disposal.

All that said, it makes less sense to talk about web 1.0, 2.0, etc. than it does to talk about the relative maturity level of the internet environment as a resource (e.g. support levels 1, 2, 3, etc.).

The most interesting implications I find are these two:
- stakeholders will remain distinguishable as types, but an individual participant will occupy multiple stakeholder roles simultaneously;
- and the individual can readily change, thanks to the maturing web, from being a recipient to a provider, or from a provider to a producer. And so on.

Control of operations, by definition, means controlling the range of effects produced by driving a collection of interactions. The usual approach to tracking degrees of control is to put gauges on each one of the smallest number of critical states (conditions) produced within operations -- and to use real-time gauges as continuously as possible. The correlation of the information from the various gauges tells whether overall operations are proceeding within an acceptable range of behaviors.

The collection of gauges is readily recognized as a dashboard. But the correlation of them is where the actual control begins. The diagram above shows the Archestra model for this correlation.

The model shows how to avoid non-sense metrics and focus on essential observations and connections. For example, there is a shared boundary between Priority and Plan, where the sharing indicates the need for an instrument that coordinates the priority and the plan. The instrument is Policy. Meanwhile, the primary rational coordinator of  Priority and Quality is a Standard. And for example, the primary rational coordinator of Accounting and Reporting is Rules.

Each part of the model is a part that has an independent definition and can be independently produced, implemented, tracked and changed. In putting all the parts to use, procurement and architecture and engineering are required to assure that they can interact in an appropriate way; while management controls assure that they probably will interact appropriately.

The explanation so far leaves two areas for further clarification.

First, the model shows four "parts" that are more like regions: Priority, Plan, Activity, and Quality. Many people may detect some similarity in this quadruplet to earlier models such as the "Deming cycle", so it is important to note that the terms in the Archestra model do not attempt to share the Deming vocabulary or any other. In the Archestra model here, 

- Priority refers to identifying and grading preferences, which logically precedes the other three terms as a management or "controls" concern.

- Plan is seen as step two, by which priorities are organized to be actionable with presumed resources.

- Activity then logically follows the plans.

- And Quality -- although it is always a target and likely referenced in both prioritizing and planning -- is not actually in the sequence until Activity has caused some output or outcome that must be held against the need for quality.  In a control model, the place of this last step is important because quality must practically pertain to all actuals, not hypothetically pertain to all possibles. In fact, a major intent of building controls to this model would  be to achieve streamlining and transparency of observations about each part, so that as little time as possible is required to get awareness of whether priorities and quality are aligned. Misalignment is dealt with by corrections.

Second, let's take one of the four main items just discussed, for example Quality: the model shows that two of its shared boundaries are Standard and Process. But what about the other two apparent boundaries -- Practices and Goals? Frankly, this may be a flaw in the visual representation offered. However, the intent here is not that the Practices and Goals arrows connecting Monitoring, Modeling and Accounting are boundaries. Instead, using Quality again as the example, Modeling is the primary referent for Quality, and if Modeling is to be able to succeed as the referent for Quality, then Modeling must be logically complemented by the definitions of Monitoring and Accounting. Likewise, Reporting (aligned with defined Rules and defined Events) is the primary referent for Plans. And so on.

Customarily, Archestra models offer "maps" to use for identifying defects, discontinuities, or other problems that exist in an already active environment. The model is an abstraction and can be taken prescriptively, but it does not assume that the actual environment is already organized as illustrated. The argument of the model is that its illustrated organization can comparatively expose an important disorganization in an existing actual environment, and help to promote the source of the disorganization to a high level of corrective attention.