All Life Is Problem Solving

The KM 2.0 meme first appeared on October 5, 2005. Euan Semple (who may have originated the term) seemed to equate it with:

“ . . . people, connected people, empowered people, people who don’t always do what you expect or what you tell them but invariably end up taking you to exciting places you that would never have expected to get to.

And not only that, but you can do this using tools that cost peanuts!”

So, KM 2.0 is about people using inexpensive Web 2.0 tools to get connected and empowered. Specifying a bit, we might infer that this refers to a type of KM which intends to enable self-organization by introducing appropriate Web 2.0 tools into the enterprise. Jack Vinson quickly picked up on Semple’s meme and on October 8th, added this thought in his own blog:

“Anything that gets you to look at something in a new light is good. Euan is suggesting that maybe a parallel change in the view of KM from command-and-control, “I know what’s right for you,” to more distributed and a sense that “we know what is right for each other.” “

Thus, he explicitly introduced the view (which Euan Semple had merely implied) that KM had previously been focused on command-and-control approaches, while KM 2.0 was focused on self-organization and community.

Thereafter, further discussion of KM 2.0 proceeded slowly during 2005, but began to accelerate in 2006, as IBM and others became aware of the meme. By the late spring of 2008, discussions about KM 2.0 had raised a number of questions associated with issues which have proved enduring including:

1. Before the introduction of Web/Enterprise 2.0 tools, was KM characterized by a primarily command-and-control oriented approach, so that KM 2.0, defined as the introduction of such tools, introduces a discontinuous, entirely new version of KM producing enhanced distributed social interaction, collaboration, communication, content creation, self-organization and community?

2. Are KM 2.0 social software/social media tools used in the service of creating an ecology that improves connectivity, resulting in building relationships and trust, better communications and knowledge sharing, and, is the ecology itself, rather than management activity, KM 2.0?

3. Is KM 2.0 the implementation and use of new social software and/or social media tools in an enterprise? That is, is KM 2.0 either equivalent to Enterprise 2.0, or just a subset of it?

4. Or is KM a more broadly social activity or set of processes that simply uses the new 2.0 tools as an instrument, along with any other old and new tools it has occasion to use in enhancing knowledge processing so that in reality, there is no such thing as a discontinuous and distinct KM 2.0?

5. Is KM 2.0 just a name for that aspect of KM which utilizes Web/Enterprise 2.0 tools to enable greater connectivity and self organization in one’s enterprise?

6. Is KM dying and is there no KM 2.0 because 2.0 cluster tools, more generally, are removing the need for formal KM?

Since these questions deal with both the definition of KM 2.0 and its relationship to KM, I’ll give my answers to them in my next post.

“America. In the face of our common dangers, in this winter of our hardship . . . . With hope and virtue, let us brave once more the icy currents, and endure what storms may come. Let it be said by our children’s children that when we were tested we refused to let this journey end, that we did not turn back nor did we falter; and with eyes fixed on the horizon and God’s grace upon us, we carried forth that great gift of freedom and delivered it safely to future generations.” (Barack Obama, January 20, 2009)

The moment was certainly moving, and I found the tears, unbidden, coming. But before too long, and in the midst of the celebration, and the eloquence, and the feeling of renewal, I could not but think about how he would lead us to fix our broken Government and Political System – a system that has allowed so many problems in so many areas of society and economy to accumulate and fester, that has allowed the Dreams of so many Americans to be ignored, that has stood by while the protections of Civil Liberties have been eroded, and while Americans have tortured others in the name of National Security. The magnitude of his and our task rivals that of the great tasks of the Revolutionary, Civil War, and Depression/World War II generations. And while I do not doubt that Americans will undertake these with the same courage and commitment as other generations, I couldn’t help but wonder whether they will be undertaken in a way that will grow both our knowledge and our problem solving capability throughout the long process of adaptation that faces us.

The title of this blog is “All Life Is Problem Solving,” and this applies no less to Societies and Governments than it does to individuals and other human collectives. All living things have ways of solving problems, and we humans and our collectives have ways of improving our innate and culturally transmitted ways of problem solving. The core of these is to improve our ability to see problems, arrive at creative alternative solutions, eliminate the alternatives that don’t both work well and increase our understanding, and communicate our surviving ideas to our fellows. Does the Obama Administration know how to simultaneously solve problems and grow our individual and collective intelligence? Will it develop such an understanding? Will it look back to the pragmatic method of American problem solving, originated in the great Roosevelt Administration that has come, in a notable irony of history, to be called “Kaizen,” and that has been mastered most successfully by Toyota, but not by any Government in its entirety? Or will it decide that it already knows the solutions to our problems and that all that’s needed is vigorous implementation, aided perhaps by the latest in Information Technology?

I hope it’s not just the last. Don’t get me wrong. I hope there are solutions and also vigorous implementation, but I hope there’s also continuous evaluation of the consequences of our actions, and quick re-inventions when things aren’t working. And I hope, above all, we realize that we need to create a new generation of problem solvers who understand that growing and transmitting how we solve our problems is as important a job as solving any specific problem or crisis of the moment. For, if we are to safely deliver that great gift of Freedom to future generations, we have to learn, once again, to eliminate “solutions” to our problems that do not preserve that gift, and accept only those that do.

Today, I’ll continue with definitions I need to clarify relationships among the members what I’ve been calling the “2.0 cluster.”

Social Media

The least clearly formulated idea in the “2.0 cluster” is “social media.” While the proliferation of definitions and conceptions surrounding this term is not yet as fulsome as with KM itself, the ambiguity surrounding this meme is already appreciable and might well approach KM before its popularity begins to decline. A recent, but still very incomplete cataloging of definitions of social media by Benedikt Koehler numbered 23 distinct definitions. These range from virtual synonyms of social software, to those that make no reference to software at all.

In its modern context “social media” is associated with tools that support social interaction and provide (to quote a definition offered by Brian Solis) “for the democratization of information, transforming people from content readers into publishers. It is the shift from a broadcast mechanism to a many-to-many model, rooted in conversations between authors, people, and peers.” Part of this definition associates social media with the use of social software including Web 2.0 software to generate media content and intense social interactions. Later on, I’ll use this definition for my discussion, while making no claims that it’s even close to representing a consensus among social media practitioners, since no such consensus exists.

Enterprise 2.0

The person most closely associated with the Enterprise 2.0 meme is Andrew McAfee. He offered the earliest definition in May 2006, and then followed with a second definition which has been widely discussed since he presented it at the end of May 2006. It is: “Enterprise 2.0 is the use of emergent social software platforms within companies, or between companies and their partners or customers.” By “platforms,” McAfee means “. . . digital environments in which contributions and interactions are globally visible and persistent over time.” By emergent he means: “the software is freeform, and that it contains mechanisms to let the patterns and structure inherent in people’s interactions become visible over time.” Finally, by “freeform” he means software whose use is “optional,” which is “free of upfront workflow,” which is “egalitarian, or indifferent to formal organizational identities,” and which is “accepting of many types of data.”

There are alternative definitions of Enterprise 2.0 out there, but McAfee’s definition has clarity and specificity to recommend it, and he resists strongly attempts to broaden its scope “to something like “all the interesting things that are happening in the enterprise software market.” This is a very good thing for anyone wishing to analyze the relationships of Enterprise 2.0 to other members of the “2.0 cluster” and to KM, because it minimizes any difficulty in distinguishing the E2.0 from other categories due to conceptual overlap.

While the variations on the various 2.0 cluster memes are also beginning to proliferate as more people write about them, it is, except in the case of “social media,” comparatively easy to put one’s fingers on dominant definitions of these categories, because early and continuing work on each of them is more closely associated with a thinker of high prestige who has offered a preferred definition of each of the categories, than is the case for “Knowledge Management.”

Web 2.0

“Web 2.0” thinking is most closely associated with Tim O’Reilly, President and CEO of O’Reilly Media, Inc. In his latest effort at a definition of Web 2.0 he offers:

“Web 2.0 is the business revolution in the computer industry caused by the move to the internet as platform, and an attempt to understand the rules for success on that new platform. Chief among those rules is this: Build applications that harness network effects to get better the more people use them. (This is what I’ve elsewhere called “harnessing collective intelligence.”)”

This definition defines Web 2.0 as a movement, but also implies a short definition of what Web 2.0 tools are. They’re internet software “applications that harness network effects to get better the more people use them.” One key idea here is that such applications view the Internet as the platform for both development and use, in contrast to Web 1.0 applications which used the Internet, but ultimately saw the PC as the platform of reference. Examples of Web 2.0 applications are by now well-known. They include applications such as Blogs, RSS Feeds, Wikis, Social Bookmarking, Social Networking, Polling/Voting, Collaborative Tagging, Interactive Media, Folksonomies, “Mashups” of various kinds, and other applications too numerous to mention.

There are problems with O’Reilly’s definition of Web 2.0, which I won’t cover here, but I do need to note that it is inclusive enough that it might well include the coming generation of Web 3.0 tools, whose distinguishing characteristic is that they are based on the “Semantic Web.” It is very likely that Web 3.0 applications will be just as oriented toward utilizing network effects and collective intelligence as Web 2.0 applications are, so, O’Reilly’s definition won’t distinguish the two. But such a distinction is important in justifying the name Web 2.0 in the first place, since, without it, why use numerical software “version-like” terminology to describe such changes at all? Why not, instead, just refer to the social web, to the semantic social web, and to the intelligent-agent enhanced semantic social web, rather than to the Web 2.0, Web 3.0 and Web 4.0 terminology currently being used and contemplated?

Social Software

The Wikipedia article on social software defines it this way: “Social software encompasses a range of software systems that allow users to interact and share data.” Clay Shirky defines it this way: “It’s software that supports group interaction.” And Stowe Boyd defines it as “software built around one or more of these premises:

1. Support for conversational interaction between individuals or groups — including real time and “slow time” conversation, like instant messaging and collaborative teamwork spaces, respectively. . .

2. Support for social feedback — which allows a group to rate the contributions of others, perhaps implicitly, leading to the creation of digital reputation . . .

3. Support for social networks — to explicitly create and manage a digital expression of people’s personal relationships and to help them build new relationships . . .”

Though Boyd’s definition is more specific than the other two, the important differences in viewpoints that exist are between the Wikipedia treatment and the accounts of Shirky and Boyd going beyond their formal definitions. In contrast to the Wikipedia account, their explications of “social software” emphasize that in the modern web-based context, social software creates emergent network effects resulting from scale and self-organization that produce the true value of the software to its users. Modern social software produces emergence when its use is widespread. It creates global attributes and patterns at the system level that are truly novel. The definition of social software I’ll use is: software that supports group interaction, and creates emergent network effects resulting from increasing scale and from the self-organization the software enables and supports.

People who view Knowledge Management from outside the field often make the mistake of viewing KM as much more homogeneous a field than it in fact is. They tend to think that “KM” means something very specific, and that what it means is the understanding of it they may have gained by reading one or two articles introducing them to it, or by talking to personal contacts they consider well-informed. But one of the first things anyone who “goes into KM” and begins to review its literature learns, is that beyond having something to do with relatively non-directive managerial activities aimed at indirectly improving the quality of decision making through manipulating knowledge, the meaning of the KM meme can vary wildly across a very broad spectrum of ideas.

A recent survey of definitions of KM by Ray Sims

initially reported 43 on in his blog. Aided by comments from others, his list soon grew to 62. Sims’s research provides a picture of the many and differing meanings of the KM meme, while explicitly rejecting the idea of arriving at a single synthetic definition. Stephen Bounds performed an evaluation of Sims’s survey when the list had grown to 53 definitions.

Here is Bounds’s analysis of the attributes identified by the definitions.

KM Activities

– Knowledge Distribution (26)?

– Knowledge Creation (21)?

– Learning (14)?

– Knowledge Classification (9)?

– Collaboration (7)?

– Knowledge Harvesting (6)

– Knowledge Discovery (2)

KM Outcomes

– Improved Execution (28)?

– Value from Knowledge Assets (12)?

– Knowledge Codification (11)?

– Knowledge Retention (3)?

– Continuous Improvement (2)?

– Cultural Change (2)?

– Improved Knowledge Processing (1)?

– Improved Resource Assignment (1)?

In this analysis, the numbers in the parens indicate the number of definitions out of the 53 that include the named attribute, and a glance at those numbers indicates that there’s a great deal of disagreement among those who have offered definitions. A review of Sims’s blog post also shows that most are quite distinct from one another.

The impression left by this and other surveys of KM definitions suggests the true state of affairs about this field – namely that

1. there is a broad measure of disagreement among its practitioners about what its core is;

2. KM is a meme with many meanings, and also

3. KM is a heterogeneous, rather than a homogeneous, movement targeted on many different ideas about how to improve the quality of knowledge informing decisions.

This has an important implication for analyses that attempt to relate KM to any other phenomenon, and specifically to relate the idea of KM to any or all of the 2.0 cluster memes; or to relate any of the sub-groups within the KM movement to any 2.0 cluster movements or sub-groups. That implication is that any such analysis must be very clear about what conception of KM is at issue in the analysis, or also, or alternatively, about what sub-group in the KM movement or 2.0 movements is the object of the analysis.

In later posts relating “KM” to the “2.0 cluster,” I’ll use the following definition of KM in my analysis. KM is the set of activities and processes aimed at enhancing knowledge processing, where knowledge processing includes: problem seeking, recognition, and formulation; knowledge production (i.e. knowledge creation, knowledge discovery, and knowledge making); and knowledge integration.This definition is one of the “outliers” identified by Sims and Bounds cited earlier. It was developed by Mark McElroy and I in 1999 and has received a good deal of discussion since then. It’s unique in making a distinction between KM and knowledge processing activity, and is embodied in our well-known three-tier model (see above), which distinguishes among KM and its outcomes, knowledge processing and its outcomes, and business processing and its outcomes.

Specifically, if one acknowledges that all the “KM activities” identified in other definitions by Bounds, are really all knowledge processing activities, then it follows that our definition recognizes all of these activities as targets of Knowledge Management, or, if enhanced, as KM outcomes, rather than as KM activities. Further, only four of the KM outcomes listed under that category would be viewed as direct KM outcomes namely: enhanced “knowledge codification,” enhanced “knowledge retention,” “improved knowledge processing,” and “cultural change.” The other “KM Outcomes” are only indirect impacts of KM from the viewpoint of the three-tier model.

Why use this definition and the three-tier model? I think the answer to that question is that the scope and boundary problems of KM are greatly alleviated by this definition, because KM starts and stops with a much narrower class of activities, which are clearly management activities targeted at enhancing knowledge processing activities. The orderly development of KM as a discipline is much more likely if the field is defined in such a way that its activities minimize overlap and turf battles with other management disciplines.

To Be Continued

In earlier posts on KM 2.0 I’ve critically reviewed many interpretations of aspects of the “2.0” trend relating to the idea of KM 2.0. Of course, such interpretations don’t end in April 2008, but have continued since then, and, if my purpose was to complete an up-to-date survey, I could continue my critical discussions through many more posts like the previous ones. However, I think my blogs up to this point have clarified the character of “2.0” phenomena sufficiently that I think it’s time to provide my own interpretation of “2.0” trends and of the character of KM 2.0 in particular. The next installments in this series will provide that interpretation, specifically an interpretation of the relationship between Knowledge Management and what I will call the “2.0” cluster. Here’s the first of the set of final installments in this lengthy series.

For about five years now, the “2.0” meme has been circulating in organizations. It began with the introduction of the label “Web 2.0” to describe those IT applications that applied web technology to social interaction on the Internet. Thinking about Web 2.0 a bit more abstractly soon led to two closely related categories called “social software,” and “social media.” These categories overlap with, but don’t quite coincide with, “Web 2.0,” since both can be associated with applications that precede Web 2.0 and can, conceivably, also include projected existing or projected Web X.0 (Web 3.0, web 4.0, etc) applications.

Applications related to all three of these categories first included blogs, wikis, social network analysis, social networking applications, collaborative content tagging, folksonomies, community support/collaboration software, and project collaboration software. But as time passed, these categories came to include many web services applications, “mashups,” digital videos, podcasts, social bookmarking, news aggregation, and virtual environments.

Some time after the introduction of Web 2.0, some enterprising observers (beginning with Andrew McAfee in March of 2006), viewing the beginning of a trend to bring Web 2.0 tools inside the firewall, began talking about “Enterprise 2.0” as a type of enterprise that has implemented “social software platforms” including Web 2.0 tools for purposes of increasing social connectivity, collaboration, and decision support within the enterprise.

The KM 2.0 meme surfaced independently and before “Enterprise 2.0” in the fall of 2005 and has been gradually spreading ever since. IBM Global Services picked up the meme in 2006 at about the same time as the appearance of Enterprise 2.0, and lent considerable weight to its circulation. By the fall of 2007, with “Enterprise 2.0” rapidly gathering a buzz, and, I think, reinforcing “KM 2.0,” the KM World and Intranets Conference, had made “KM 2.0” the theme of their 2007 conference.

Since then, the discussion of KM 2.0 among practitioners has accelerated, including favorable comments about it expressed by KM notable Tom Davenport, but there’s no consensus about whether “KM 2.0” is a useful notion, indicating a major new beginning in KM, a sort of ‘second chance.” And there’s also no consensus on what’s meant by KM 2.0, or how it relates to KM, or more generally, how KM relates to Web 2.0, social software, social media and Enterprise 2.0.

By the “2.0 cluster,” I mean Web 2.0, social software, social media, Enterprise 2.0 and KM 2.0 – all current 2.0 memes. In the posts, I’ll offer my understanding of: each member of the 2.0 cluster, the relationships of each member with KM, and also my reasoning in developing this relationship. After I do that, I’ll end by considering a recent and, I think, mistaken conjecture made by an Enterprise 2.0/social media enthusiast that the “KM” and Social Media (SM) movements “are locked in an undeclared cultural war for the soul of Enterprise 2.0.”

To Be Continued

This post completes my analysis of Ray Sims’s presentation to the Boston KM Forum on April 9, 2008. Ray envisions three scenarios to relate Web 2.0 and KM. The first of these states that “Web 2.0 is ideally situated to support Personal Knowledge Management / Personal Learning Environment (PKM/ PLE).” Ray argues for that by presenting a “View Your Mind” map of his own personal learning environment. He distinguishes the following categories in his “mind map”: text, audio, writing and drawing, formal training, people, data and information hacks, physical space, and reflection. Within the text category, blog-related 2.0 applications, web-related 2.0 applications, intranet-related 2.0 applications, and reference 2.0 applications are mentioned. In the audio category, feedreader, ipod, and podcast web 2.0 applications are mentioned. In the writing and drawing applications, blogging is mentioned. In the people area, web 2.0 social networking applications are mentioned. In the data and information hacks category, a personal wiki is mentioned. The majority of listed items in the mind map are not Web 2.0 applications.

Ray then claims the following benefits of Web 2.0 tools for individuals.

— Increase knowledge within chosen field

— Maintain long-term employability

— Build external network

— Bridge generational barriers

— Increase competency for thriving in information abundance

— Opportunity to become an enterprise 2.0 evangelist

Most of these benefits, even if one grants that Web 2.0 produces them, don’t speak directly to KM goals. “Increase knowledge within chosen field” does. But, the connection between the tools and this outcome is vague in the slides, and I don’t know whether a more precise connection was made by Ray in the oral presentation. “Building an external network” may be viewed as an outcome that enhances the activity of building external relationships with other KM professionals.

In short, the case made that Web 2.0 tools strongly support either a Personal Learning Environment or Personal Knowledge Management is not made in this list of benefits, though I think a stronger case for this can be made, if one were to get into the detail of how Web 2.0 can support various knowledge sub-processes that are aspects of personal learning. Ray goes on to present a Twitter illustration. But I think the illustration is one of people communicating and exchanging bits of information. The connection between twitter exchanges and learning or improved knowledge processing is implied but not made explicitly here.

Ray next moves to claimed company benefits and he offers these:

— Smarter employees

— Reduced Training & Development expense

— Access to external networks

— Bridge generational barriers

— Create an enterprise 2.0 on-ramp

I think the “smarter employees” benefit may be there but it needs testing and demonstration. Reduced training and development expense sounds like a reasonable benefit claim, but again, it has to be shown that the impact of Web 2.0 tools really does reduce the need for formal training and development. “Access to external networks” seems like a straightforward benefit, but “bridge generational barriers” may or may not occur from increased use of Web 2.0 tools. Finally, creating an E 2.0 “on-ramp,” may or may not be viewed as a benefit. It depends on whether E 2,0 has been successfully sold first.

Ray then goes on to prescribe that companies get involved in Web 2.0 and presents a list of necessary 2.0 competencies, and Dave Pollard’s 2.0 vision. I’ve commented on Dave Pollard’s vision in an earlier post in this series. Ray’s 2.0 competencies are to the point, but the tools themselves will not produce these, they have to be created by people before they adopt the tools.

Ray’s second scenario he calls “the easy entry,” and expresses it this way: “Enterprise (KM) 2.0 is easily adopted & instantly valuable for small to medium sized teams and projects.” There’s an immediate problem with this, since, his treatment of KM doesn’t show that E 2.0 is KM. Ray presents a few additional slides arguing that introduction of blogs and wikis is very valuable for Team Project-level practice, and also suggesting abandoning using e-mail. But any specific argument relating these changes to enhanced knowledge processing is absent.

Ray’s third scenario is enterprise adoption of 2.0, which he suggests, is already happening in some enterprises and shows some promise. He suggests that the four greatest opportunities, from a KM point of view, in case of adoption of E 2.0 are:

— Increased social capital

— Increased innovation

— Improved decision making

— Improved efficiency

While these opportunities may exist, Ray isn’t clear about why E 2.0 creates the first three opportunities, and thus far the empirical record is unclear on whether E 2.0 does create such opportunities. Ray covers the fourth opportunity, “improved efficiency,” in more detail. He mentions the following five effects of E 2.0 in relation to increasing efficiency.

— Increased transparency (openness)

— Network effect

— Raw speed, e.g. wiki edits versus documents

— Less overhead

— Opportunity to reduce email

Other slides amplify his reasoning. One slide shows that wiki collaboration involves fewer exchanges and steps than e-mail collaboration. Another slide quoting Matt Moore, makes it clear that blogs and Twitter are more open than e-mails and instant messages. He also points out that reducing e-mail involves a move to “pulling” as opposed to “pushing” information, and is also a move to collaboration on a work product, rather than talking about such collaboration. He also points out that these work products are “more open,” and “more easily tagged and searched” than e-mail.

But then, Ray considers “concerns and challenges” about introducing E 2.0. These include: 1) linking intellectual property, 2) running counter to the need for compliance, 3) loss of control by management, 4) wasting employee’s time, 5) doesn’t fit with the company culture, 6) technology immaturity and proliferation, and 7) additional information silos and digital landfills. Items 4), 6), and 7) suggest an increase in inefficiency and conflict with the claim that E 2.0 increases efficiency. I think this is a matter of balance between effects that increase efficiency and those that decrease it, and that the claim that efficiency will be increased, like the other claims for E 2.0 benefits, is, at best, a hypothesis.

Ray ends his very interesting presentation with some advice including: “decide if the utility metaphor is viable.” If so, then consider an “intranet 2.0” approach, or one “leading with core work processes.” Also, “find and nurture the early adopters and innovators,” start with an “individual, team or company function strategy versus the entire enterprise,” integrate/coordinate technology, workflow/process, and people “on enterprise 2.0 path.” Ray also points to three critical success factors: “a champion or champions,” a “comprehensive training and assimilation plan,” and “comfort with user-driven innovation and emergence.”

This is all good advice. But it highlights some real difficulties of implementation. Champions may be hard to come by without more proof that E 2.0 will be beneficial, whether or not it enhances knowledge processing, and we really don’t know what a “comprehensive” training plan for E 2.0 might involve. And finally, if “comfort” with innovation and emergence is a key success factor, then we may have a “chicken-egg” problem, since such comfort tends to be correlated with previous success relating to innovation and emergence. So, the companies that may need E 2.0 the most, may be in no position to adopt it.

Ray ends his presentation by urging people to “just do it” with respect to E 2.0, and also to “engage in the knowledge management debate.” I have tried to do that in this extensive review of his thinking, because I think it is among the most valiant attempts made to relate Web 2.0 to Knowledge Management. But I think I’ve shown above that, in the end, his conceptualizations of both KM and Web 2.0 are not really precise enough to support his analysis of the relationship between the two. He asserts a number of things about the relationship. But his detailed arguments really don’t make the case that Web 2.0 tools have a special significance for KM beyond the notion that in the proper circumstances and context and, perhaps along with other tools, Web 2.0 tools can help Knowledge Managers to enhance knowledge processing. But the same can be said of many other software tools including Web 1.0 tools, so the task of showing a special relationship between Web 2.0 and KM and hence some basis for saying that there is a KM 2.0, still remains.

To Be Continued

Richard Vines and I have just released a paper entitled “Interoperability and the Exchange of Humanly Usable Digital Content Across a Global Economy.” The paper has been published at both an Australian and a US web site. It discusses how to achieve interoperability in XML dialects, i.e. how to transform or translate XML-based digital content from one XML language to another, within one overarching transformation architecture. Some approaches to this problem reflect the theory that such translations can be completely automated, but Richard and I think, and argue in this paper, that this aspiration could well prove to be very problematic. In contrast, any transformation system – we think – must build within it a provision to apply Human Interpretative Intelligence (HII) to continuously reformulate the transformation rules and models used in such systems.

We also think, and argue, that it will be necessary to make a technical design choice about the means by which the translation process between different XML languages is achieved. By way of making our case, we examine three transformation systems that have three entirely different ontological approaches to address the same translation problem: the Common Ground Markup Language, (the CGML system), Contextual Ontology_X Architecture (the COAX system) and OntoMerge system.

Based on work by Kuhn, and Popper’s answer to his claims about incommensurability, we suggest that the primary criterion for comparing alternative translation/transformation systems for XML standards and schemas is the ease of formulating expanded frameworks/revised theories of translation that create commensurability between source and destination XML content and the merged ontologies. We break this criterion down into two sub-criteria: 1) the relative commensurability creation load in using each system, and (2) relative system provisions for and constraints on the use of human interpretative intelligence. On both of these sub-criteria, a detailed critical evaluation indicates that the CGML system is better than the other two, OntoMerge is next, and COAX ranks as the system with the highest commensurability creation load and the least relative provision for incorporating human interpretative intelligence.

The need for human intervention, and the need to make a technical design choice about the way in which content is translated – have important implications for the development of any global interoperability architecture, in the context of the current push for the semantic web initiative. We conclude by suggesting that premature standardization should be avoided, and that there is a need for further thought and careful additional comparison and evaluation before any system, including those reflecting the semantic web initiative, is adopted as the basis for any global XML interoperability architecture.

This post continues my analysis of Ray Sims’s presentation to the Boston KM Forum on April 9, 2008. In approaching “Knowledge Management,” Ray again asks what the term “means to me.” He begins by describing his own research on definitions of KM. His initial effort produced 43 separate definitions which he reported on in his blog. Aided by comments from others, his list soon grew to 60 definitions. Ray’s research provides a comprehensive picture of the diversity of conceptualizations of KM and their relationships, while explicitly rejecting the idea of arriving at a single synthetic definition.

In his presentation, Ray transitions from the diversity of KM definitions to three key definitional questions that are important to answer to understand the kind of KM one is doing. The questions are: what is the scale of KM? What is the domain of KM? And what are the metaphors we can use to understand or define KM?

Beginning with “scale,” I very much agree with the idea that focusing on scale is important. Ray distinguishes the individual level of analysis with its personal learning environments and personal KM, from the team, community, and project levels with their knowledge management and learning processes, and the organizational level with its learning and KM processes and activities. In my own work, I’ve made similar distinctions, specifically referring to levels of nesting of knowledge processes in organizations, and to KM targeting based on both knowledge sub-processes and agents (individuals, teams and projects, friendship and other self-organizing groups, organizational sub-divisions, committees of “experts,” communities of practice, and the organizational level). I think distinctions among agent levels are rather fundamental to KM since the complexity and expense of interventions tends to be correlated with the level of targeted “agents.”

Ray’s next definitional question relates to the “domain” of KM. Here Ray begins by asking the question, “where does KM start or stop?” His slide on this presents a number of categories in white, gray and blue ellipses. The slide is effective in displaying the broad range and diversity of categories associated with KM in one way or another, and therefore in highlighting the boundary or scope problem, and the fuzziness of its boundaries. In fact, it may be the best slide I’ve seen yet on this problem. Ray’s treatment continues with some of the results of Stephen Bounds’s evaluation of Ray’s survey of definitions of KM. Stephen performed his evaluation when Ray’s list had grown to 53 definitions. Here is Stephen’s analysis (also quoted by Ray) of the attributes identified by the definitions.

KM Activities

— Knowledge Distribution (26)?

— Knowledge Creation (21)?

— Learning (14)?

— Knowledge Classification (9)?

— Collaboration (7)?

— Knowledge Harvesting (6)

— Knowledge Discovery (2)

KM Outcomes

— Improved Execution (28)?

— Value from Knowledge Assets (12)?

— Knowledge Codification (11)?

— Knowledge Retention (3)?

— Continuous Improvement (2)?

— Cultural Change (2)?

— Improved Knowledge Processing (1)?

— Improved Resource Assignment (1)?

In this analysis the numbers in the parens indicate the number of definitions out of the 53 that include the named attribute. Ray highlights “improved knowledge processing” in this slide, and in the next one discusses this definition as an “outlier,” though not pejoratively. Before I move on to that slide however, I’d like to point out a couple of things. First, while all of the “KM activities” are performed by knowledge managers in the course of their work, they are also performed by “knowledge workers” in general. That is, none of these activities are exclusively or primarily knowledge managerial in nature. Rather, it is more accurate to call them “knowledge processing activities.” Second, note that if we take all the “KM activities” in Stephen’s categorization and place the word “enhanced” in front of them, then they look just as much like KM Outcomes as the listed items under this last category.

These comments bring us to the point made by both Ray and Stephen that the definition of KM as activities and processes intended to enhance knowledge processing is unique in making a distinction between KM and knowledge processing activity. Of course, that definition, as indicated by both Ray and Stephen, is the one developed by Mark McElroy and I, over the years, since 1999. Ray proceeds to amplify the distinction by presenting our three-tier model which distinguishes among KM and its outcomes, knowledge processing and its outcomes, and business processing and its outcomes.

I think Ray and Stephen are right to recognize the difference between our definition and others, but I’m not sure they draw out the full implications of our definition. Specifically, if one acknowledges that all the “KM activities” identified in other definitions by Stephen, are really all knowledge processing activities, then it follows that our definition recognizes all of these activities as targets of Knowledge Management, or, if enhanced, as KM outcomes, rather than as KM activities. Further, only four of the KM outcomes listed under that category would be viewed as direct KM outcomes namely: enhanced “knowledge codification,” enhanced “knowledge retention,” “improved knowledge processing,” and “cultural change.” The other “KM Outcomes” are only indirect impacts of KM from the viewpoint of the three-tier model.

Why accept our definition of KM and the three-tier model, rather than some of the other definitions? I think the answer to that question is that the scope and boundary problems Ray highlights in his presentation are greatly alleviated by this definition, because KM starts and stops with a much narrower class of activities which are clearly management activities targeted at enhancing knowledge processing activities. With such a definition, KM efforts are much less likely to overlap with general management efforts, or with content management or customer relationship management.

The orderly development of KM as a discipline is much more likely if the field is defined in such a way that its activities minimize overlap and turf battles with other management disciplines. KM already has the difficulty that the distinction between it and information management is very hard to make. To define KM in such a way that the term means the broad range of activities we do when we are making and integrating knowledge (and in some definitions, even when we use knowledge, which is all of the time), is disciplinary suicide because it is a continuous source of conceptual confusion for the field.

Next, I’m not sure Ray’s use of the term “domain” in the above context is a good choice. Certainly discussion of KM activities and outcomes is important, but I think that his “scale” and “domain” categories are really about how to cut up the world in such a way as to distinguish the targets, or foci, of KM. I do think the term “domain” can be usefully applied to the description of targets. Specifically, I think the issue of business domains is an important one. KM needs to be focused on specific levels of interaction (agents), and on specific activities or processes, but, also, I think it needs to be focused in specific business domain areas since the quality of knowledge processing in organizations may often vary greatly across different business domains in the same organization.

Moving on, Ray’s next definitional question focuses on “metaphors.” He mentions “stocks” and “flows” as important metaphors in defining KM. “Stocks” are static and are associated with codifying, capturing, harvesting, and storing knowledge, while “flows” are “fluid” and “dynamic” and are associated with “conversations,” “fragments,” and “connections.” The idea that the “metaphors” one uses to talk about, describe, or analyze “knowledge” may have important effects in how one defines KM is an idea I agree with. In KM it is an idea that has been advanced by Daniel Andriessen who is referenced by Ray in his presentation.

However, though I agree with the general idea of the impact of metaphors about knowledge on our ideas about KM, I don’t see it as very different from the idea that the conceptual frameworks or “paradigms” we use to talk about, describe, or analyze “knowledge” will affect how we define KM, or how we view it for that matter. So, I’m afraid I don’t see what is novel or particularly important about the idea. After all, why shouldn’t our epistemology, i.e. our theory of knowledge, affect how we define KM?

In any event, Ray’s highlighting that many view “knowledge” as a stock, is surely correct. And a stock at any point in time is certainly static. However, I don’t see what’s static about activities such as “codifying,” “capturing,” “harvesting,” and “storing.” That is, it seems to me that such activities are always changing from moment to moment, and therefore are dynamic in character.

Next, is the metaphor of viewing knowledge as a flow, as dynamic and as associated with connections, conversations, and fragments. I must confess that I think the idea that “knowledge is a flow” and therefore is not a “thing,” is a misuse of ordinary language. It’s not that I doubt that knowledge claims can be expressed in messages and sent from person to person, or store to store, through connections, so that such claims can be said to “flow” through a network in the form of communications. Certainly this is a valid and sensible way to look at the exchanges between and among human beings, and the exchanges of bits and bytes that occur in organizations. However, I think that such flows of knowledge claims don’t in any way contradict the idea that what the knowledge claims assert is linguistic content with its logical and semantic content and that this content is comprised of abstract objects. On the contrary, the idea that “knowledge flows” from node-to-node in social networks, presupposes the prior existence of static knowledge claims that can be communicated through flows of various kinds.

Of course, the fact that knowledge claims occur in conversations, and may be expressed in fragments, and that both are exchanged through connections, doesn’t mean that the knowledge claims themselves are dynamic. In fact, the fragments expressing knowledge claims and connections through which they are communicated, are static at any point in time, while the conversations are dynamic and continuous even while the knowledge claims made in the course of such conversations express static content objects.

Ray does ask the question “why flows?” and lists the following points:

— Speed of change versus speed of codifying

— Continuous versus something that happens at the end of the project

— Small pieces loosely joined, context preserving

— Broader participation, with more connections

— Weak signals perception

— Results: innovation and better decision-making

He also quotes Dave Snowden to the effect that:

“If you ask someone, or a body for specific knowledge in the context of a real need it will never be refused. If you ask them to give you your knowledge on the basis that you may need it in the future, then you will never receive it.”

I’m afraid I don’t see the connection between these points and whether knowledge ought to be viewed as a flow. Again, my basic problem is as above. Just because we can make knowledge flow, doesn’t mean that “knowledge” is a flow. And, if we define it that way, it will lead to a definition of KM which is quite misguided, because that definition will overlook the idea that it is our knowledge processes that produce change in the things we call knowledge.

Ray takes the idea of “flow” further by using two of the metaphors analyzed by Daniel Andriessen, “knowledge as water,” and “knowledge as love.” He points out that in Andriessen’s panel study, “knowledge as water” was favored most as a metaphor for diagnosing the KM problems in a situation, while “knowledge as love” was favored most as a metaphor for developing KM solutions. And to illustrate this he quotes some diagnoses of problems and some solutions developed by Andriessen’s panelists. Without quoting the detail here, I’ll simply say that most of the diagnoses are not very relevant to common sense KM concerns, and even though the solutions are a little more relevant, one of them, namely “Don’t try to manage and systematise knowledge,” is in direct contradiction with the others since they are all clearly prescriptions for KM activity.

In general, while I liked Ray’s emphasis on scale, and domain, I thought his emphasis on “metaphor” in defining knowledge should have been replaced with a more formal consideration of alternative theories of knowledge and their implications for how KM is defined. In my view, these too, involve metaphor, but given their more explicit and elaborated nature, they are more subject to illuminating critical analysis and fair comparison in arriving at the theory of knowledge that will best complement one’s own view of KM.

Reviewing Ray’s presentation up to this point, we see that his treatment of Web 2.0 is vague in specifying actual Web 2.0 configurations and that his treatment of Knowledge Management emphasizes the diversity of conceptualization in the area, but lacks an assessment of the various definitions and a decision about which definition he will use in relating Web 2.0 and KM. Let’s keep this in mind as we review his treatment of how they are related.

To Be Continued

Back to blogging. The Presidential campaign is now over, a few other commitments are completed, and I’m now free to end my unexpected vacation and continue my KM 2.0 and Knowledge Management series.

This entry will continue my discussion of presentations given at The Boston KM Forum on April 9, 2008. Ray Sims offered a very interesting and imaginative presentation entitled: “KM and Web 2.0 – A User’s Perspective,” covering four topics: 1) Web 2.0, 2) Knowledge Management, 3) three scenarios for bringing the two together, and 4) some closing thoughts. I’ll break my discussion of Ray’s presentation into a few posts because I think it reflects many of the existing problems people have in thinking about KM 2.0, Web 2.0, and Knowledge Management.

Ray’s approach to Web 2.0 is to explain “What “2.0” means to me . . . “ That’s done with a graphic; a “mind map” with the “2.0 meme” at the center and with links from the meme to six associated nodes or dimensions of the idea: a) My Networks, b) Emergent, c) Fast, d) It’s All About Me, e) Open, and f) Always On. These dimensions are then further broken down by associating them with other nodes or sub-dimensions. The resulting conceptual hierarchy is a clean one (perhaps too clean) since each sub-dimension is associated with only a single dimension.

Even though this mind map is supposed to illuminate what Ray means by Web 2.0, all of the sub-dimensions under a), b) c) and e) refer to social characteristics rather than to Web 2.0 software with the exception that the “perpetual beta” is one of the sub-dimensions of Emergent. However even this reference to software is not exclusive to Web 2.0. Further, while category f) includes the sub-dimensions Global, 24x7x365.25, Mobile Devices, Software As A Service (SAAS), and “virtual,” I don’t think any of these categories are associated closely enough with Web 2.0 to even begin to give one a clear idea of what it is.

The one category where Web 2.0 software associations are named is d) “It’s All About Me.” That category is associated with the following sub-categories: User Generated Content, Diversity, The Long Tail, Software Application Choice, Tags, Folksonomy, Personal Brand, Mass Career Customization, and Informal Self-directed Life-long Learning. Of these characteristics, only “tagging” and “folksonomy” seem to refer directly to Web 2.0 software tool capabilities. “User Generated Content” is associated with Web 2.0 software, but certainly not exclusively, since content management portals can also support user-generated content, and Web 3.0 tools will certainly also provide this sort of capability. Web 2.0 does involve “software application choice”; so this, too may be added to the very few characteristics actually associated with Web 2.0 software.

Ray’s next slide expands on the thinking presented in his mind map slide by offering a two column table contrasting “traditional” and “new world” profiles, the implication being that the “new world” characteristics are associated with a Web 2.0 profile.

Apart from Ray’s attempt to use only two profiles to describe organizations, a clear over-simplification, I also think that his profile characterizations associate social and IT characteristics in a way that is questionable from an empirical point of view. I recognize that these profiles are Ideal types; but nevertheless, to be useful, the “traditional” profile has to at least approximate the pre-Web 2.0 enterprise and the “new world” profile has to be one that it is at least possible to approximate in reality.

Whether highly differentiated 21^st century organizations where “right-brain” functioning and “uncontrol” are dominant can exist is still arguable, depending, of course, on what one means by “control” and “uncontrol.” But given ownership structures of, and legal requirements for, formal organizations of all kinds, it seems highly doubtful that they can. In saying this, I don’t mean to deprecate the present trends toward networked organizations and trans-networked organizations, but I think real organizations can at most be mixes of Ray’s two profiles.

Apart from this problem, when we look at both slides together, we see that they seem to focus more on conceptualizing “2.0” as an idea, than they do on specifying what a Web 2.0 software configuration is. That is, it seems that Ray is more focused on conceptualizing an expansive view of Enterprise 2.0, even though he doesn’t use that term, than he is on putting forward a specification for Web 2.0 as a set of social computing tools. Having said that, the right hand-side of the table is better than the mind map at listing Web 2.0 software, including micro-blogging, blogging, wiki, tagging and folksonomy, and personal learning environments. But its specification is far from a representative list, and ignores mash-ups, a category that may yet prove to be the most important in the Web 2.0 lexicon, since it provides the ability to create and make use of composite applications that may support knowledge processing more broadly than the products of software vendors.

In sum, in considering Ray’s attempt to characterize Web 2.0, I think we see an over-reach, and one that is not uncommon. In previous reviews of writing on Web 2.0 we have also seen a tendency to define it by going beyond the tools themselves to social attributes that are “necessary” requirements of Web 2.0. There’s nothing wrong with doing that, of course, but it is necessary to keep the distinction between Web 2.0 tools and the associated characteristics of successful Web 2.0 separate, so that we do not define-in success, but make “success” the result of an empirical assessment of what happens when we introduce the software, rather than a mere logical consequence of our definition of Web 2.0.

To Be Continued