At a meeting a few weeks ago with Fujitsu representatives, I heard about their BToPPe framework. This is a system that can help to ensure that companies understand all relevant dimensions of investments which are made.

I hadn't heard of this framework before, but found it interesting:

Essentially, it's just a SWOT analysis, but focusing the enterprise on overlapping domains that may impact on the potential success of a project. For complex issues, it may be a good tool to examine possible impacts in a structured way.

There's a book called "Predictably Irrational" by Dan Ariely. While I wouldn't really recommend the whole book, it did contain one experimentally-supported concept which I found interesting.

In essence, the experiment tested the idea that humans operate according to either social norms, or market norms.

If true, this would explain why some companies struggle to achieve effective collaboration: their environment emphasises market norms, and thus the what's-in-it-for-me principle wins out.

On the other hand, if the company achieves an environment where social norms are dominant, effective collaboration is much more likely.

In an ongoing debate on actKM about the relationships between knowledge and information, Foucault's concept of pouvoir-savoir has been raised by Michael Olsson. The original quote is here:

« Il n'y a pas de relations de pouvoir sans constitution corrélative d'un champ de savoir, ni de savoir qui ne suppose et ne constitue en même temps des relations de pouvoir... Ces rapports de "pouvoir-savoir" ne sont donc pas à analyser à partir d'un sujet de connaissance qui serait libre ou non par rapport au système de pouvoir ; mais il faut considérer au contraire que le sujet qui connaît, les objets, sont autant d'effets de ces implications fondamentales du pouvoir-savoir… » (« Il faut défendre la société »)

I have a confession to make.

Most of Web 2.0 leaves me cold. All this hype about Wikipedia, social networking solutions that will magically sustain themselves and revolutionize the world (Facebook, I'm looking at you) is generally just so much marketing bullshit, frankly.

So I tend to yawn a bit about books that yammer on about harnessing social power. But after reading the Ars Technica interview with author Clay Shirky as part of a review of Here Comes Everybody, I had to revise my opinion.

Ray Sims has done a sterling job in assembling 43 54 different published definitions of Knowledge Management.

As most people who have worked in the area know, one of KM's commonly quoted flaws is that there isn't one "gospel" definition of KM.

I thought it would be interesting to work through the definitions and summarize how these definitions talk about KM.

Tom Davenport makes an excellent point in his most recent post about the challenges of decision making:

We have lost much of the connection between the supply of information and the demand for it in decision-making. Despite the fact that companies often justify IT projects on the basis of better decisions, there is seldom a direct tie between the information a particular system produces and the decisions that are supposed to be based on it.

(An edited version of a post to Bob Lewis's Advice Line)

CMMI has evolved to handle the complexities of trying to standardize processes across a large enterprise.

Beyond a certain size, even finding out the current state of play is difficult, let alone trying to co-ordinate standards through a centralized body. Attempts to do this include Enterprise Architecture, CMMI, Six Sigma etc etc.

The problem is that "one size fits all" can easily turn into "one size fits none". Innovation is easily stifled when all changes have to go through layers of bureaucracy (which I presume CMMI imposes).

A fascinating article in Fast Company magazine about the research being done by Duncan Watts to empirically test the famous tipping point theory of Malcolm Gladwell.

In essence, Watts sets up simulated worlds with strict constraints. Some are controlled through AI agents, while others rely on real-world input from thousands of human volunteers. The results are, to my mind, pretty compelling:

Watts wanted to find out whether the success of a hot trend was reproducible. For example, we know that Madonna became a breakout star in 1983. But if you rewound the world back to 1982, would Madonna break out again? To find out, Watts built ... an online music-downloading service ... filled it with 48 songs by new, unknown, and unsigned bands [then] recruited roughly 14,000 people to log in. Some were asked to rank the songs based on their own personal preference, without regard to what other people thought. They were picking songs purely on each song's merit. But the other participants were put into eight groups that had "social influence": Each could see how other members of the group were ranking the songs.

In the days past when I worked for the IT support section of DSTO, this mystical program called "TARDIS" popped up from time to time.

They didn't tend to talk to the IT department (or at least not the part that I worked for), so it was always a bit amorphous and no-one seemed to know what it actually did.

Well, Graham Durant-Law has a number of informative PowerPoint presentations (particularly this one) and it explains the process in more detail.

I have a lot of respect for the work that Anecdote does, but I'm going to have to come down entirely on Dave Snowden's side on the ongoing debate between him and Shawn.

I was pleased to see that Dave picked up on my comment about McDonald's employees not being knowledge workers. I think the attitude of management towards McDonald's staff is a clear example of why preserving the notion of a knowledge worker is still important.

For those insisting on a definition of "knowledge worker", mine is quite simple: it's being employed for the knowledge you bring rather than the knowledge you will be taught.

Yes, it's a simplification and ignores a lot of edge cases, but it captures an important large chunk of the difference.