There has been much discussion in class (and always in practice) about measurement.  Practitioners like myself are always faced with the task of justify an endeavor.  It is interesting because it is not only at the funding stages, but all along the way.  After surveying the landscape thoroughly, I came to the conclusion that most ROI calculations on KM is at best an approximation, and at worst wishful thinking.  It is important to frame the Knowledge Management program narrowly enough to fulfill on objectives, but measuring these objectives is often futile.

I recently came across the work of Karen Stephenson, and my thoughts about measurement have changed.  Karen is internationally recognized in network theory, and she is president and founder of Netform International.  Karen is a trained mathematician and anthropologist.  She discovered that by analyzing dead civilizations, which she describes as networks, she was able to apply her findings to corporate settings.  Corporations, like ancient civilizations, are nothing more than networks of people.  Inside the network exists patterns that predict success or failure of a organization by the way information flows through the network.  She goes on to describe the difference between a hierarchy and a bureaucracy, and the role within the networks of key stakeholders.

What is truly fascinating about her work to me is that she asserts you can actually measure these networks.  Her company, Netform International, does exactly this.  She goes into companies and determines the value of their networks.  She helps companies determine key personnel.  Having read the work of Robert Putnam (Bowling Alone) and Wayne Baker, Stephenson takes the idea of social capital to a much richer context.

I must admit part of me remains skeptical as I think about presenting the value of a my company’s network at the next executive committee,  Nevertheless, it cannot be any worse than the crude ROI numbers I calculate now.

This is the first time I have have blogged in awhile as I was out of town attending the Conference Board’s Knowledge Management and Organizational Learning Conference.  In addition, I was in New York on business interestingly enough looking at a e-learning solutions for the capital markets.  I will comment more on this later.

Like most people who are likely to read this blog, I am on too many mailing lists, both paper and electronic.  I try not to read most of what comes my way as if I did, I would have no time for anything else.  However, I do find the quality of the Conference Board’s material to be exceptional and relevant.  I write this because I DO read everything they send me, and it is for this reason I decided to attend this conference.  Many of the noteworthy names in KM were there.  For a complete listing please see the Conference Board’s web site.

A couple of themes emerged speaker after speaker which echo what we are learning in class.  This seemed like a brilliant intersection of the theory and the practice.  Meet people where they are, and embed the KM process in their routine, don’t impose it on top of the routine.

Perhaps more importantly than the meeting the gurus, was the opportunity to discuss with others who are in similar positions to me, the ways in which they have overcome their own organizational hurdles.  After sharing my own experiences with them, I concluded I am actually farther along than I thought.

Warren Sterling, Ph.D., Director, Development Partnerships for Teradata gave an interesting presentation about Technology and KM/OL.  He spoke more from a CRM framework, but he gave some interesting points to consider regardless of application.  For example, he distinguished between structured and unstructured data.  This has a spillover effect on tacit and explicit.  Most of what is interesting to a business is the unstructured data.  That is all of the things a business “knows” about its processes, cutomers, products, etc.  This information is usually not captured.  The way I interpreted this is that unstructured data is actually a subset of tacit information.

Using the words structured and unstructured has helped me with my project for class.  My project is an attempt to capture all of the unstructured data about my company’s e-commerce’s activities.  I would not have used this framing, but in doing so, it has allowed for a systematic approach to capturing the data.  I think this was Warren’s main point.

He went on to discuss several technologies that aid in the capture of this tacit of unstructured data.  For example, he talked about the E-Motions Database Research (University of Southern California).  This attempts to answer the research question,  “What if you could capture the face animation vectors and determine how people reacted to stimuli?”  He referred to it as Facial CRM.  In his presentation he asserted that 50-90% of interaction information is non-verbal.

How do you capture this non-verbal information and then codify it?  The example he gave was at an ATM machine.  What emotion is present as people are conducting a transaction at an ATM machine.  Clearly this is the first step at capturing tacit data in this case emotions.  While part of me finds this fascinating, there is a part of me that is terrorized by the implications.  George Orwell was right.

I would like to apply this technology to the sales process.  If I use this example in my business, it would be useful information to have the emotions of a portfolio manager captured in a database as he or she made transaction decisions.  It would provide the covering sales person a competitive advantage.  The question of course is, who would give consent to be observed in this fashion?  I plan to e mail Warren and ask if any studies of this sort have been done.  I will report back my answer.