Al Rubenstein+ spoke about his concept of knowledge nuggets (or intellectual nuggets) and the conceptual KM system in which they are used. In essence, these nuggets are If/Then statements that capture essential intellectual ideas and concepts, though Al acknowledges that the nuggets may take other forms such as correlations and influences.
These nuggets fit into a KM system with two knowledge flow processes: collection and use. Nuggets are collected via a debriefing interviews or discussions at the end of projects, changes executive positions, routine debriefings, during preparation of training materials, etc. These are then collected into a "raw nugget pool" after which the raw nuggets must be refined, verified and tagged to be useful to the organization.
How are the nuggets used? Al identified two main processes. First, users need some way to identify their question or problem and probe the nugget pool for likely answers. Second, users or the system need to be able to screen the candidate nuggets for applicability to the question at hand. Finally, there is an aspect of review once the nuggets have been applied. How well did the nugget(s) fit the situation, and what were the short-term and long-term results of using the nugget(s).
Beyond defining the basics of nuggets that the accompanying KM system, Al spoke about his long experience in research and consulting with organizations. At every step along the way, he had an anecdote from his work to add color to the ideas and help us see how the concept could apply to reality. A major aspect is the user acceptance of such systems - especially the barriers to user acceptance. He provided a long, familiar list of barriers & facilitators to user adoption of KM systems. He also discussed a number of aspects around how KM systems need to be designed and measured, many of which appear in his new book.
Of the anecdotes Al shared with the group, many had to do with people having very self-centered views of the company. These may be the funnier examples, but they certainly point out human nature: Q. How do you decide the inventory levels in your facility, Mr. Foreman? A. Enough to keep me from being fired. One can find these kinds of examples in any area of the business from purchasing to mergers and acquisitions to executive turnover.
The concepts Al described are exactly that. He has not built a specific system; rather he gave us an idea of how any KM system can be described in the terms he uses. He is clearly convinced that the outline he provided is the way to go for the system. He also fully acknowledges the issues associated with user adoption and buy-in from the corporate environment. Taking a quick glance at his book, he has gone into more depth on these aspects than he did in the talk.
What I heard in the description of nuggets is a return to expert systems, particularly in the If/Then format that Al prefers for the nuggets. However, I think the KM system Al discussed, the expert system is a small part of the overall picture. The knowledge nuggets must be continually renewed as new nuggets become available and as the existing nuggets are used in new settings, where the traditional expert system has a more static knowledge base. And there is the need to look at the bigger picture of how the KM system works within the organization and metrics associated with use of the system.
The discussion was based on his new book, Installing and Managing Workable Knowledge Management Systems, Rubenstein & Geisler, 2003. The book collects a number of nuggets associated with what they have learned about KM systems and presents them at the end of each chapter, as well as in the summary at the end of the book.
+ Al Rubenstein has a long history of research and thinking about management of technology that comes out in his talks. He has taught at Northwestern University in the Industrial Engineering and Management Sciences for many years and is now "retired," which means he has started a consulting business, IASTA and will be working for many more years. He has a long list of consulting work that covers nearly all industries.