In my last post, The Headlong Rush Into Analytics, I dabbled with several analytics tools to graph the undergraduate majors of law school attendees over a recent 14-year period. Ask a real data scientist if “dabbling” is the right word for describing my little experiment and the response will probably be some combination of rolled eyes, grumbling and sighs. That’s what experts in any field of endeavor tend to do when they come across a layperson dabbling in their specialty. Each and everyone of us has done our share of dabbling, and we’ve all probably reacted with disdain when viewing the dabbling of others in our own areas of expertise. I know for certain that I’ve often enough snorted at the amateurish efforts of others who ignorantly comment on KM or, worse yet, roll out some application and call it a knowledge management initiative.

What is it about dabbling that makes it so irritating and yet so strangely irresistible to those of us involved in knowledge management? Think about it. Dabbling is in some respects a precursor or catalyst for KM. You might even say that the purpose of KM is to harness the curiosity and confidence that compels one to dabble and to guide it in a structured way toward just-in-time understanding. In short, knowledge management is supervised dabbling! Continue reading “Dabbling”