Three Stories each week, totalling 500 words is Al's requirement. At the end of 10 classes this should achieve a letter grade equal to an A in lieu of Exams. Each story will contain 167 words more or less, and the three stories will through the magic of writing and presentation styles tie in to form a whole. If I learned anything from Larry Lessig, his ideas on UGC (user generated content) and how he ties 3 stories to make one argument, then this should be smooth sailing. Sounds simple but the math works as follows. 3 hours of watching Al's class + 2 hours of reading the material he suggests each week (this week it is 7 papers and 2 ppt's) + 1 hour to compile and write this blog will equal 60 hours of effort for this course.
Story 1: Readings for the week: I narrowed in on Steve Job's Stay Hungry - Stay Foolish, commencement speech and was pleasantly surprised that he still pays homage to Lessig in his style of presentation. Did not know he had cancer and recovered among other things. Pollard and his future of KM, came across as a depressing article, he should really style his presentation on Lessig as Jobs did. May be then his stories will connect better. The Knova white paper - 10 Principle for KM, like most folks who write about this subject make KM appear to be everything and a mystery. In this day an age of transparency and connecting with the masses, I wish folks would stop doing this particularly in white papers. Here is how the author describes KM in the starting paragraph: "depending upon the nature of the initiative. KM, as we all know, is not a technology or a set of methodologies…". The author (Tom Tobin) then goes on to list 10 principles of KM, which increases the mystery 10 fold and ends up subscribing to Pollard's doomsday vision of KM. The fourth reading "Performance management" by Cognos's Doug Barton (IBM bought them out), talks about CPM, but fails to define the acronym anywhere in the material. Doug starts out by saying that CPM is financial performance management, but then goes on to talk about everything else, so I came away wondering. The fifth reading "One more time what is KM" by Harris and Berg, talked about Tacit and explicit Knowledge, which caught my eye and appears to be a recurring theme in other papers I read, I took this one step further applied my scant datamining skills and googled "tacit and explicit" + Knowledge and got 38400 hits. This has to be an important concept, I am sure by the end of this course, this concept will rise to the top. I did a word frequency check on Casanato's "Glossary of terms" and got a score of 8 for TACIT and 10 for the term EXPLICIT. I love finding patterns using heuristic word frequency!!. The final reading "Building KM systems" by Bowman, is a well written paper that gets into data mining techniques and structure of knowledge repositories. In his conclusion he talks about the measuring the return of KM systems and the lack of approaches thereof. May be we should design systems with "measuring the return" as a key criterion, we might be in a less of a mess if we did perhaps. I will end with that thought for my first story.
Story 2: Class Notes: The Second Story: What I gained from Class this week. This being the first class, the focus was mostly on an overview, ground rules and who is Al. Did not know that Al is going in for his Juris Doctorate. I am told that on a PhD tract one has to write 1000 words a day, far cry from the 500 words a week that this blog will generate for the next 10 weeks. If in some small way I can contribute to that 1000 words, may be this blog will achieve a higher purpose. So Al, this one is toward your Juris Doctorate: Larry Lessig is the Key!! Beyond that, this course is about KM themes such as: KM Technologies, Diagnosing/Solving Knowledge problems, KM best practices, PKM, BPM/BRM (hot and new) and Knowledge Based systems.
Parting Shot for this week: BPM and BRM will be explored in detail, where in we will learn to document Informal systems using the "Swim Lane Diagram" that depicts work flow.
Story 3: Conclusion:
This is a discussion/Learning course about Data/Information/Knowledge/Wisdom by exploring 7 THEMES over a 10 week period. One view point to describe KM is to look at it as data stored in a database: Data is stored in Fields, Information is stored in Records and Knowledge is the pattern(s) that can be discovered across tables and data sets. Everything can be looked at as a Knowledge Problem if you wear the right glasses/lenses!!. Stay Hungry - Stay Foolish, and I will get there.