Professionals in the applied sciences make progress through careful experimentation and measurement. In pursuits where human behavior and other intangibles are at stake, such as KM, progress isn't as straight forward. To make good decisions about where to invest our time and effort, KM professionals need a measure of what efforts work and a way to forecast their potential benefits. Fortunately, some smart people in fields very different from KM have shown that you can reduce uncertainty and make better predictions with little hard data. This presentation looks at how to apply some of those principles to KM using models such as Fermi questions and Monte Carlo simulations. With these models, we can begin to reduce the uncertainty in projects and generate numbers to work with. And with those numbers as a starting point, we can make more informed and analytical decisions that consider the tangible and intangible variables that determine program success. The result? Better decisions and better tools for reacting to the outcome of KM efforts.
Click here for the overview.