This tutorial, part 2 of a two part series on Knowledge Based Selection, demonstrates the selection processes and capabilities of Knowledge Based Selection Methods and Tools. These tools, integrated with business decision making procedures, can arguably reduce selection risk and improve chances for success in IT projects. Given the appalling rate of IT project failures, selection can potentially help reduce risk in some 30% of cases, with an associated estimated cost of about $30B annually to industry according to some sources. In this tutorial, we illustrate a number of the procedures for rapid decision processing through the real-life selection of a PDA device. The process gave confidence to the argument to wait for the solution, while weighing risk against return.
building a mousetrap car
in collecting data and building the KB was about three days, and the best fit became immediately apparent, though it upped the ticket I was willing to pay. The rest, as indicated above, is history. On a general level, the process I invoked from literally zero knowledge to a decision went through a number of steps - most of which can be accomplished in WebTESS, though more sophisticated analysis and tradeoffs were done with TESS (my advantage!). However, I could remove unacceptable alternatives rapidly,