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.
criteria for measuring a sucessful outcome
hierarchy here). Figure 1. Criteria Priorities for my requirements. Assuming I am satisfied by this priority layout, I can ask further questions such as would the decision change if I excluded low priority criteria? Figure 2 illustrates the TESS response to this question. In the spider diagram, criteria decline in priority going clockwise from the top. The light blue dashed line indicates the cumulative priorities of the criteria, going from about 15%+ each for Basic features and PC Synchronization