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.
information that one can get from epr tutorial
is using typical descriptive information to remove from the mix the choices that obviously will not match. In order for this to be adequate and reliable, information needs to be present, presented in a way that enables a quick elimination. Side-by-side table constructs can help, but can also confuse, and are not necessary for this first step. To filter a few out of a large number of choices, however, can require better tools, as we shall see below. From this process, I have narrowed down the choice to