Poor decisions are expensive and their damage cumulative. Companies invest in training in enhancing personal creativity, productivity and the like but decision analysis is given short shrift except at the higher levels of the organization or in very technical areas, like R&D or quantitative finance. On one hand it is understandable why many decision models whether deterministic or probabilistic are not used. The modeling requires a strong mathematical foundation. This is anathema for some managers who instead rely on their instincts, “their gut” to make critical decisions. So in decision making we have the two methods which cognitive psychologists call system 1 (intuitive) and system 2 (rational) thinking. In system 1 we use heuristics that have served us well in surviving uncertain environments. In system 2 we build models both formal and informal to assist us. There are weakness with each. One problem with intuitive thinking is that although it is fast, the first information we receive on any subject, we tend to treat as the most valid. In model building there is the risk of over optimization and waste of precious time. We do not need to build maps so detailed (Del rigor en la ciencia) that when opened become the country.
With this in mind, I set out to build a unified selection model to aid decision making whether for IT project comparison, product comparison, or make or buy analysis that attempts to leverage the strength of both systems, reduce their weaknesses and thereby lead to better decision making. The next several blog posts will discuss the elements of the model and in March (2009) I will release a whitepaper.