From what if to what's best in DSS

Abstract The author of IFPS/OPTIMUM presents some typical applications of optimization within decision support systems (DSS). They show that finding ‘what's best’ is gradually superseding the ‘what if’ and ‘goal seeking’ type of analysis that is prevalent now. IFPS/OPTIMUM is now used by over 130 companies, including many of the Fortune 500 ones. The main drawback of ‘what if’ and ‘goal seeking’ type of analysis is that one cannot impose restrictions on model variables and have the DSS generator solve for values of the ‘what if’ or ‘goal seek’ variables that satisfy those restrictions. Instead, one would have to muddle through many ‘what if's’ or ‘goal seeks’ at random and check if the restrictions are satisfied. It is a manual process that is very time consuming. ‘What's best’ analysis with optimization allows one to impose such restrictions easily and do the analysis quickly. This type of analysis is playing an increasingly significant role within decision support systems. Practicing management scientists and managers should note this phenomenon. New tools and new ways of addressing problems are emerging.