Enterprise decision management depends on the ability to understand the current state of the business process and what might happen to that process if inputs changed. Historically, though, the data needed to guide management decisions has been sparse, narrowly focused and of uncertain quality. To address these limitations, many organizations have turned to data warehousing, with its promise of a single version of the truth, and considerable progress has been made. Standardization of analysis has lagged behind standardization of data. As a result, managers are often faced with conflicting interpretations of the truth, all based on the same facts. As William Faulkner once observed, "Facts and truth really don't have much to do with each other."
Microsimulation modeling - an analytic method pioneered in the public sector - offers an innovative solution to the challenges surrounding enterprise decision management. First developed in the 1960s, microsimulation models were originally maintained on government supercomputers, where they spun through large data files to simulate the impact of proposed changes to tax and transfer programs. The ambitious scope and granularity of these models led a panel of the National Research Council to conclude in 1991, "No other type of model can match microsimulation in its potential for flexible, fine-grained analysis of proposed policy changes."
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