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What-if analysis can be used as a process in data-driven decision making toinspect the behavior of a complex system under some given hypothesis. Wepropose a What-If Machine that creates hypothetical realities by resampling thedata distribution and comparing it to the an alternate baseline to measure theimpact on a target metric. Our What-If Machine enables both a method toconfirm/reject manually developed intuitions of practitioners as well as givehigh-impact insights on a target metric automatically. This can supportdata-informed decision making by using historical data to infer futurepossibilities. Our method is not bound by a specific use-case and can be usedon any tabular data. Compared to previous work, our work enables real-timeanalysis and gives insights into areas with high impact on the target metricautomatically, moving beyond human intuitions to provide data-driven insights.

Should you make your decisions on a WhIM? Data-Driven Decision making using a What-If Machine for Evaluation of Hypothetical Scenarios