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The next phase is Predictive Analytics. This is when historical performance data is combined with rules, algorithms, and occasionally external data to determine the probable future outcome of an event or a likelihood of a situation occurring.
The final phase is Prescriptive Analytics. Prescriptive Analytics goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and showing the decision maker the implications of each decision option.last=Stewart, Thomas. R., McMillan, Claude, Jr. |title=Descriptive and Prescriptive Models for Judgment and Decision Making: Implications for Knowledge Engineering|journal=NATO AS1 Senes|year=1987|volume=F35|pages=314–318}}</ref> Prescriptive Analytics not only anticipates what will happen and when it will happen, but also why it will happen. Further, Prescriptive Analytics can suggest decision options on how to take advantage of a future opportunity or mitigate a future risk and illustrate the implication of each decision option. In practice, Prescriptive Analytics can continually and automatically process new data to improve prediction accuracy and provide better decision options. <ref>{{cite
==History==
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