Robert Grossman had a nice post - Five Common Mistakes in Analytic Projects that made me think about the role of decision management in putting predictive analytics to work. Of Robert's 5 mistakes, 3 are directly addressed by decision management:
- There is not a good plan for deploying the model
Because decision management is focused on applying models in operational systems and because it combines a focus on business rules to automate decisions with analytics to make them smarter, there is always a plan for deploying the model with decision management. - Working backwards, instead of starting with an analytic strategy
Decision management always begins with the decision in mind - focusing on the desired outcome, using that to drive the definition of the analytic project and thus the data to be integrated etc. - The predictions of the model are not actionable
Decision management provides a framework for doing exactly what Robert suggests - understanding the measures for a decision (part of decision discovery), defining the actions to be taken - the rules (part of decision service development) and analyzing the results to understand what works and what does not (decision analysis).














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