Enterprise analytics initiatives are advancing along a natural progression, starting with descriptive analytics that tell us what our organizations and our customers have done in the past. Then, predictive analytics help to show us what the organization or customers are likely to do in the future. However, the greatest value lies in prescriptive analytics, where data shows us likely options for how we can respond to the upcoming changes and trends highlighted at the predictive stage.
Afterall, knowing something is likely to happen doesn't help if we don't know what to do about it. Prescriptive analytics can guide us to suitable solutions.
Hyoun Park, Chief Research Officer of Blue Hill Research, joins All Analytics Radio to discuss how enterprises can move from the predictive analytics stage to prescriptive analytics where they can put data into action. Blue Hill has developed a framework for that thought process and the steps to get to prescriptive analytics and meaningful insights. In this show you will learn:
- About some of the best practices in developing predictive analytics, setting the stage for an eventual move to prescriptive analytics
- What types of applications lend themselves to use of prescriptive analytics
- How to blend the suggestions for action raised by prescriptive analytics apps with a decision maker's experience and "gut" feelings
- How prescriptive analytics are being used in the real world today
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