What is the difference between Descriptive and Prescriptive Analytics in a retail context?

All answers to this question.

Think of it as an evolution. Descriptive is your "Rearview Mirror"—it tells you sales were down 10% last week. Prescriptive is your "GPS"—it tells you that because sales are down and a storm is coming, you SHOULD discount winter gear by 20% tomorrow to clear stock. To get there, you usually need a Predictive layer first (forecasting). While you don't necessarily need to be a Python expert, you do need to understand optimization algorithms. Most BAs use tools like Alteryx or specialized supply chain software that handles the heavy math, but you must understand the business constraints to feed the model correctly.

   Answered 2024-08-24 by Barbara Martinez

Do you think your current data quality is high enough for prescriptive models? Most projects fail here because the underlying data is too messy for an algorithm to trust.

   Answered 2024-08-26 by Richard Davis

• Richard hits the nail on the head. Prescriptive models are extremely sensitive to "garbage in, garbage out." Before Matthew tries to prescribe actions, he should perform a Diagnostic analysis to find out WHY the sales dipped. If the data isn't clean, the "prescription" the AI gives might actually hurt the business rather than help it.

     Commented 2024-08-27 by Michael Brown

In retail, prescriptive is all about the "Next Best Action." Start small with a single product category before trying to automate your entire inventory logic.

   Answered 2024-08-29 by Jennifer White

• Great advice, Jennifer. A pilot program in one category is the best way to prove the ROI of advanced analytics to a skeptical VP.

     Commented 2024-08-30 by Matthew Wilson