AI/ML Prescriptions

While BIRetail’s “Inferences” can provide answers to every question you ask, it is extreme grunt work to manually scavenge for every single issue that could go wrong for a Retailer in a single day.

Prescriptive Analytics is the technique to get actionable recommendations from BIRetail, without asking!

With our rich domain expertise, BIRetail has identified common operational areas in Retail that tend to grow slack and require constant tweaking to optimize their business efficiencies. Each of these Business Use Cases use a combination of extensive data and a massive weave of ‘if-then-else’ type of decision trees that look at a plethora of permutations of rules to arrive at a recommendation for each granular actionable.

The approach built within such recommendation engines is to simulate the step-by-step problem-solving thought process that a human undertakes to arrive at the best solution for a single problem. And that is why techniques are named ‘artificial intelligence’. The way such systems are coded, they allow the engine to constantly learn ways to handle new scenario based on past patterns, and hence these engines also deploy ‘machine learning’ techniques.

BIRetail uses Data Science algorithms to create each such Prescriptive Analytics Use Case. Once the business rules are configured for each individual Retailer, the benefit is to have a cheat sheet of prescribed recommendations to be carried out, without diving into a plethora of data and analysis.