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Increff Merchandising solution is a predictive system where one day’s data may not be sufficient to give insights. For example, if you are using it for OTBs there can be other constraints like MOQ, etc. which need to be considered when making a decision. The solution consumes daily data to analyze the best use case for running your ARS (Automatic Replenishment System), and for any other analysis, the solution consumes large volumes of data, of weeks to months to years, to accurately predict the optimum demand.
Q: Why don’t Increff use AI/ML in algorithms?
A:
Merchandising is largely a theory of constraints problem and for that algorithms and statistics give not only highly accurate outcomes, but also explanations for those outcomes. AI/ML cannot give you detailed explanations.
AI/ML cannot realistically learn business constraints or take business decisions - a business leader has to feed those into the system. So there is really not much useful contribution of AI/ML in such areas.
There is nothing new to learn as such, because business constraints and rules are already well understood by the merchandising fraternity .
You do not need AI/ML to do 2+2 ! Algorithms and statistics are near accurate and millions of times faster and compared to AI/ML, for such problems
At a fundamental level, the biggest problems faced by merchandisers are
Inability to store, process and analyze large amounts of data
Making sub-optimal decisions because of the above inability
Increff MS replaces Excel with a tool that helps merchandisers with the above problems
We do not need to replace the art and science of merchandising itself via AI/ML
Assortment Planning
Q: How is MS Pro going to work for online channels? Is it even useful on that front?
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