Inventory Management/ AI-based forecasting in grocery stores
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Inventory management or warehouse management is a bigger challenge than it appears to be. But, it’s not impossible to minimize the losses that occur due to over/under-stocking.
Real-time data allows grocery stores and supermarkets to forecast the potential sales and demand of their items through predictive analytics, highlighting which items are in demand and those to discard. This removes the problem of stock that’s just taking up space on shelves and not selling; this solution reduces overall inventory costs, ensures high-demand items are always in stock, and increases potential revenue.
Some older forecasting techniques work on products as clusters and can’t take the local dynamics into account. A good AI model can make predictions about products at a granular level considering local and regional trends.
Benefits for the company
Data Science helps supermarkets and grocery stores better manage their inventory and have the optimised amount of stock for each item.
Feasability
High
Type of expertise/ AI domain
Prediction, Forecasting, Clustering
Internal data required
Stocks Data, Demand, Purchase Data
Predictive analysis is saving millions of expenditures for today’s food and beverage retailers. AI solutions these days are very flexible and customizable, so you can achieve near-perfect predictions that consider market scenarios, seasonal shifts, customer preferences, competition moves and any other aspect that influences a product’s demand and the time a product spends in warehouses or the store shelf.