Harris Farm Markets Taps DataRobot for Demand Forecasting

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With over two dozen stores and an expanding geographic footprint, the chain needed a way to consistently meet consumers’ demand for variety and freshness. Harris Farm Markets Head of IT, Phil Cribb, turned to DataRobot to implement an artificial intelligence and machine learning platform that could generate accurate predictions, with minimal labor on the part of the IT team.

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Challenge
Predicting grocery needs is difficult, especially in the recent unpredictable environment. Harris Farm Markets needed a way to consistently meet consumers’ demand for variety and freshness.
Solution
Using DataRobot’s Automated Time Series, Harris Farm Markets put in place a data-driven decision-making solution for the chain’s stocking operations taking into account a wide range of data points, from seasonal impacts to customer numbers.
Result
Within a few months, Harris Farm’s DataRobot implementation resulted in 400 deployments for demand and 30 for customer-number forecasts, using 25 individual models for hourly numbers and five clustered models for daily numbers. The net result: an estimated tenfold increase in capacity of their resources to create demand forecasts, leading to much more accurate purchasing of perishable inventory.

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