How to Leverage Big Data, Machine Learning, and Optimization in Your Omni Retail Supply Chain
Retailers are now collecting more data than ever before.
They are looking to exploit it to improve profitability using advanced analytics. A lot of attention has been given to predictive analytics, which use statistical and machine learning (ML) techniques to better predict consumer demand. Using these methods, retailers are seeing big improvements in forecast accuracy.
However, most retailers are not taking full advantage of advanced prescriptive analytics, which leverage these improved predictions and promise to deliver a profit improvement equal to or greater than that which they are now seeing from predictive analytics alone.
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Advanced Analytics Are Rapidly Changing Retail
Increases in processing power, data storage speed and capacity, and broadband ubiquity have combined to fuel a revolution in retail analytics over the past decade. No longer is it sufficient to use simplistic models based on limited data to make predictions, and then act on them using traditional approaches. The most profitable retailers are now investing in sophisticated techniques that leverage increasingly powerful computing resources to look more deeply into their businesses, find hidden drivers of demand, and make smarter decisions aligned with their ultimate goal: greater profitability.