Machine Learning Steps Up Retail Performance

Unless you’ve somehow avoided the intense competitive pressures of eCommerce, retail is a tough place to be right now.

Sears, Macy’s and JC Penny are closing stores.

American Apparel and The Limited are gone.

Amazon is rewriting the retail playbook in ways that are leaving competitors struggling. And to make things even more challenging, consumers are constantly raising the bar in their expectations for an exceptional customer experience.

In this environment, running your supply chain the way you always have probably won’t get you where you want to go.

It’s time to consider the options. And one of those is stepping up your supply chain planning.

A more optimal supply chain increases fill rates, improves on shelf availability, and turns inventory over more rapidly.

It’s about better forecasting, inventory optimization and replenishment.

And now a new technology, machine learning, can help overcome even the most challenging obstacles, including new product introductions, extreme seasonality, promotions, and even short shelf life items.

It’s changing the face of supply chain planning, helping companies break through their supply chain and business performance barriers like never before.

Costa Coffee is sensing demand at 5600 points-of-sale (POS) with an award-winning supply chain. Internet retailer Wayfair achieved a 6 to 1 reduction in planning workload, while increasing inventory turns to faster than Amazon.

Download the white paper and consider how machine learning based supply chain planning can accelerate your business performance.

Find out how in just two months of running a new machine learning system, Aston Martin reduced the inventory value of its safety stock items by 18 percent while immediately improving FTA service levels to 97.1%, above its target.