Replenishment Optimization Provides Morrisons with the Best Availability

Morrisons improved product availability, reducing shelf gaps by up to 30% using Replenishment Optimization, a machine learning solution for automated ordering.

Replenishment Optimization at Morrisons

For those that follow retail, you will have read of the huge turn-around and the fact that Morrisons, the UK's third-largest supermarket, has increased annual profits by almost 50 per cent.

We have been working with Morrisons for over a year now and, within 12 months, we rolled-out our automated ordering system, Blue Yonder Replenishment Optimization across 130 categories, 26,000 SKUs and in all 491 Morrisons store. This has contributed significantly to increased success in replenishment, reducing shelf gaps by 30 per cent, ultimately providing a better customer experience and reducing missed sales and waste.

Grocery faces their greatest challenge

Morrisons success is set against the grocers’ greatest challenge to date: rising commodities prices and the falling pound is stretching consumers’ purse strings. This has added to the pressure supermarkets have felt for some time, with market share segmented between discounters, dedicated online fresh retailers and old favourites. The grocery landscape has further fuelled the need to provide the best customer experience. Additionally, operational efficiencies have become critical in the road to success.

Innovative retailers are turning to advanced machine learning and artificial intelligence to help them with both these challenges, while also boosting profits and Blue Yonder Replenishment Optimization is at the heart of this change.

How is Blue Yonder helping?

People can make great decisions, but not 13 million a day. Customers’ demands and habits change too frequently for people to be fast enough, accurate enough and consistent enough. Machine Learning technology will pick up these changes in patterns accurately, with speed and consistency – and in Morrison’s case, across 26,000 SKUs and growing.

The strength of the machine learning system lies in its ability to factor in events and circumstances that a replenishment manager would not be able to accurately quantify on their own. For example, it can predict the impact that dates such as Valentine’s Day and Easter have on customer demand for certain products, and even gauge the impact the weather can have on customer purchasing habits on a day to day basis.

Replenishment Optimization at Morrisons

Simplifying the process for the best customer experience

Blue Yonder’s technology uses the data to create accurate predictions and then automates the ordering per store, per product. It also balances multiple and competing KPIs, so the level of waste and availability is optimised to KPIs.

The technology has not only helped improve product availability for Morrisons across its 491 stores, thus helping to improve the customer experience, but it has also simplified the ordering system. Employees are no longer required to spend time manually ordering, which ultimately frees up their time to spend with customers.

If you are interested in finding out more about how Blue Yonder Replenishment Optimization can help you, get in touch.

Morrisons improves Product Availability


Stephan Erb Stephan Erb

Stephan Erb is a Software Engineer driven by the goal to make Blue Yonder's data scientists more productive. Stephan holds a Master degree in Compute Science from the Karlsruhe Institute of Technology (KIT). Prior to joining Blue Yonder, he has been working at SAP.