Waitrose improves stockholding, reduces waste
The ‘Waitrose’ name has become a byword in the UK for the highest quality, freshest produce and widest product range in-store. This leading supermarket brand is now using SAS® to forecast customer demand, helping ensure the right products hit the right shelves at the right time.
Part of the John Lewis Partnership, Waitrose is one of the UK’s best-known grocers, with a brand promise based on high quality products, from fresh fruit and vegetables to packaged goods, combined with outstanding customer service. Waitrose is a unique retailer for two reasons. First, it’s the only supermarket to hold a Royal Warrant from HM Queen Elizabeth II. Second, the business is co-owned by its 39,000 employers or ‘Partners’ rather than shareholders.
With some 190 branches carrying over 15,500 product lines - and 30% of the range new each year – Waitrose needs to ensure it predicts demand accurately to supply the right products to the right stores in a timely way. Ordering the correct stock is essential, to maximise sales and ensure the least waste possible. On a regular basis, it’s also important to ensure the right stock is in place for specific events and promotions: chillers full of special-offer ice cream as the heat wave hits, shelves stacked with mince pies as Christmas approaches. Now, with the help of a SAS® demand forecasting solution and support from SAS partners, Waitrose is achieving more accurate store replenishment, satisfying the needs of its valued customers and balance sheet alike. Since the system rolled out, the branches have seen a reduction in stockholding of at least eight percent and a fall in wastage of up to four percent.
Matching supply with demand
Waitrose looked at various vendors in a formal tender process, narrowing six down to two. “We saw solutions like SAS that could do the whole job for us: using historical data to improve normal forecasting, observing sales and reacting to seasonality, as well as improving event forecasts,” says Richmond. Waitrose was not previously a SAS user. “One reason we chose SAS was that the other solution was a ‘black box’. You can use SAS as a ‘black box’ but it’s also very flexible: you can continue developing it to meet specific forecasting needs. We also believed we could have a good working relationship with SAS - a partnership.”
“We wanted to continue using our branch ordering system, developed in-house, but with a new approach to demand forecasting,” says Kim Newark, Forecasting Systems Manager. However, problems emerged with the system performance and the forecast models during trials says Newark. “So we involved StatApp, a SAS partner with expertise in retailing, to improve the model. The project ended up very much a partnership between Waitrose, SAS, StatApp and another SAS partner, Amadeus, the latter helping us sort out performance. After all, we were forecasting for every product line, every day, for every branch overnight.” This additional development led to further trials, which delivered greatly improved results, and the system was rolled out across the store estate. SAS models now run overnight, with forecasts automatically feeding into the Waitrose stock control and replenishment system.
More in store
We have achieved increased productivity, efficiency and financial gains across our 190 or so branches,” says Richmond. “With the help of SAS we have been able to reduce stockholding by at least eight percent and reduce wastage by three to four percent. We’d originally estimated a two percent drop in wastage, so this is far better than predicted. In addition, we can look at past events and see if mistakes were made, at Christmas say, and put them right next time. Or look at successes and try to replicate them. SAS is very good at providing visibility of the forecasts, to measure accuracy.”
The next step, says Richmond, is to push forecasting further back along the supply chain to predict what Waitrose orders from suppliers. “In terms of forecasting, we wanted to look at where we could achieve the biggest benefits first, which meant the branches – we knew we could make big gains there,” Kim Newark concludes. “As we move forward, we would say ‘where do we go next?’ using the same data and our forecasting in different ways.”
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Support branch ordering and customer service as effectively as possible: consistently ensure the highest product quality and availability, minimise wastage, control costs in a highly competitive retail space.
SAS® modeling and predictive analytics for accurate demand forecasting, both for day-to-day forecasts and particular events/promotions
Faster and more accurate demand forecasts to improve stock ordering, delivery and replenishment; stockholding reduced by 8% and wastage reduced by up to 4% plus improved customer service and satisfaction through higher product availability.
“We can look at past events and see if mistakes were made, and put them right next time. Or look at successes and try to replicate them. SAS is very good at providing visibility on the forecasts, to measure accuracy.”
Manager - Branch Ordering Development