Earlier research commissioned by ECR has shown that removing inaccuracies from stock records via a stock audit may lead to a substantial sales lift that has been found to be between 4% and 11%.

While the advantages of error-free stock records are apparent, retailers may decide to accept small errors in stock records for low-value SKUs sold in large quantities to reduce the effort associated with stock audits.

Some retailers may therefore use an accuracy range instead of a binary measure of accuracy for classifying their stock records. In this case, a stock record that differs by (say) 1% from the stock level actually available in the store may still be regarded as accurate.

The extent to which and how an accuracy range influences sales, as compared to a binary measure of accuracy, has not yet been investigated. In this meeting, the academic team will present their proposal to conduct new research that could help fill this information gap.

Retailers will then discuss the research proposal with the academics and share back how they could imagine this new research could help them make better decisions and improve their operations.