Retailer SPAR Austria is aiming to minimise food waste in its stores through increased digitalisation of the group's inventory.
In cooperation with Microsoft and a number of other partners, the retailer has developed a solution that facilitates more targeted order suggestions and demand forecasts for all stores.
Using AI, a new solution from SPAR ICS looks at data around sales volumes, weather conditions, marketing promotions, seasonality, and other factors, in order to produce a precise forecast of optimal product order quantities per store.
An automatic ordering system, which has been in place at SPAR Austria for decades, forms the basis of the new system, which has recently trialled in the fruit and vegetable segment.
The new system claims a prediction accuracy of over 90%, meaning that the right amount is available in the right store at the right time.
"The advantages are manifold – not only for SPAR Austria, suppliers, customers, and team members – but above all for the environment. In this project, SPAR uses the potential of technology and AI to meet the needs of our customers and save resources at the same time," said Markus Kaser, SPAR Austria board member for IT, buying, marketing, and CSR.
The retailer is implementing the project in cooperation with SPAR ICS, Microsoft, and Paiqo, an AI company.
Microsoft Azure’s Advanced Analytics tools use cloud-based data, enabling an easily-managed supply chain.
"The predictions are a valuable support for team members involved in the ordering process. AI does not replace previous processes but rather complements them. The optimisation of the supply of over 1,500 stores also has a positive impact on the work of our 40,000 in-store team members," added Hans K Reisch, SPAR Austria’s deputy board chairman.
Food Waste At SPAR Austria
Products that are close to their best-before date are sold at a reduced price on a separate shelf or via Too Good To Go or donated to social organisations.
Every SPAR, EUROSPAR, and INTERSPAR store in Austria has a fixed charity partner located close to the individual store.