Harnessing the Power of AI to Minimise Food Waste

Given their short shelf life, milk and dairy products can be tricky when it comes to food waste management. The REIF (Resource-Efficient, Economic and Intelligent Food Chain) project is exploring Artificial Intelligence (AI) based approaches to turn milk and dairy products from a challenging product group into a key contributor to food waste reduction.

In August 2020, the CSCP and its project partners met at the headquarters of the German retailer Tegut in Fulda to get a first-hand impression on the different store concepts, including detailed tours of the back offices. The visit yielded valuable insights into the daily work routines in the retail sector and the related consequences for the implementation of automated, demand-driven and markdown mechanisms for milk and dairy products.

The learnings and insights were jointly analysed during the second half of the visit. The team discussed how a markdown, which is a price reduction for products with a short expiration date, could be effectively implemented at Tegut. A wide range of aspects, from technical to behavioural ones, were on the agenda:

  • How can the markdown be implemented technically?
  • How to design impactful monetary incentives for the consumers?
  • How can you set a price based on the expiration date while ensuring that the product itself is not devalued?
  • What communication strategies are necessary in order to ensure that consumers understand and endorse the markdown concept?

Using the example of Tegut, these questions were discussed in detail, leading to new ideas which will be further developed and piloted during the upcoming months.

As a project partner, CSCP’s focuses on ensuring an efficient integration of all relevant stakeholders, both during and after the project. The CSCP is also supporting the participating companies to adapt operational processes and organisational learning through trainings and capacity building.

The REIF consortium consists of 18 partners and it will be coordinated by the University of Applied Sciences Augsburg. The project is funded by the Federal Ministry of Economics and Energy (BMWi).

For further information, please contact Rosa Strube.