Using Artificial Intelligence to Increase Planning Accuracy and Reduce Food Waste in Canteens

A Project between Porsche and Delicious Data

EDITOR: ALINA BIERMANN

In the EU, around 88 million tonnes of food are wasted every year, accounting for 8% of global greenhouse gas emissions. Company canteens play a significant role in this, as food is wasted during processing and preparation steps, in the form of leftovers on plate returns or due to miscalculation. One of the main drivers of food waste in canteens is planning uncertainty. To counteract food waste, Porsche teamed up with Munich- based AI startup Delicious Data.

Alarge proportion of the more than 36,000 Porsche employees in Germany pass through the car manufacturer’s canteens, the so-called “employee casinos”, every day to take a break, catch up with colleagues and fill their empty stomachs. In support of Porsche’s sustainability strategy , Porsche Catering is increasingly focusing on regional and seasonal products in its food and beverage offering. In addition to reducing the ecological footprint of the food on offer, Porsche continuously monitors and analyses the amount of food wasted in order to find solutions to avoid throwing out food items. According to United Against Waste , overproduction and plate returns cause the majority of food waste in company cafeterias. The good news is that 30–50% of food waste in canteens can be avoided with better analytics and planning tools. Porsche thus engaged with Delicious Data to take its planning accuracy to the next level.

The Project

In the summer of 2020, Porsche’s Innovation Management team and Delicious Data saw a mutual opportunity for a joint project to reduce food waste caused by overproduction in Porsche’s employee casinos by using Delicious Data’s AI-based demand forecasting solution. Together with the project leaders from Porsche Catering and HR Digitalization, the teams decided on a four-month pilot project starting in November 2020 in four Porsche pilot restaurants in Weissach. The initial situation in the casinos included 40% fluctuations in capacity utilization within a week, which led to a high degree of fuzziness in planning accuracy. The joint project was intended to use forecasts to enable production to be more in line with demand. In addition, measures to reduce food waste and all relevant KPIs were to be made visible and evaluable via an analysis dashboard.

Outcome

Despite Covid-19, Porsche and Delicious Data were able to successfully complete the pilot. The goal to increase planning accuracy was achieved, and the planning deviation was reduced by up to 40% during the measurement period. Even at the pilot restaurants, where various food waste initiatives were already in place and resulting in 32% better outcomes than at the non-pilot cafeterias, Delicious Data was able to reduce overproduction by another 10%. The impact at the non-pilot restaurants is considered to be even higher. Another accomplishment is the reduction in the amount of planning time required from the casino personnel. It is expected that future time spent per week per restaurant can be reduced significantly.

Future Outlook

With the ultimate goal of reducing as much food waste as possible, Porsche and Delicious Data are now set to deploy the technology in all the other German Porsche casinos over the next six months. Other possibilities to digitize and support Porsche’s casinos are currently being examined.

Acknowledgements

We would like to express our sincere thanks to Ulf Schnoor (Porsche), Patrick Gehe (Porsche), Jakob Breuninger (Delicious Data) and Valentin Belser (Delicious Data).

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Contact for this project

Alina Biermann
Ventures Associate,
STARTUP AUTOBAHN powered by Plug and Play
alina@pnptc.com

Anja Mertens
Digitization & Innovation,
Porsche AG
anja.mertens1@porsche.de

Andy Grau
Innovation Manager
Porsche AG
andy.grau@porsche.de

Christoph Acker
Innovation Manager
Porsche AG
christoph.acker@porsche.de

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