Especially relevant for Human Resources Managers, company catering managers, sustainability managers, and controllers

Production forecasts are part of everyday life in industrial operations. Until now, however, colleagues in the kitchens of the same companies have not been supported by state-of-the-art technology in the same way as the processing area. Machine learning forecasts are changing that, supporting kitchen teams and creating process reliability. Porsche was able to pilot Delicious Data's forecasting solution last year and is now rolling it out to all sites.

Sustainability is one of the main topics of the current time. Food waste is a major driver of change in this regard. The food we waste worldwide contributes to about 8% of total anthropogenic greenhouse gas emissions. In the ranking of countries, food waste would be the third-largest emitter of greenhouse gases worldwide, just behind the USA and China. German food services account for 1.7 million tons or 14% of food waste nationwide. The intelligent use of technology can help reduce this and save money at once.

What learnings or insights will the participants take away from the session? This session will help provide an overview of how more targeted planning can have an impact on costs, merchandise usage, and sustainability KPIs for staff restaurants. Forecasts with a deep learning algorithm of expected guest traffic and menu distribution can have a direct impact on the merchandise used, resulting in savings or quality improvements. With increasing pressure from guests and staff, as well as the cost of carbon offsetting and regulatory targets, the kitchen can help achieve business goals.

We will discuss following questions:

• How can we optimize our canteen planning process, reduce cost and the environmental impact of wasted food with AI?