Smart Meal Planning

With support of:

Smart Meal Planning conducts research on the potential of AI in predicting production quantities in case of last-minute adjustments in the food industry.

Why this project?

Many producers of fresh and perishable foods have similar business processes for their ordering procedures. Orders from their customers are typically placed in two stages. In the first stage, long before the effective delivery date, a relatively large volume is ordered. In the second stage, typically very shortly before the effective delivery date, the producer receives last-minute adjustments to the initial order volume. However, the timing of the second stage no longer allows for traditional production. This results in an imbalance of HR planning, rushed orders of raw materials, extra pressure and stress on kitchen staff, and when demand drops, an excess of produced meals that remain unsold. In addition, typically only the final (adjusted) order quantity is invoiced, regardless of the size of the late adjustments.

While the potential of AI is often clear to these companies, internally they generally lack the resources and technical knowledge to develop this AI potential themselves. There are also barriers to adopting existing software platforms: digital maturity of the food company and AI maturity of software vendors, training of staff, but also the fact that a prediction system for non-perishable goods is simply not accurate enough for perishable meals.

Research approach and results

Smart Meal Planning is a collective practice-based research project (TETRA type) that aims to give AI companies more clout to increase their sales market towards the food sector and food companies, enabling the latter to achieve more efficient production planning.

This will be done by demonstrating the added value of AI in predicting production quantities through various case studies.