77521Machine learning to help the hospitality industry recover through optimised food productionClosedCollaborative R&DInnovate UKThe global hospitality industry does not have a tool that can accurately help it predict how much food to produce, and when. This results in both economic and environmental challenges. Overproduction of food leads to vast costs; in the UK Hospitality and Food Service Sector, food waste was estimated at over £2.5bn in 2011, with 75% of it recorded as avoidable. The environmental impact is monumental; if global food waste were a country, it would be the third largest emitter of greenhouse gases after the USA & China. Overproduction also lowers food quality. Underproduction causes its own issues; hurting customer satisfaction and margins. Providing chefs with a tool which can give them actionable insights based on a wide range of data including weather patterns, historic waste, time of day and demographic of customers could help them optimise their production. This project aims to build on WSL's experience of building machine learning models and presenting actionable data to chefs in around 1500 kitchens to build a prototype production planning tool which can be presented to customers for feedback. This project's timing is imperative; the hospitality industry has been one of the hardest hit by COVID-19, and needs tools to help it have greater control over operations and margins.