A.I. forecasting to reduce food waste - COVID-19 impact

The UK hospitality industry generates over 1 million tonnes of food waste each year, equivalent to approximately £3 billion in cost and over 4.5 million tonnes of CO2\. At the same time, UK restaurants yield a meager 3-5% average profit margin, making it one of the least profitable industries in the country. This economic struggle has been dramatically exacerbated by the COVID crisis. Through effective food waste reduction, restaurants can boost profitability by up to 2pp, while drastically reducing the environmental impact of their operations. The key to reducing food waste lies in accurate demand forecasting. Restaurants order their perishable inventory days and weeks before selling dishes to their customers. Given that most restaurants rely on rigid 4-week demand averages and gut instinct to make their procurement decisions, food orders are routinely in excess of real demand - creating food waste. Tenzo will research & develop a cutting-edge forecasting tool, which will allow restaurant businesses to accurately forecast customer demand. Utilising powerful artificial intelligence algorithms, the tool will achieve the following objectives: * Generate accurate restaurant sales forecasts based on historical sales, weather, public events and other features * Split daily forecasts into item-level and hourly projections * Provide those forecasts to frontline workers (chefs, section managers, etc.) within a user-friendly mobile app - enabling them to know easily how much food to: * prepare and when (e.g. how much chicken to grill every hour); and * order and when (e.g. how much fish to order for next week). Tenzo's project will focus on finding the most accurate forecasting algorithms and combining them with a user-friendly software interface to ensure frontline workers are empowered to reduce food waste in their day-to-day operations. By 2024, our tool could reduce annual UK hospitality food waste by over 38,000 tonnes, CO2 by over 175,000 tonnes and restaurant costs by over £20 million.