In the summer of 2018, social media users in the UK began posting photographs of empty shelves at stores run by four of the country’s largest supermarket chains. Market researcher IHL estimates that out-of-stocks cost traditional brick and mortar retail stores $984bn across the world and $144.9bn in North America. The retail sector often bears the brunt of such criticism because the failures in its supply chain are so conspicuous. Yet the struggle to forecast and meet demand transcends industries and markets. Many companies are now seeking to manage this challenge using an approach known as demand sensing, which uses new mathematical techniques and real-time data to predict short-term demands accurately. Demand sensing has its roots in demand forecasting, which has been with us since the 1950s.
