Prior to the pandemic, average grocery profits hovered around 2 percent, largely due to store and supply chain inefficiencies. Shifting product demand and rollercoaster sales further compounded these issues, with stores now throwing away one-third of fresh inventory. This over-ordering not only costs profitability, but forces retailers to increase prices to make up for these losses.

At a time when grocery stores are pushed to the limit, one grocery automation system drastically increases sales and margins while reducing the 43 billion pounds of annual food waste. Currently in more than 2,000 grocery stores nationwide, Seattle-based Shelf Engine’s intelligent forecasting and order automation system uses advanced statistical models, machine learning and neural networks to generate the most accurate orders for grocers.

Shelf Engine recently announced a $41 million Series B funding round to expand ordering solutions to grocers facing mounting customer, labor and competitive pressures. The round, which brings Shelf Engine’s total funding to date to $58 million, was led by General Catalyst.