Case Study: Blue Bottle Coffee improves pastry ordering accuracy with Provectus AI demand forecasting

Blue Bottle Coffee increases ordering accuracy, cuts food waste through ML-driven demand forecasting

Blue Bottle Coffee, a global coffee roaster and retailer, wanted a better way to forecast pastry demand across its 70+ cafes. Cafe leaders were manually estimating orders several times a week, which often led to underordering, stockouts, overordering, and unnecessary food waste. To solve this, Blue Bottle Coffee partnered with Provectus to build an AI-powered demand forecasting and predictive ordering system.

Provectus developed machine learning pipelines on AWS to ingest sales and inventory data, train and compare models, and generate pastry demand forecasts for daily and weekly ordering. The solution gave cafe leaders and developers a user-friendly way to review and adjust predictions, while improving ordering accuracy by 8% in July versus the previous month. The result was less waste, better food utilization, fewer stockouts, and a stronger bottom line for Blue Bottle Coffee.

Blue Bottle Coffee