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o9 Solutions, Inc. > Case Studies > Digital Transformation in Coffee Retail: Reducing Waste and Improving Customer Focus with AI-Powered Forecasting
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Digital Transformation in Coffee Retail: Reducing Waste and Improving Customer Focus with AI-Powered Forecasting

Technology Category
  • Functional Applications - Inventory Management Systems
  • Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
  • Recycling & Waste Management
  • Retail
Applicable Functions
  • Warehouse & Inventory Management
Use Cases
  • Demand Planning & Forecasting
  • Inventory Management
Services
  • Data Science Services
The Challenge
A multinational coffee roaster and retailer, with a network of over 30,000 coffee houses worldwide, was facing significant challenges in its operations. The company's baristas were spending around six hours a day on administrative tasks such as ordering, inventory management, and forecasting, which was detracting from their ability to focus on customer service. Additionally, the company was grappling with a significant food waste problem due to inaccurate forecasting. This issue was complex, as each store stocked between 500 and 5,000 SKUs, and demand volatility was influenced by factors such as weather, assortment, pricing, and local events. The company had invested in data science teams and developed proprietary algorithms to predict the impact of weather on demand and store traffic, but these were not being utilized to their full potential.
About The Customer
The customer is a multinational coffee roaster and retailer, with a network of over 30,000 coffee houses around the world. The company is committed to reducing waste and improving customer service, and as part of this commitment, it initiated a large digital transformation program. The company has invested in data science teams and developed proprietary algorithms to predict the impact of weather on demand and store traffic. However, it was facing challenges in terms of significant food waste due to inaccurate forecasting and baristas spending too much time on administrative tasks rather than customer service.
The Solution
The company initiated a large digital transformation program with o9, aiming to reduce administrative work for baristas and decrease waste through AI-powered forecasting, assortment planning, and replenishment on a single platform. The o9 platform was able to automate forecasting, replenishment, inventory management, and assortment planning, using analytics and minimal manual input. The company was also able to forecast at a Store-SKU level, incorporating leading indicators such as weather and local events. For local events, an app was developed to support baristas in inputting their local knowledge about the market. Changes in weather or local events would drive auto-replenishment based on o9’s digital brain. The company's proprietary algorithms, developed in Python, were incorporated into the o9 platform, allowing the company to run AI algorithms at scale.
Operational Impact
  • The implementation of the o9 platform led to a significant transformation in the company's operations. Baristas were able to spend less time on administrative tasks and more time focusing on customers, leading to improved customer service. The company's food waste problem was also significantly reduced due to more accurate forecasting and replenishment. The company was able to leverage its investment in data science teams and proprietary algorithms, running these at scale on the o9 platform. This allowed the company to respond more quickly to changes in demand and make more accurate predictions about the impact of weather and local events on store traffic and demand.
Quantitative Benefit
  • Significant reduction in hours spent on manual planning and inventory management at a store level
  • Substantial reduction in the volume and dollars of food waste
  • Improved assortment planning and faster response to changes in demand

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