The client, a prominent bakery-cafe chain in the US and Canada, approached Tiger Analytics with a critical need to enhance their operational efficiency. They sought to develop and implement a scalable ML-driven Demand Forecasting solution to streamline labor and inventory planning across all cafes. The client faced significant hurdles in achieving precise demand forecasts, essential for efficient labor scheduling and inventory planning. Tiger Analytics tackled the challenge of precise demand forecasting, crucial for efficient scheduling and planning, delivering actionable insights.

The impact of Tiger’s solution was transformative, significantly enhancing forecast accuracy and delivering tangible business benefits. By improving sales forecasts by over 300 basis points and order forecasts by more than 400 basis points compared to the previous system, the client realized substantial cost savings and revenue increase. This amounted to an estimated annual savings of $2 million, achieved through reduced stockouts, enhanced labor management, and decreased food waste. The project, including MLOps, was seamlessly integrated into the Google Cloud Platform, ensuring scalability, transparency, and long-term sustainability.

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