How Valtech data scientists helped unlock billions in savings

This client is a global food and beverage leader with a wide portfolio of brands and near-global operations.

Data underpins everything this client does. Data helps the company forecast demand across a massive global supply chain. It helps align multi-brand strategies. It informs product development and helps the client get even closer to their many customers around the world. 

They asked us to optimize the way they work with their internal and external data. Since 2019, our data scientists have worked with this client on a number of transformative projects.  

The client’s supply chain success hinges on precision.   

If they over-forecast, they purchase too many materials, commit too much budget up front and pay to store excess inventory. If they under-forecast, they risk production shortfalls, miss sales and spend resources on rush supply-chain corrections.  

We built them a dynamic, AI-native forecasting system designed to eliminate waste, optimize procurement and strengthen supply chain resilience. 

The solution was built on four key pillars: 

• Opportunity assessment that continuously monitors the accuracy of forecasts to uncover performance gaps and machine learning opportunities 

• AutoML implementation that rapidly identifies and promotes the best-performing models 

• An ensemble modeling framework that adapts to shifting patterns and inputs 

• Continuous learning architecture that improves over time, not just during deployment 

This self-learning system helps the client reduce material waste, improve forecasting precision and strengthen their global supply chain against future shocks.

As the client began tearing down their own internal brand silos, new opportunities emerged to scale data capabilities across the organization. 

Whenever we built a data component, we assessed where else it was needed and how fast we could scale it. By reusing tools across teams, we freed up resources and unlocked millions in annual savings. 

• By eliminating forecasting errors, we freed up $2.7 billion in working capital to be invested elsewhere. Each year, the dynamic supply chain minimizes carrying costs, which unlocks a further $500 to $700 million in working capital. 

• By ensuring what we build is reusable across the organization, we save the client about $84 million annually. 

Together, these initiatives continue to deliver durable value across our client's global operations.