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Tom DiMattina, vice president supply chain at Bayer, tells how the company adopted a demand-planning tool from OMP to enable digital transformation and processing reengineering.
DiMattina focuses on two areas within Bayer’s consumer health organization — one aimed at achieving digital supply chain excellence, supporting all supply functions across North America, and the other devoted to cross-functional management within the company’s upper respiratory supply chain group.
Bayer’s initial challenge was to improve the planning function while coping with rising inflation and supply chain turbulence. It set forth to take out cost, optimize inventory and improve the demand signal to factories — all without raising prices for consumers.
Following a review of several vendors serving the marketplace, Bayer chose OMP to address its demand-planning processes. DiMattina says the company realized that it could customize the standard OMP platform to take advantage of the wealth of real-time consumption data coming from its retailers. In the process, it came up with a “sell-in/sell-out” forecasting model. “We had all the data,” he says, “but no way to put it all together and integrate it into our demand-planning process.”
Artificial intelligence is a key element within the application. Bayer can use a large language model to send and receive emails, then feed the resulting data back into the system for accurate demand planning. “AI is a way of leveling the playing field,” DiMattina says.
Bayer now has a team dedicated to creating “touchless” demand planning. “We want to try and make it as hands-free as we possibly can, so they can focus on enriching the forecasting and further improving accuracy,” he says.
The company plans to extend the OMP software to cover the supply side as well, with the vendor acting as its global partner for supply and demand planning across the enterprise.
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