As one of the largest millers in North America, grain producer ConAgra Mills is tasked with staying as close as possible to its customers, most of whom are small food producers and bakers who need to react quickly when their customers' baked goods preferences change. As with any consumer-facing business, these small companies are driven to keep their costs as low as possible without a concurrent reduction in service or quality. And many of these companies also depend on ConAgra Mills to not only provide them with flour products, but with price risk management as well.
As consumer tastes have changed over the years, so has the complexity of flour production. ConAgra Mills produces more than 800 different SKUs of flour, from 23 plants running every day of the week. But while product complexity was increasing, ConAgra Mills was losing out on opportunities to maximize its business. As Bill Stoufer, the company's president, recalls, too often ConAgra Mills was operating on a random basis in terms of measuring capacity in the various plants, which meant some mills were more full than others.
The company had been using a traditional ERP system, but ConAgra Mills found that it needed a way to transform that production and capacity information into a form that its sales staff could use when negotiating deals with their customers. Ideally, the food giant was looking for a way to predict market changes and customer needs a year to 18 months in advance.
"Our customers operate in an increasingly complex and volatile market environment," Stoufer points out, adding that in the search for a better way to maximize capacity utilization, ConAgra Mills found the answer well outside of the milling industry, in fact, outside of process manufacturing entirely: the airline industry.
The two industries aren't as dissimilar as one might think, Stoufer points out. "If a plane leaves with empty seats, they miss the opportunity to maximize their business. It's the same within the milling business." Both industries seek to minimize unused capacity without overbooking resources. Just as the airlines want to fill every seat using the optimum number of planes, so too does a milling company like ConAgra Mills seek to keep all of its plants producing the right products in the right quantity at the right time.
As a means to that end, ConAgra Mills adopted a predictive analytics solution developed by high-tech giant IBM Corp. and SignalDemand, a provider of supply chain optimization solutions. The solution helps ConAgra predict future market conditions for its business as well as for its customers, by offering them more affordable products.
Using the dashboard for capacity utilization, ConAgra Mills can accurately predict for its customers where it has open capacity, Stoufer notes. The company can now better focus on the most profitable products since the solution provides insight into underlying supply chain costs. In fact, capacity utilization has increased by 3% to 5% in the year since the dashboard solution was adopted, which translates to several million dollars of incremental revenues. Improved margin decisions have also helped the company maximize revenues.
