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Modeling Magic
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February 7, 2005 (Computerworld) --
Operations research, the application of modeling and mathematics to business problems, had had a checkered history at The Procter & Gamble Co. since it was first tried in 1968. That all changed in 1993, when P&G hit a financial home run using the process and operations research (OR) leapt to prominence at the company.
In the early 1990s, the maker of Pampers diapers, Pert shampoo, Pringles potato chips and nearly 300 other consumer products decided to look broadly and deeply into its entire North American manufacturing and distribution network, and it tapped two IT staffers to join a team charged with reducing supply chain costs and improving efficiency. The project team developed computer models that pointed the way to a supply chain restructuring that would consolidate P&G's North American plants by 20% and lower supply chain costs by $200 million a year.
"That project planted a seed," recalls Glenn Wegryn, one of the analysts on the project and now associate director of P&G's 17-person OR group, known as IT Global Analytics. "It really was a wake-up call about the capability you could provide by using OR tools tied to a deep understanding of how P&G's operations worked."
While many companies put OR in their engineering or research departments, P&G put its OR group in its IT shop. "IT is one of the very few organizations within a company that has true end-to-end visibility into all the operations of the company," says Wegryn. "Part of our success is that we are a crossover capability; we have as much business knowledge as we do knowledge of our instruments and tools."
Wegryn's group works on some 100 projects a year and has worked in every P&G product category and geographic region. Most, but not all, of the problems considered by Global Analytics can be thought of as supply chain questions: How many plants should there be for this new product, and where? Where should distribution centers be located? What's the optimum transportation network? How can we deliver faster and better to these particular customers?
Glenn Wegryn, associate director of P&G's OR group
Image Credit: Ted Rice
P&G applies IT-assisted analytic techniques in three broad areas. First, it uses optimization models to determine how best to allocate supply chain resources, most often on the basis of net present value.
Second, simulation models allow P&G to mathematically try out various options to see how they might play out over time, and to test the sensitivity of results to changes in key variables. Simulation and optimization models are often used together. An optimization model may point to an option that is further evaluated and tweaked by simulating how a supply chain would behave under that option and how stable it is.
"We've found that the success of a supply chain is not necessarily operating at the absolute optimal solution, but operating at one of the more robust solutions in the real world," says David Dittmann, a Global Analytics manager.
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