What Is Operations Research?

In the simplest terms, operations research (OR) is the process of using sophisticated analytics to tackle complex business problems. But to the growing number of companies that rely on massive amounts of data to efficiently run their businesses — everyone from Google to Hertz — OR is a secret weapon. Gone are the days when executives’ instincts determined when a product should launch or how much inventory should fill store shelves. Now, tools like enterprise-scale simulation and risk-assessment software — along with a core team of number crunchers known as “quants” — are arguably as important to a business’ overall success as its most-trusted execs.

Why It Matters Now

The list of Fortune 500 companies getting into the OR game is expanding, says Mark Doherty, executive director of the Hanover, Md.-based Institute for Operations Research and Management Sciences. Complex, global organizations are constantly in need of better ways to manage their processes, resources, products, and people, he says. OR allows these companies to do exactly that and find a competitive advantage. “In the private sector, OR is the secret weapon that helps companies tackle complex problems in manufacturing, supply chain management, health care, and transportation,” he says. For example, Procter & Gamble doesn’t make any significant analyses on supply chain structure without input from the OR team, since improving the slightest of margins in a company of P&G’s size can generate huge dividends.Other sectors, too, are increasingly relying on analytics. “In government, OR helps the military create and evaluate strategies,” says Doherty. “It also helps the Department of Homeland Security develop models of terrorist threats. That’s why OR is increasingly referred to as the ‘science of better.’”

The Strong Points

One of the myths about OR is that it applies only to operational issues. But OR is a cross-functional discipline that can apply to anything from executive compensation and new product branding to inventory management and organizational design. Plus, thanks to exponentially more powerful computers and next-generation software, data gathering that used to take months can now be performed with the click of a button.

The Weak Spots

Off-the-shelf software for optimization, simulation, and other OR techniques often comes with the promise of solving any complex problem, but there is no one-size-fits-all solution. What these software packages lack is “company intelligence” — data that’s specific to the nature of a particular company’s problems and challenges, says Glenn Wegryn, one of P&G’s top data crunchers. Thus, companies like P&G must rely heavily on customized, project-specific tools developed in-house, as well as a cadre of data analysts to target particular problems.

Case Study

Every product at P&G requires a variety of materials obtained from hundreds of sources worldwide. Using OR techniques, Wegryn’s team analyzes which source is optimal for every product. “A lot of times, there are service and quality considerations,” he says. “We also measure whether a manufacturer really has the capability to deliver the materials at the quoted price.” For instance, retail clients of P&G spend $140 million per year on in-store displays for P&G brands in the United States alone, often buying the display from one vendor. By using OR to determine the best source via a Web interface, P&G now pockets nearly $67 million annually in cost savings and has slashed the order-and-delivery cycle for store displays from 20 weeks to eight.

Additional reporting by Andrew Hines and Jake Swearingen.

referensi:bnet.com