Armed with an idea that he hoped would wow his audience, IBM mathematician Howard Sachar rose to make his sales pitch in a conference room packed with 30 of J.P. Morgan Chase’s top technology executives. “Chase’s future challenge is to appear as one bank to consumers,” Sachar told them. “It’s a future in which a Chase customer dials just one number, and the person on the other end knows everything about you.”
Far from being a simple customer-service strategy, Sachar explained, the “one bank” idea actually creates a complex technological puzzle that can include everything from moving the bank’s phone system online to overhauling its call centers with more-powerful computers.
But instead of offering up a menu of existing IBM technologies for Chase to choose from, Sachar unveiled his secret weapon. It was one that he believed Chase wouldn’t find at the other companies bidding on its big technology outsourcing deal. “We can give you direct, intimate access to IBM’s gray cells,” Sachar said. That’s what he likes to call the nearly 3,000 researchers, including 2,000 PhDs and 6 Nobel laureates, who spend much of their time thinking about the future.
If Chase executives picked IBM, Sachar explained, they’d get to see that future and the technologies it inspired before their competition does. Moreover, Chase could even help shape that future by throwing its tough problems at those IBM researchers who work on challenges such as the one-bank strategy, thorny issues that have made modern banking as much a tech business as a money business.
Eighteen months after that first meeting, Sachar found out just how memorable his pitch was. On December 30, 2002, Chase signed a $5 billion multiyear contract with IBM to run its technology infrastructure. It had been a close race with EDS, says Michael Sztejnberg, Chase’s managing director of enterprise technology services. But Chase chose IBM in part because “we were attracted to the ability to get an early view into the research that could hold promise for our business,” he says. The final contract even included a new role for Sachar at Chase’s New York headquarters. Though still at IBM, he heads the bank’s technology futurist group, made up of IBM scientists and Chase executives. “Now my full-time job is brainstorming about the future,” he says.
Over the past two years, IBM has increasingly been using its gray cells to sell, pulling its scientists out of their research labs and sending them on client calls. As the company shifts its emphasis from making mainframes to providing complex technology services, it wants those scientists to focus less on products and more on understanding and meeting customer needs. Although IBM has a long tradition of tapping researchers to solve real-world problems, the company now has its first formal organization designed to do so. On Demand Innovation Services, a year-old unit at IBM’s Thomas J. Watson research center in Hawthorne, New York, pairs scientists with sales and marketing people in IBM’s consulting services. The effort has paid off in contracts big and small, the company says. And the contact with customers has also energized some of Big Blue’s big brains, inspiring them to come up with ideas they say they never would have thought of sitting back in their labs.
Of course, packing scientists off to meet with top executives at important prospective clients comes with some risks. First, there’s the simple issue of wardrobe. Jeans and tennis shoes are the uniform of choice for most researchers. IBM doesn’t offer any formal dress-for-success counseling, but the scientists have learned to ask how formal a meeting will be and mimic the plumage of their business-side counterparts.
Tougher than a wardrobe makeover is softening the scientists’ sometimes-intense personalities. “Scientists have a habit of telling the truth,” says Jarir K. Chaar, who is director of IBM services research and holds a PhD in computer science and engineering. “We have these consciences that make us want to get to the heart of a problem, even if it’s tough for a customer to hear.”
Baruch Schieber, an IBM researcher with a doctorate in computer science, says he’s learned to temper his style. “I used to believe that you could solve everything using math,” he says. In his early meetings with clients, he would use equations to show how he could solve their tough business problems. “Over the years, I have become much more humble. Clearly, not everything is so black and white.”
While he now reins in the desire to plug everything into an equation (including the raising of his own children, a habit that he says does not amuse his wife), he still believes math plays an important role in solving the challenges that keep executives up at night.
Consider the case of Boston Coach. The car-service company (owned by Fidelity Investments’ venture-capital unit) wanted to install wireless technology in the cars of its 900 drivers to help improve scheduling. But to maintain its on-time guarantee, Schieber says, Boston Coach was very conservative in the number of reservations that it took. “I suggested that they had a bigger problem than technology,” he says. “They had a big math problem staring them in the face.”
That math problem? An old brainteaser known as the “traveling salesman,” which involves determining the best route for a salesperson to take in order to make the most calls in a certain period of time. Boston Coach’s complex version of the problem was the perfect mind-cramping poser for Schieber. He figured that with the wireless technology IBM was installing in the company’s dispatch centers, there would be gigabytes of data coming in that could be used to create a better schedule for drivers every few minutes, if necessary. Moreover, Schieber believed he could build a system that would allow drivers to pick up more customers in a day, increasing Boston Coach’s sales volume but still meeting the on-time guarantee that was the company’s core strategy.
Hazary Arjune, Boston Coach’s chief information officer, says the idea of applying something as abstract as math to a real-world problem that had frustrated the company for years was met with some trepidation. “We know our business; we know limousines,” he says. “Our dispatchers carry all this knowledge in their heads.”
Schieber, curbing his desire to show off how quickly math could solve the problem, hung out in fleet operations at company headquarters just north of Boston, asking questions and getting to know what the dispatchers knew. Then he built a computerized dispatch system called “fleet optimization,” which created schedules that took almost everything into account, including marrying a driver’s personal schedule with the company’s needs. “You have these stereotypes of scientists–that they are propeller heads or that they can’t be let out of the research labs,” Arjune says. “But then you meet people like Baruch.” What started as a technology sale turned into a far bigger project, including installing Schieber’s optimizer in Boston Coach’s nine offices around the country.
The IBM scientists who’ve worked with customers seem to find the experience invigorating, too. “For many of our researchers, there’s nothing better than validating their ideas in the real world,” says Peggy Kennelly, vice president of IBM’s On Demand Innovation Services. Schieber knows that feeling firsthand. “You have such a sense of power when it only takes you a few minutes using math to solve a problem that a businessperson has been struggling with for years,” he says.
Fara Warner (firstname.lastname@example.org) is a Fast Company contributing writer.