Only a few years ago, physicist Greg Blonder was probing subatomic particles for the key to superconductivity. Chemist Amy Muller was researching a newly discovered class of carbon. And biologist David Isenberg was hard at work trying to figure out the human brain represents the sounds of human speech.
Today, physicist, chemist, and biologist have reinvented themselves as corporate strategists, bringing the scientific method to the gauzy task of anticipating the future. At AT&T’s Customer Expectations Research Lab, located in a bright, airy corner of the old Bell Laboratories building in Murray Hill, NJ, a group of 40 PhDs turned marketers search for fundamental truths about the way people adapt to new technologies. Blonder is the resident futurist-in-chief, guiding the mix of physical scientists, computer experts, engineers, psychologists, mathematicians, and MBAs; Muller heads up the Opportunity Discovery Department — ODD, for short — where Isenberg also works.
“Obviously, what we’re doing doesn’t quite rise to the level of Newton’s first law,” says Blonder. “But it’s also a lot more fundamental than conducting focus groups to figure out which breakfast cereal will be popular next year. We have to begin to understand human beings as well as we understand atoms.”
Like the people who work there, the lab itself is a hybrid, a crossroads of change. In part, its existence testifies to AT&T’s recognition that the company must change — too often in the past, its approach to science has left it “fumbling the future,” failing to take commercial advantage of a number of its homegrown innovations, from cellular technology to C++ computer language. Its existence also demonstrates a shift in AT&T’s understanding of science — that the game has changed from technology to the way people use technology.
AT&T has allocated 10% of its research budget to the lab — from Blonder’s view that’s a “10% bet” that the legions of scientific researchers employed by AT&T are researching the right thing. (The Bell Labs name, along with two-thirds of its researchers, were transferred this year when Lucent Technologies spun out of AT&T.) At 41, Blonder is a natural for his new job. After graduating from Harvard with a degree in physics, he joined Bell Labs in 1982. As the company’s focus shifted away from the physical sciences, Blonder found himself playing the role of mediator between the company’s researchers and executives who had come to view each other with increasing suspicion.
Consider, he says, that when the typewriter was first introduced, most people recoiled at the idea of communicating in a medium that seemed to offer no insight into the writer’s style or personality. Years later, when the answering machine came along, people dismissed it as cold and impolite. In time, both products were able to overcome people’s reservations — largely, argues Blonder, because they satisfied basic human needs more compelling than the obvious ones of speed and utility.
The typewritten letter came to assign a special importance to a subject that a handwritten note could not. And for many consumers, the answering machine satisfied a latent desire that people had to screen their calls and protect their privacy.
By the same logic, Blonder and his colleagues expect Caller ID — the service that gives your telephone the technology to identify the caller at the other end of the line — to become an integral part of everyday communications. Blonder sees a commercial bonanza for the company that comes up with a technology to use caller ID to screen out calls from the pesky job applicants while sending through important messages from home.
Social context is only one of the tests Blonder, Muller, and Isenberg apply to help determine whether and how quickly people will adapt to new technologies. “Observability” and “tryability” are two other factors. One reason new models of athletic shoes catch on quickly, Blonder says, is that everyone can see them on the street. In contrast, things like computer memories are difficult to market because people tend to use them in private.
While Blonder looks at history, Muller is applying anthropology. She’s sent pairs of researchers to dozens of sites — including a bank in San Paulo, a charter school in Minneapolis, an engineering firm in San Francisco — to see how the Net is changing the way people work. The aim is to identify chokepoints where information backs up or holes where it leaks out. Are there places where people have created low-tech paths around technological obstacles or where informal networks have sprung up and subtly altered the protocols and hierarchies within the enterprise? From these disjointed observations, Muller and her team hope to match the changing nature of work with new products designed to support it.
Isenberg’s role is more that of the conventional strategist, using scenario planning to generate alternative views of the future. He describes it as a search for those areas of “critical uncertainty” facing the company. In AT&T’s case, uncertainty might involve a major shift in regulations, the arrival of a new set of competitors, a restructuring of capital markets, or an unanticipated technology breakthrough, like a technique for achieving video compression at 10 times the present rate. Other scenarios are built around social changes, like a dramatic jump in the numbers of telecommuters.
All this is pretty new and controversial stuff for an industrial research lab that once saw its mission as extending the frontiers of basic science. And it’s still not clear, even to those who are predicting the future, what the future of the Customer Expectations Lab will be.
“I’d say we’re still in the process of developing credibility,” Blonder says. Isenberg acknowledges that it’s still early in the Lab’s development: They have yet to figure out how to disseminate the Lab’s findings or apply them to particular lines of business.
“We’re on the edge of being unconventional, so we have to find more indirect ways of insinuating ourselves into the process,” says Muller. “We can’t just go around the building here and say we’re really smart and we can help you. We tried that. It doesn’t work.”
Steven Pearlstein (email@example.com) is a business and economics reporter for “The Washington Post.”