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 THE STAT 26Percentage of wireless customers who use their cell phones to take picturesMore Vitals
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MAY 25, 2004
The New "Molecular Economy" Information systems will take their cues from biological ones, according to It's Alive. Here's Part 1 of an excerpt from the book It's Alive: The Coming Convergence of Information, Biology, and Business by Christopher Meyer and Stan Davis Chapter 1: Learning from Life Cycles The best way to predict the future is toEconomic Evolution Imagine that it's 1971 in Palo Alto, California. You've wandered into a building at the Stanford Industrial Park, a nondescript place with cinder-block walls and rented furniture. The 3180 Porter Drive site is as plain and drab as the surface of the moon, and the guys working here seem to be living in their own private universe, speaking their own unique language. Someone's nattering on about the new "Intel 4004." Apparently, this new gadget he's talking about is called a "microprocessor." Someone else seems to think it's really great that this thing contains 2,250 transistors. They're both worked up over the fact that this "microprocessor" has an entire "CPU" on a single "chip." As an average person living in 1971, you have no idea what they're talking about. In this ugly building on Porter Drive, also known as the Xerox Palo Alto Research Center (PARC), the computer wonks are also talking about "operating systems" and "laser printing" and "icons." Soon they will be going on about the "mouse," "point and click," and the "graphical user interface"; eventually, "bandwidth" and "network protocols." In the early seventies, these terms were arcane jargon, but the words and the concepts they represent are as familiar to us now as "assembly line" and "mass production" were then. That's because the computer scientists at places like Xerox PARC and Bell Labs were, in fact, inventing the future -- which is now our present -- building the new economic engine that would overtake the industrial economy of the preceding 150 years. "Computer speak" is the lingua franca of the world we inhabit at the beginning of the 21st century. Today, in commercial laboratories with names like Maxygen, Diversa, and Nanosys, it's happening again. A new generation of scientists is inventing the next new world with its own novel nomenclature. Their terms of art, phrases such as "combinatorial chemistry," "gene shuffling," "high-throughput screening," and "MEMS" sound just as arcane to the average person now as computer terminology did in 1971. But pay attention. In the same way that researchers at PARC and Fairchild Semiconductor and Bell Labs created technology that established a new economy based on information, scientists in labs today are inventing a future based on molecular technologies. These include not just biotechnology but nanotechnology and materials science as well. Cargill Dow Polymers is growing polymers for plastics in corn plants. PPG Industries is making nano-scale coatings that enable windows to wash themselves in the rain. Bio-Rad Laboratories is attaching naked strands of DNA to gold nanospheres and injecting them into people with a nano-BB gun.
At John Deere, for example, the art of breeding -- as in thoroughbreds and show dogs -- has been used to evolve a schedule for a highly complex factory that makes seed planters. Using a computer, the metal-benders create a few random schedules that express the sequence of planters to be built in a digital code made of zeros and ones. That code is a set of instructions, just as DNA carries a set of instructions, its "genetic code." Deere engineers evaluate each schedule with a simulator, which is like letting the horses grow up, and then racing them -- in silico. The winning sequences are then mixed, put out to stud in an approach that is essentially sex for software. Through this approach, which uses a "genetic algorithm," parts of the best schedules are recombined to create a new generation, just as horse genes are recombined, albeit through a somewhat messier process. Forty thousand new schedules run simulated races every night, and the winner is the schedule that runs tomorrow's real-life production derby on the John Deere factory floor. Genetic algorithms are already in widespread use, improving jet-engine designs, credit-scoring forms, and stock-trading rules. The bigger story than sex for software is the abstract principle that biological behavior -- in this case sex -- can be written into digital code, then applied to the most intractable business problems. Stay with us, and you'll see that this translation of a biological function into a computer process is only one of many ways in which the concepts of evolution apply to business, in this case through precisely measurable operations improvements. In 1984, a multidisciplinary group formed the Santa Fe Institute and began a research program based on a really big idea: that biology is not the only system that evolves, and that the concepts of evolution help to explain the process of change in any connected system, be it an ecology or an economy. Since then SFI has extended its work to other social systems -- a business, a tribe, a crowd, a stock market, or a political party. Their work (and similar work at the University of Michigan, IBM, and many other places) has created some early tools, and a point of view that lets us see the economy as an ecology, and an organization as an organism, at the level of rigor needed to do empirical science. That's the level at which you begin to use evolutionary concepts to schedule factories. These techniques, in time, may become as pervasive as the computerized spreadsheet is today. In fact, you can get started on your PC right now with a Microsoft Excel add-on called Evolver. The theory of evolution through selection goes back to Charles Darwin in 1859, though the practice goes back to hunters and gatherers and their dogs. In Darwin's time, scientists recognized that biological systems evolve without any conception of the future, and yet the systems' future paths are significantly affected by their past. The new wrinkle for business today is the computing power that enables us to cast forward to test different evolutionary paths. At a startup called Icosystem, for example, former Santa Fe Institute research fellow Eric Bonabeau uses genetic algorithms to breed strategies for Internet service providers (ISP), then simulates an industry of competing strategies to observe the evolutionary adaptation of each "species" of ISP. As these tools continue to develop, they will start to provide insight into the business problems currently reserved for senior strategists. A generation ago, the spreadsheet "deskilled" financial analysis, meaning that the most junior assistant in your company, equipped with the right software on a PC, could organize and manipulate data and enter the province of a once-highly specialized profession. In the years to come, new tools relying on the power of evolution can similarly "deskill" a wide range of activities, including strategy and planning. Today, the focus is on operations; the frontier, as at Icosystem, is strategy. Tomorrow, the boundary will move to organization, and managers will be able to test evolved organization designs and compensation systems to optimize the cultures that emerge.
BW MALL
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