Nature’s Bottom Line

Anyone who pays at least cursory attention to the financial markets has surely divined what stock analysts share with meteorologists, evolutionary biologists, astrologers and, heaven knows, political pundits: no one can say with certainty that he has any idea what will happen tomorrow.

That’s a big problem, whether you’re managing astronomical sums of other people’s money or just deciding what to pack for London. It might seem another problem altogether to spend your time reconstructing that fateful period 3.5 billion years ago, when protein molecules dancing through the earth’s primordial foam collectively spit forth the first proto-bacteria, life’s earliest ancestors. You know the rest.

But for Stuart Kauffman–philosopher, medical doctor, evolutionary biologist and entrepreneur–all these problems underscore a single phenomenon: complex, self-organizing systems continuously adapt to and change with their environments but do so in ways that are impossible to predict. It’s a head scratcher. In a universe damned by entropy to gradual dissolution, things sure seem pretty well put together. So, how is it that evolving systems as diverse as the biosphere, your immune system or the global economy have grown from nothing into organizations of imponderable complexity?

That is the question that Kauffman and other theorists have struggled for many years to answer, and their ideas are finally seeping into the business mainstream. “The machine metaphor dominated how we thought about businesses in the Industrial Age,” Kauffman says. But now “the biological metaphor–thinking of firms as an ecosystem–is making its way into the business world.”

In 1996 Kauffman founded Bios Group, a partnership with Ernst & Young designed to apply complexity science to Big Business. In five years, it has completed more than 50 projects for FORTUNE 500 companies, solving thorny problems of supply-chain management for Procter & Gamble (How do you get the soap from factory to home with optimum results for P&G, its retailers, and consumers?), decimalization for NASDAQ and crowd control for Disneyland (How do you avoid long lines at rides?).

Complexity theory was born in 1984, when brainiacs from the Los Alamos National Laboratory founded the Santa Fe Institute. The SFI remains a cauldron of Ph.D. sorcery, where physicists and biologists consort with psychologists and anthropologists, all in pursuit of the patterns that underlie the adaptive systems around us. “The bigger story,” says Susan Ballati, SFI’s director, “is not about Bios Group or SFI or other offshoots; rather, it is how a complex adaptive-systems approach to looking at the world is really what will be driving policy, business, education and research in the 21st century.”

Roughly defined, a complex system is an organization of individual “agents” in which each acts on his own behalf but collectively they build a network capable of reacting to changes in the system’s environment (for instance, the stock market, where you might have lost money yesterday because thousands of individuals, acting independently and spontaneously, sold a stock you also own). Agents may be actual critters–ants are a favorite for scientists–DNA molecules or the units that make up a company’s supply chain.

Take ants. Individual ants set out randomly to find the closest food source, each emitting pheromones to mark its trail. Other ants sniff out the pheromones, follow them to the food and all the while leave additional markers for their colleagues. More pheromones mean more traffic and thus a better route. In this way, ants, each working alone, collectively build the most efficient routes. Stealing a page from the ants, scientists followed one another’s pheromones toward the development of, among other tools, “agent-based modeling” software, programs that simulate individuals’ reactions to everything from grocery displays to guerrilla warfare.

With the advent of microprocessors in the ’80s, complexity took off because programmers could do such things as pour in and manipulate an unlimited number of variables in agents’ behavior. “This is a mathematical approach to behavior,” says Chris Meyer of Cap Gemini Ernst & Young, who first approached Kauffman with the idea to start Bios. “We have here the beginning of a science that would make ‘social science’ no longer an oxymoron.”

Unlike traditional engineering thought, complexity acknowledges that the whole of a system surpasses the sum of its parts, that agents’ interactions cause developments that are not accountable by analyzing individual components. The trick will be to harness this interaction.

Ford Motors contacted Bios last May, seeking a new way to determine what features its trucks should have, and in what quantity to produce them. Given all the possible combinations of options and models, Ford theoretically could build a unique truck for nearly every man, woman and child on the planet. Bios programmed software to represent the needs and tastes of consumers and set them truck hunting in a simulated market designed to maximize revenue to Ford, revenue to dealerships and satisfaction to customers. Ford, sufficiently impressed, became an investor in Bios in September.

Another commonly used complexity tool has brought more sex into the workplace–sort of. Genetic algorithms take advantage of the notion that, as Meyer puts it, “code is code,” be it your parents’ DNA or the zeroes and ones of the digital age. The birds and the bees have survived all these years because splitting and recombining their genetic code–sexual reproduction–creates novelty and, with it, adaptability. Similarly, Scotland’s United Distillers and Vintners uses software that “breeds” schedules for moving around the company’s 7 million casks of whiskey–a “survival of the fittest” for distribution bottlenecks. It’s the economic equivalent of a successful evolutionary adaptation.

The complexity community itself is clearing new paths by uniting the most disparate parts of our experience. Kauffman does so himself. When Boeing sought help speeding up its airplane design-and-construction process, he instinctively reached for a $23.94 Lego set. By setting scientific creativity to work on Big Business’s problems, there’s just no telling–quite literally–what will emerge next.