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Why has the world economy grown so explosively in the past 100 years? And why has it simultaneously become so complex? To answer these questions, you must look beyond traditional economic theory, says Eric Beinhocker, senior fellow at the McKinsey Global Institute and author of The Origin of Wealth. Only by regarding the world economy as a "complex adaptive system" - similar in structure to the brain, the Internet or an ecosystem - can you understand how wealth is created, and how your organisation can create more of it.

It's an idea that seems too abstract to be useful. Since when did high-concept economics have practical ramifications for business? This was the chief thought going through the heads of around 60 members of the London Business Forum, as they gathered to hear Beinhocker speak at the New Players Theatre near Charing Cross Station. Yet during the event they received plenty of advice that could make an immediate difference to their organisations. And they heard so many surprising facts about the economy that their perspective on its was sure to be changed irrevocably.

For example, Beinhocker began the event with a brief history of economics that covered the past 2.5 million years. He did this by citing the research of Professor J. Bradford DeLong at the University of California, Berkeley, who has shown that most of the wealth in the world has been created in the last century. The economy, as DeLong defines it, has been in existence since man created the first stone tools - or "products", if you will - to make life easier. "Basically the story of the human economy is that for a long, long, long time we were really, really, really poor, and then all hell broke loose," Beinhocker said.

He added that the complexity of the economy has also grown explosively over the past century. Anthropologists working with today's most remote tribes know that the average hunter-gatherer community has access to about 102 products and services, including clay pots, hunting bows and so on. By contrast, Beinhocker calculated, a modern city such as London or New York has access to about 1010 products and services. "It's hard to get a feeling for just how huge a number that is, but I'll give you one relative measure: there's 106 species on the planet," he said. "So the human economy, mostly in the last 100 years, has created more variety, more complexity than the entire ecosystem of the Earth."

The other amazing thing about today's world economy, he suggested, is that no one's in charge. "We like to think our political leaders run the economy in some way and are responsible for creating jobs... [but] the reality is no one runs any of this; they might have some influence on patches of it, but the economy is a self-organised, bottom-up system."

Traditional economic theory can't explain such things because it makes the fundamental assumption that the economy is an equilibrium system, Beinhocker said. "If you drop a ball into a bowl it will eventually come to rest in equilibrium at the bottom and it won't move until some other force disturbs it," he explained. "And economics views the economy in the same way: that supply and demand and other forces drive the economy towards a resting point and unless some kind of outside shock - such as a technology change or a change in consumer tastes or political events - moves it, the economy should in theory [become static]." The problem is that "equilibrium systems don't grow explosively, they don't create novelty and they don't just spontaneously self-organise and create order."

The economy is in fact a "complex adaptive system", Beinhocker argued. "In these types of systems the parts or particles - or 'agents,' in the lingo - adapt and change their behaviour over time. They respond to signals in their environment and they evolve." He added: "All the interactions and interacting behaviour of these agents at a micro level then create larger-scale, macro patterns in the system." In other words, the economy is just as dependent on the laws of evolution as the natural world.

"Modern science actually views evolution as... an algorithm," he continued, "a generic process that can be used to describe any number of systems. In fact, we can think of evolution as a search algorithm; it's a way of finding fit designs." This endlessly repeating process ensures fit designs are scaled-up or "amplified", while unfit designs attract fewer resources and eventually become extinct. "The industrial revolution is in some ways the 'Cambrian Explosion' of the economy," he suggested. Consider the modern bicycle: it didn't appear from nowhere but from endless iterations on a basic design conceived in the 19th century.

Beinhocker argued that all innovation is the result of deductive tinkering, whether this tinkering takes the form of mental iteration or physical prototyping. "To get to [the modern bicycle] there was a whole lot of 'Try stuff, see what works, pick the best one, make more of it.' In short, an evolutionary process," he said. "In unpredictable systems, this deductive tinkering process is really the only way you can search the space of possibilities effectively for fit designs."

He also distinguished between physical technologies, such as bicycles, and social technologies (ways of organising people), such as Henry Ford's assembly line. Business plans, he said, are ways to "stitch together" these two types of technologies. "We can think of business plans as a kind of fit design for a business," he says. They are in turn subject to evolutionary forces at three levels: the individual, as we mentally consider multiple options and discard those we consider to be weak; the organisational, as we try to sell our preferred ideas to colleagues and thereby win resources; and the market, as we try to attract customers and investors.

As a thought exercise, Beinhocker encouraged the LBF audience to consider how it might improve the design of the Galapagos finch, one of the bird species studied by Darwin. "Would we make the beak longer? Would we give it more powerful wings? Would we change its digestive systems so it could eat different foods?" In order to make such decisions, we'd need to tick off a "pretty daunting list" of research areas, he suggested. "We'd have to know every food this thing eats, we'd have to know what the future evolution of all of its food sources would be, we'd have to know everything we could about it's competitors and habitats. We'd also have to understand the inside view of the finch pretty well so that if we changed a wing design then we wouldn't have it crash onto the ground or something."

There is, of course, no hope that we could ever gather such knowledge, "but in business we're all arrogant enough to think we can actually do this," he pointed out. Most companies are in fact anti-evolutionary. For example, he suggested, they are not creative enough: "Everyone's got their heads in one business model, one mental model, and it's very hard to break out of that, and create variety," he said, "And for evolution to work it needs what biologists call super-fecundity, more variety than the system knows what to do with." In most companies, he added, it is "very difficult to move resources around and scale up ideas that are good."

So how do we make our companies more adaptive? "We need to conduct what I call strategy by experiment," Beinhocker concluded. "Rather than trying to predict the future in our strategic planning processes we should experiment our way to the future; we should have portfolios of initiatives, of ideas, some of which may be contradictory." To support this view he pointed out that Bill Gates, while trying to make Windows the predominant PC operating system worldwide, was also investing heavily in Unix and several other competing technologies, in order to hedge his bets.

Other key measures that Beinhocker recommended included:

• scaling up things that are working while scaling down things that are not, with greater speed and Darwinian ruthlessness than has previously been the case;
• greater diversity of "mental models" - "We need people who didn't all grow up as engineers or accountants or marketing people, or whatever the dominant mental model is in your company;"
• better metrics and information from the marketplace to better-inform innovation investment decisions;
• "a culture of challenge" in the innovation selection process that "fights against the politics that are at work in most organisations, [to] trump whoever's most powerful, whoever's running the biggest business unit and so on;" and
• greater flexibility to move resources around "so we can scale up the stuff that's working and also - very, very hard - kill off the stuff that's not."