What businesses can learn from the fascinating natural world

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Ecosystems have evolved over thousands of years into very efficient and effective systems and network structures. Contrary to popular belief it is not survival of the fittest but rather very complex and collaborative relationships that ensure the growth and survival of species. One of my favourite examples is the coral reef. Coral is an animal and it secretes limestone. Were it not for coral’s ability to secrete limestone we would not have huge coral reef structures like the Great Barrier reef. But coral would not grow at the rate that it does were it not for an alliance that the coral has with an algae called Zooxanthellae. The algae lives inside the coral and being a plant photosynthesise giving off oxygen and sugars. The corol who’s outter shell protects the algae from being eaten, benefits from having its own food factory curtsey of the algae  (up to 90% of its food resources are supplied from this alliance) and grows at rates of 3-5 times faster than if it didn’t have this alliance structure. Which business wouldn’t benefit from an alliance that helps it grow at that rate? What is also interesting about the coral reef ecosystem is that the alliance between the coral and the algae has enabled coral to create an majestical platform around which an entire community of sea creatures live and thrive. If we were to metophorically speaking, imagine that a coral reef were a business that had created a platform around which a community could thrive and develop, would that remind you of any very successful new businesses models? Many of today’s fastest growing and most successful businesses are adopting this platform-community focused business model – Apple-iTunes, Facebook, Google are all mimicing the ecocystem structures seen in nature. Businesses are fast learning that the key to success is platform and community building.

Taking the concept of exploring nature to find business solutions, Peter Miller has written the excellent book Smart Swarms. Peter has looked at the complex relationships found in swarms, from ants to bees to birds and made exciting and valuable discoveries. You can read more below and I would encourage you to buy the book it makes for an excellent thought provoking read. Smart Swarms available at Amazon

Below is an excerpt taken from an Article Peter Miller wrote for British Airway’s High Life Business Magazine.

Psychologists have known for some time that we possess blind spots in our decision-making. When faced with uncertainty, we fall back on mental shortcuts that can get us into trouble. Among our many bad habits, we ignore information if it contradicts our beliefs. We cling to facts that have been disproved. We’re overconfident in our ability to make predictions. And we’re easily impressed by a vivid story or the most recent bit of trivia. The list goes on and on.

Consider the trap known as the “decoy effect”, which we fall into when we’re wrestling with two equally appealing options. Let’s say you’ve received two job offers: A, which is close to home and pays an average salary and B, which is 45 minutes away and pays considerably more. It’s a difficult choice, because you value both your time and your money. So you struggle with the decision. But if you’re given a third choice, C, which is close to home like A but pays even less, then your decision becomes easy. You still can’t make a rational choice between A and B, but it’s clear that A is a better job than C, the decoy. So you pick A and move on.

We can’t help such irrational behaviour, because that’s how our brains work, says psychologist Dan Ariely in his bestseller, Predictably Irrational.

“Humans rarely choose things in absolute terms,” he writes. “We don’t have an internal value meter that tells us how much things are worth. Rather, we focus on the relative advantage of one thing over another, and estimate value accordingly.”

To make his point, Ariely asked students at MIT in Boston to look at photographs of three other students and pick which one they’d rather go on a date with. Two were photos of undergraduates who’d been judged attractive by an earlier group — the Brad Pitt and George Clooney of MIT undergraduates. The third was a shot of either “Brad” or “George” that had been digitally retouched to make him less attractive. The results were decisive: the students picked the undistorted Brad when the decoy Brad was included and the undistorted George when the decoy George was included 75 per cent of the time.

“Everything is relative,” Ariely says, whether we’re choosing spouses or bicycles or our next vacation spot. “Like an airplane pilot landing in the dark, we want runway lights on either side of us, guiding us to the place where we can touch down our wheels.”

Marketers are skilful at exploiting this blind spot. In one famous example, Williams & Sonoma, the home furnishings retailer, added a second bread-making machine to its line that was almost 50 per cent more expensive than the £180 model already offered.

Although the company didn’t end up selling many of the higher-priced machines, sales of the less expensive product nearly doubled, since it now seemed affordable.

Humans aren’t the only ones who behave irrationally in the presence of a decoy. Hummingbirds are also easily influenced when choosing between equally appealing containers of sugar water. So are honeybees, jays and individual ants in similar circumstances. But ant colonies are different. They seem to be immune to irrational behaviour, as recent experiments have proved.

“Individual ants are prone to these errors, but when you put a bunch of them together in a colony, they’re not,” says Stephen Pratt, a biologist at Arizona State University who, with Susan Edwards of Princeton, collected 26 colonies of ants from the woods in central New Jersey.

The colonies belonged to the species Temnothorax curvispinosus, which lives in cavities such as hollow acorns. Because such shelters don’t last very long, these tiny ants are forced to move rather frequently and as a result they’re quite good at finding new sites. “They’re pretty choosy about where they live,” Pratt says. They prefer dark cavities with small entrance holes, presumably because such holes are easier to defend.

To test the ants’ decision-making abilities, Edwards and Pratt offered each colony two new nest sites: A, which was dark but had a large entrance hole, and B, which had a small entrance hole but a cavity that wasn’t dim enough. This was the same kind of choice as the job offers mentioned earlier, with each option possessing multiple attributes. The researchers then forced the colonies to choose between A and B by removing the top from their current nests, and waited to see how the ants would respond.

As Edwards and Pratt predicted, some colonies picked A and some picked B, but the ants as a whole showed no strong preference for either one. Faced with equally appealing choices, the colonies couldn’t distinguish a clear winner — which was the rational response. The researchers then added a decoy nest, D(A), that was as dark as A but had an even bigger entrance hole, making it less desirable than A.

If the ant colonies were like the MIT students selecting a date, they should now pick A, since A was clearly preferable to the decoy D(A).

But the colonies didn’t do that. They didn’t go for the irrational choice. The proportion of colonies that picked A didn’t increase, as it had with the MIT students.

Nor were the ant colonies swayed by the second decoy, D(B), which had a small entrance hole like B but was even brighter inside. If they had acted irrationally, more of them would have picked B, since it was now clearly superior to the decoy. But they didn’t do that either, even though that’s exactly what consumers do when picking a TV set, a toaster or a bottle of wine at a restaurant. What makes ant colonies different?

It has to do with the process they use to make decisions, Pratt says. Rather than relying upon individual ants to examine all three options, compare their relative merit, and then select the best one, as a group of people might do, the colonies divide up the decision-making duties, sending scouts to only one site each. If each scout judges her site to be acceptable, she returns to the colony and recruits another scout to visit the site. (I say ‘she’ because all ant workers are females). If the second scout approves of the site, she joins the first in recruiting two more ants, then four more, then eight more, in an exponential build-up of support.

Meanwhile, other ants are evaluating the remaining sites in a kind of race to see who can attract the most scouts to their site the fastest. The winning site becomes the colony’s choice.

By spreading out the decision-making among many scouts, in other words, “They’re actually avoiding the irrational behaviour that they would otherwise have made if they’d had to do the whole problem as individual ants,” Pratt says.

Such intelligent group behaviour is more common in nature than you might think. Ants and honeybees use swarm intelligence to find the best sources of food. Termites use it to build elaborate mounds filled with passageways to regulate the air and moisture inside. Shoals of fish use it to sense predators and alert individuals from one end of the group to the other. Herds of caribou use it to follow migration routes to distant calving grounds. Such behaviour also offers us intriguing models for our own problem-solving. If ants can do it, after all, why can’t we?

That was the question posed by managers at American Air Liquide in Houston not long ago. The company, a subsidiary of a £10bn-a-year group based in Paris, was searching for a way to manage its increasingly complex business. As a producer of industrial gases such as oxygen, nitrogen and argon, Air Liquide was dealing with fluctuating energy prices, uncertain customer demand, variable production costs and multiple delivery systems.

Although its managers had a wealth of data available to them from 100 or so plants, they were never sure what challenge the next day might bring. So a consulting group suggested they borrow a few ideas from ant colonies, which have evolved problem-solving techniques to cope with similarly complex environments. These techniques, translated into computer algorithms, were adapted to fit Air Liquide’s problems, helping managers there to optimise thousands of decisions a day and save the company millions of dollars a year.

Such original thinking comes at a good time, according to experts. In a recent survey of business executives, McKinsey Quarterly found that only about a fourth believed their companies are currently making good strategic decisions. Two thirds said their organisations are making bad decisions about as often as good ones. The rest said good decision-making is the exception rather than the rule.

“Our candid conversations with senior executives behind closed doors reveal a similar unease with the quality of decision-making and confirm the significant body of research indicating that cognitive biases affect the most important strategic decisions made by the smartest managers in the best companies,” write Dan Lovallo and Olivier Sibony.

One executive who takes such cognitive biases seriously is Ben Leedle, CEO of Healthways, a £450m-a-year company based in Nashville, Tennessee, that specialises in promoting healthy living among participants in corporate health plans, government employees and others.

When faced with strategic decisions such as acquisitions, investments or mergers, Leedle and his managers have adopted a novel process. “We wanted to get away from both the authoritative, top-down model and the loudest-or-most-persistent-voice model,” Leedle says. “So we asked ourselves, how do we let a lot of really smart people into our process of decision making? How do we pull in the ‘power of many’ versus the ‘brilliance of one’? And then how do we scale and cascade that through our organisation?”

Their solution was to split the decision-making duties into four roles: the decider, the recommender, the input gatherer and the vetoer. The decider ‘owns’ the decision. The recommender formulates the plan. The input gatherer organises relevant data. And the vetoer reviews the call. By establishing separate roles, Leedle says, he and his managers have better prepared themselves to address key questions, “such as, what are the risks with a decision? How do you size the risk? What are the economics of the decision? Who will be impacted by the decision, either directly or indirectly?” All those factors come into play.

Although their approach takes more time and effort than seat-of-the-pants decision-making, Leedle says, “It cuts through a lot of wasteful energy and ends up being less costly in the long run.”

As for Stephen Pratt’s ant colonies, the biologist says he’s hesitant to give advice to people who run human organisations. “But if I had to suggest a single broad lesson, I’d say that if you structure the decision-making of your group so that everything is riding on one or two overstressed individuals, you may be demanding more than they can reasonably provide,” he says.

“When you do that, you’re making the limitations of these few individuals the limitations of the whole group. Whereas, if you cleverly divide the problem up so that no individual has to carry out a task so demanding it’s liable to fail, then the group as a whole can do better.” It works for ant colonies, he says. Maybe it will work for human organisations, too.

On the other hand, he adds, maybe the ants that took part in his experiments were no ordinary specimens. “We collected these colonies near Princeton where Einstein used to walk,” he says. “Maybe these were just really smart ants.”


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