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Do organizations do better when they have a central leader who calls the shots or a decentralized group of individuals who sort out their own division of labor?

The question has intrigued philosophers, biologists, political scientists and business leaders for centuries.��

A new honeybee-inspired study, , offers answers. It suggests that while both kinds of organizations can survive and thrive, leaderless groups may have an edge—as long as communication is good and there’s just the right mix of risk-takers and cautious followers.

“We found that decentralized strategies of decision making are at least as good as centrally coordinated ones and, in many ways, may be more robust and resilient,” said corresponding author Zachary Kilpatrick, a professor of applied mathematics who studies how animals, including insects and humans, make decisions.

Using math to understand decision making

Peek at a bee colony and you’ll find tens of thousands of individuals toiling away, each with their own unique role in supporting the hive. Some explore surrounding meadows, foraging for nectar and pollen and scouting for information to bring back to the group. Others hang back, cleaning the hive and feeding the larvae. While the queen lays eggs and chemically signals her presence, she doesn’t determine who does what.��

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Elephant troops follow the lead of the matriarch while baboons and schools of fish tend to collectively decide which way to move. Credit: Adobe Stock photos

Ants and termites operate similarly, without a central authority.

Other animals are more hierarchical.

In a herd of elephants, the oldest female makes the call on where to find water and when to flee, when survival is at stake. Wolf breeding pairs direct where the group hunts and rests.��

Wild baboons are a mix of hierarchy and egalitarianism, living in ranked groups but deciding democratically where to go when it’s time to move.��

To get at which system works best under what circumstances, and how leaderless societies manage to accomplish so much, Kilpatrick and his colleagues—Hyunjoong Kim of the University of Cincinnati and Krešimir Josić of the University of Houston—developed a mathematical model informed by research on real animals in the wild.

The model simulated life in a bee colony under different scenarios with varying numbers of bees; good and bad environmental conditions; and a central coordinator vs no central coordinator.

Surprisingly, the study found no difference in outcome between scenarios where a central coordinator determined who does what and scenarios where individuals acted based on their own risk tolerance.��

“Turns out those models behave identically,” said Kilpatrick.��

And in some ways, the leaderless group was more resilient, the model suggested.

“If one individual is making the decisions for an entire group, and that individual dies, gets removed or can’t communicate with the group it leaves it really vulnerable,” Kilpatrick said. “In a decentralized group if you knock out one communication pathway, there are others.”

Another question at the core of the experiment, and in day-to-day life in a hive: How many risk-takers, or scouts, should be sent out to forage and how many should cautiously wait?��

The study found that the larger the group, the smaller the proportion of risk-takers it required. That’s because each brave bee that puts its life on the line to leave the hive adds proportionally less new information to the colony upon return.

“If you send too many foragers out, you’re going to waste a bunch of energy for little additional benefit,” he said. “The same scaling logic may hold for human groups, where a small team may need half its members exploring while a large field needs only a handful.”

Notably, the study found that the more challenging the situation, in terms of weather and resources, the more critical it was for this division of labor to be dialed in.

Zachary Kilpatrick

Lessons for humans

Kilpatrick said the findings could help inform development of artificial neural networks (computing systems modeled after the human brain) and multi-agent systems (think drone swarms working collectively toward a common goal).��

“One of the best ways to design efficient systems and technologies is to look at what nature has done.”��

But the study also yields other lessons for humans.

Research has shown that our ancestral default, from living in small hunter-gatherer bands, is to make decisions collectively. Some small organizations, like kibbutzim or co-ops, still do this. But as organizations grow larger, humans tend to build centralized hierarchies and install powerful leaders to control them.

“That flexibility is one of our most distinctive traits as a species,” Kilpatrick said.

Yet much human advancement can be attributed to moments when, without direction from above, risk-taking individuals break out to make scientific discoveries, launch startups, explore new territories or create avant-garde art—nudging the more cautious to follow them when the time is right.��

As new, more complex challenges arise, humans might want to take a cue from the bees, said Kilpatrick.

“Our research suggests that there can be a real benefit to having decentralized, individuated exploration that ultimately gets shared back with the community.”��