A decade ago, I embarked on a new hobby — one that many more people have taken up in the meantime. I became a beekeeper. At the same time, I became a bee observer. Like Sherlock Holmes (in His Last Bow), I spent many pensive nights and laborious days watching the little working gangs.

What I didn’t expect was to learn lessons about organizational strategy and behavior that would inform my work as a human capital consultant. Professionally, I help large businesses manage risk by focusing on how their recruiting, compensation, training, and other systems encourage people to behave. What I came to recognize was that beehives were organizations that naturally got things right. The honeybee colonies I was cultivating were structured for consistent long-term growth and the prevention of severe loss due to unpredictable environmental surprises. Bees are masters at risk management.

Take, for example, their approach toward the “too-big-to-fail” risk our financial sector famously took on. Honeybees have a failsafe preventive for that. It’s: “Don’t get too big.” Hives grow through successive divestures or spin-offs: They swarm. When a colony gets too large, it becomes operationally unwieldy and grossly inefficient and the hive splits. Eventually, risk is spread across many hives and revenue sources in contrast to relying on one big, vulnerable “super-hive” for sustenance.

Here’s another lesson by analogy: No queen bee is under pressure for quarterly pollen and nectar targets. The hive is only beholden to the long term. Indeed, beehives appear to underperform at times because they could collect more. But they are not designed to maximize current returns; they are designed to prevent cycles of feast and famine (a death sentence in the natural world). They concentrate their foraging on the most lucrative patches but keep an exploratory force in the field that will ensure future revenue sources when the current ones run dry. This exploratory force (call it an R&D expenditure) increases as conditions worsen.

Distributed decision-making is another honeybee strategy for mitigating risk. Individual bees make decisions based on local cues and information, making the beehive perhaps the original empowered organization. In contrast to stodgy centralized systems, bees are able to make high-quality, relatively quick choices through distributed authority because the colony has mechanisms in place that reinforce sound judgments and execution. The competence of the individuals, for example, is assured by a disciplined career development program. By the time bees are sent into the field, they are prepared—and, even then, novice foragers are frequently accompanied by veterans who show them how to efficiently and productively move among, and work, the flowers. Knowledge management is also essential. Bees have a great communication system by which the good incoming information is always overwhelming the bad and is on constant display for the bees to see. Thus, individual workers have access to an accurate, up-to-date depiction of the real world.

Risk is also tempered by diversity in a beehive. When making big decisions, bees use a process that is similar to the Delphi technique: They assemble multiple viable options that they present to other bees to vote on independently and iteratively until a quorum is reached. As the Marquis de Condorcet showed (in the collective wisdom proof), good, unbiased decisions are made if a solution space is well sampled and the final judgment is determined by independent decision-makers. One of the attributes that determines the range of options that bees ultimately consider is genetic diversity. The greater the diversity in the bees’ DNA, the more sensitive they are to different conditions and circumstances, and the more options the hive is able to gather. More diverse hives are better at everything and more productive than less diverse ones.

Finally, bees choose the mistakes they will make, and are careful to make the right ones. The future is as unknowable for them as it is for us. A share of failure is inevitable. Sometimes, however, if you know you might be wrong, you can decide how to be wrong. For example, it is energy- and resource-costly for bees to build comb, and they don’t want to manufacture it if they aren’t going to use it. At the same time, they don’t want to under-build and miss a life-saving opportunity to store honey. To strike the right balance between these potential errors, honeybees use a sliding rule (with respect to empty comb cells) that guides them toward the least bad mistake: “We will only over-build if conditions are good and nectar is flowing and we will only under-build if times are tough and nectar influx is marginal.” These errors are better than the alternatives. The bees consider the worst that can happen no matter how improbable and protect themselves against that eventuality.

Should we try to build these features more fully into human organizations? No analogy is perfect, but the logic is hard to argue with. Honeybees have institutionalized procedures that prevent catastrophic loss, and their record of accomplishment is stunning: more than 100 million years of productivity and growth. Note, too, that no one needs to regulate the hives to keep them from taking on irresponsible risk—behaviors like these keep them self-regulating.

Companies differ enough from hives that we’ll probably never be able to do without regulation. But managing for practical scale, long-term success, distributed decision-making, diversity, and least-worst outcomes may be the best hope for keeping organizations healthy. It is the wrong impulse to put a damper on all the risk-taking that produces value. By adopting the kinds of features that keep bees venturing productively, but never gambling catastrophically, businesses might avoid heavy-handed regulation, and everyone will be better served.