When Expertise Backfires

In 1958, as part of the Great Leap Forward, the Chinese government decided to eliminate a pest they thought was hindering agricultural productivity. Their target? The sparrow.

Research showed every sparrow consumed about 10 pounds of grain each year. By removing the sparrow from the system, Mao Zedong’s administration hoped to automatically increase the grain supply for humans.

So they launched a patriotic—and highly successful—campaign against sparrows. Millions of ordinary citizens were mobilized to kill the birds and within two years, the sparrow was nearly extinct in China.

Eliminating sparrows, however, turned out to have unintended consequences. Sparrows don’t just eat grain; they’re also the primary predator of locusts. With the sparrows gone, the locust population exploded. Swarms decimated the very crops the government had tried to protect, causing far more damage than the birds ever had.

According to a 2025 study, the anti-sparrow campaign alone accounted for a 20 percent drop in crop production, leading to the deaths of two million people.

The government actually chose an effective approach to solving complicated problems: they applied their expertise to develop a solution to control the system. So why did it go so drastically wrong?

The leaders failed to realize they weren’t dealing with a complicated problem. They were dealing with a complex one.

Complicated problems are difficult to solve, but they have a finite number of parts that interact with each other in predictable ways. With the right expertise, one can develop and apply a rule, process, or algorithm to find a good solution. Examples of complicated problems are fixing a car engine, solving a rubric’s cube, or navigating the tax code.

Complex problems, however, are a different animal altogether. Unknowable unknowns and hidden feedback loops interact to produce unpredictable consequences. Through experimentation, learning and judgement, outcomes can be influenced, but complex problems are never solved permanently. Examples include raising a child, predicting the weather, or investing in the stock market.

The best response to a complex problem is to “dance” with it. Start by probing, experimenting, learning. Then develop guiding principles, set conditions for success, and stay ready to adapt as necessary in order to influence outcomes.

Complicated and Complex problems are both be difficult to deal with. But they’re made even worse if you don’t first recognize what type of problem you’re facing and pick the proper approach. Here are a few questions to help you clarify your situation:

• Are there best practices that guarantee predictable results?

• Can an outside expert solve the problem without living in the context?

• Is the problem “alive” and reacting to your interventions?

• If you change one part of the system are ripple effects unclear?

If you answered yes to the first two, then your problem is complicated. Hire an expert, develop a plan, and focus on efficiency. If you answered yes to the second two, then the problem is complex. Assemble a diverse team, run small experiments, and focus on adaptability.

History is filled with well-intended leaders who solved the wrong problem brilliantly. Invest time early on to ensure you know what you’re dealing with, so you don’t inadvertently eliminate the sparrow that’s holding the whole system together.

For Reflection: Is your biggest challenge right now complicated or complex? Are you responding appropriately?