How to avoid the risk of oversimplification in complex problems?

To avoid oversimplification, the key isn't to make problems more complicated, but to ensure your "simplification" is of high quality. This might sound a bit convoluted, so let me explain with an analogy of building a house.

A Poor Simplification (Oversimplification): "I want to build a house. A house is just four walls and a roof, right?" If you follow this line of thinking, you might just nail some planks together and build a shed. What's the result? It sways in the wind, leaks in the rain, you freeze in winter, not to mention the lack of plumbing, electricity, and a proper foundation. This is oversimplification; in an effort to make the concept of "building a house" sound simple, you've discarded everything truly important.

A Good Simplification (First Principles): "I want to build a house. Let's go back to basics and ask: What is the fundamental purpose of a 'house'?" The answer is: To provide a safe, comfortable living space that offers shelter from the elements. Starting from this most fundamental need, you will naturally deduce:

• To be "safe," it requires a solid foundation and load-bearing structures.
• To "shelter from the elements," it needs high-quality walls and a waterproof roof.
• To be "comfortable," it requires consideration for insulation, ventilation, and lighting.
• To be "livable," it needs plumbing, electrical, and sewage systems.

You see, this approach is also a simplification; it breaks down the complex concept of a "house" into a series of fundamental, indispensable functional requirements. You aren't misled by "what other people's houses look like," but rather start from the essence of the problem to reconstruct a solution.

So, to avoid the risks of oversimplification, here are a few points from my personal experience:

1. Keep asking "Why?" like a child. For every part of a problem that you take for granted, ask "why?" multiple times. For example, if someone says, "Our product must have feature A; it's standard practice," you should ask: "Why is this standard practice? What fundamental problem does it solve? Does this fundamental problem still exist today? Is there a better way to solve it?" Many oversimplifications stem from our unthinking acceptance of certain "common sense" or "assumptions."

2. Break down the problem, but don't discard the essential parts. Deconstructing a problem is the first step, but the key is to identify which parts are "load-bearing walls" (core elements) and which are "decorations" (non-core elements). Oversimplification is treating load-bearing walls as decorations and discarding them. So, after deconstruction, take time to examine each small piece and determine its importance. An effective method is to ask yourself: "If this part were removed, would the entire system collapse? Or would the core functionality be affected?"

3. Look at the problem from different angles, ideally by talking to a "layperson." A complex problem is like a polyhedron. If you only look at it from one angle, you'll always see just one flat surface. For instance, if you're an engineer, you might simplify the problem into technical implementation. But if you talk to a salesperson, a customer service representative, or even an end-user who knows nothing about the technical aspects, they will tell you about entirely different facets they perceive. These "outsider" perspectives can often help you discover critical aspects that you might have "professionally" simplified away.

4. Start from first principles, recombine, and then validate on a small scale. Once you've identified a set of fundamental "building blocks" through questioning and deconstruction, try using these blocks to construct an entirely new solution. This solution might look completely different from existing ones. But don't rush to roll it out broadly; first, create a minimum viable prototype to validate it. For example, in the house-building analogy, you could first build a small model, spray it with water, and blow a fan at it to see if your structural design is truly waterproof and wind-resistant. This validation process can help you uncover blind spots that might exist in your simplification process.

In summary, the secret to avoiding oversimplification is not to reject simplification, but to engage in "deep simplification." It requires you to cut through superficial complexity, get straight to the essence of the problem, and then, starting from that solid core, reconstruct the solution step by step, with clear logic.