We are all prone to self-deception. This is perhaps the most difficult, and most human, obstacle to successful product development. When you’ve poured your nights and weekends into an idea, you fall in love with it. You become emotionally invested. And that emotional investment is exactly what Victor Lombardi warns against in Why We Fail, because it breeds bias—the silent killer of objectivity.
Bias allows product teams to ignore evidence, dismiss negative feedback, and ultimately, build products that only they, the creators, truly love. The only reliable weapon against this universal human flaw is the unflinching, cold logic of the Scientific Method.
The Ego Traps That Sink Products
To understand the solution, you must first recognize the problem. Here are two common biases that allow us to rationalize failure:
- Confirmation Bias: This is the tendency to seek out, interpret, and favor information that confirms or supports our prior beliefs or values. If you believe your new feature is revolutionary, you will latch onto the single positive tweet while conveniently dismissing the 20 negative ones. You see what you want to see, not what is actually there.
- The IKEA Effect: Studies show that when we assemble something ourselves, we irrationally overvalue it. This applies directly to product teams. Because you spent months building that complicated interface, you believe it must be valuable, even when users are clearly abandoning it in droves. Your ego and your labor are clouding your judgment.
These psychological traps create a dangerous bubble of “Groupthink.” Everyone on the team confirms everyone else’s flawed positive assessment, and the truth—that the experience is terrible—is politely ignored until it’s too late.
The Scientific Method: Your Shield Against Bias
Lombardi advocates for injecting the scientific process directly into the heart of experience design. The goal is simple: to generate verifiable, objective data that is impossible to deny.
This is how you apply the method to your product:
Step 1: Form a Falsifiable Hypothesis You must move past vague goals (“We want more users”) and form a precise, testable hypothesis that can be proven wrong. For example: “We hypothesize that changing the checkout button from ‘Proceed’ to ‘Finish Purchase’ will increase our conversion rate by 5%.” The key word is falsifiable. If the conversion rate doesn’t increase by 5% (or, worse, decreases), your hypothesis is false, and you must accept that fact.
Step 2: Execute Controlled, Rigorous Testing You must rely on methods that eliminate bias and provide clean data. This means using A/B testing (showing version A to half your users and version B to the other half), controlled user interviews, and large-scale metrics tracking. The test must be designed so that only one variable changes (A vs. B) to isolate the cause and effect. You are performing an experiment, not a demonstration.
Step 3: Confront and Accept the Data This is the hardest, but most vital, step. When the data comes back—and it often contradicts your dearest beliefs—you must accept the outcome without qualification.
- If your new feature, which took six weeks to build, shows a 20% drop in user engagement, you must admit it was a failure and pivot.
- If your test shows a simpler, less elegant solution performs better than your complex, beautiful design, you must choose the simpler solution.
The Scientific Method forces you to check your ego at the door. It makes your product development data-driven rather than ego-driven. The numbers don’t care about how hard you worked or how clever you thought your idea was. They only reflect what the customer actually did.
By adopting this mindset, you don’t just avoid catastrophic failure; you ensure continuous, incremental success. You are constantly testing, failing quickly, learning faster, and building a product that is perfectly tailored to the verifiable reality of the user, rather than the hopeful delusion of the designer. This commitment to truth—however painful—is the secret to designing experiences that truly work.