The Hypothesis Trap: Why do We continue to ask the Wrong questions?
The most significant flaw in decision-making is not the data, but the hypothesis itself. The mistakes that businesses, investors, and policymakers make before they even get started
Photo by Mike Cho On Unsplash
The Wrong inquiry Can lead to the termination of a business
Netflix placed a $1 million wager on the company in 2009.
It launched the “ Netflix Prize , ” a competition to build a better recommendation algorithm The predicament? Elevate the current system’s precision by at least 10% Three years After breaking the code, a team of data scientists from around the world finally succeeded in finding it
The winning algorithm was never employed by Netflix
Why?
As a result of the incorrect questioning they made
The genuine issue was not enhancing precision by 10% The reason for people clicking on a movie but not watching it was comprehended. For what reason did they abandon the films in their midway point?. It is worth noting that recommendations based on past behavior were not always indicative of future choices
Netflix tested out a theory. However, it was not the most important factor
They are not the only ones who are impacted by this
Every Hypothesis Has a Hidden Hazard
The first step in any significant business decision is to establish a hypothesis
What if the problem isn’t in testing but in framing?
Take Quibi, the $1.75 billion streaming disaster. It was founded on a single conviction:: The demand for mobile-friendly, high-quality short video content was due to a popular demand Proving this was the foundation of every trial, marketing approach, and expenditure
The genuine concern was not about the demand for brief videos. It was The question of whether they would be willing to pay for them when YouTube and TikTok became free
They were too late when they realized they had made a mistake
The Conjecture that Stumps Up Wall Street
Markets run on assumptions
LTCM, the hedge fund that almost caused the collapse of the global financial system in 1998, is worth mentioning. Established by economists who won the Nobel Prize, it relied on a central concept: that Markets are logical, and price fluctuations always correct themselves
It worked perfectly for four years. In 1998, Russia defaulted on its debt. The panic set at inch did not demonstrate logical behavior. LTCM’s trades, which were built on mathematical calculations and assumed normal market conditions, fell apart
Within weeks, the fund experienced a $4 loss. 6 billion. The Federal Reserve was compelled to intervene to prevent the spread of disease
The models they used were not mistaken. Their hypothesis was
The risky lure of Confirmation Bias
What is the reason behind intelligent individuals falling into this trap?
We evaluate our own beliefs rather than relying on what we need to educate ourselves
It’s called Confirmation bias The inclination to search for evidence that supports our current beliefs while disregarding disparaging data. Millions of dollars are given to unsuccessful business ideas due to this. Unprofitable startups argue that they require an additional pivot to achieve profitability. Politicians tend to overlook the weaknesses of their policies when they attempt to make changes
Look at Theranos. Elizabeth Holmes’ blood-testing startup was backed by investors who gave $700 million, despite the company’s evident scientific shortcomings. The idea that a single drop of blood could pass through numerous tests was never seriously challenged
It had become one of the most significant deceptions in Silicon Valley history by the time the truth was revealed
What is the method to validate a hypothesis?
The key to successful hypothesis testing isn’t relying on proof alone. The objective is to determine if you’re mistaken before it becomes too late
How can one steer clear of the trap?
1. Reverse the Law of Evidence:
Instead of asking, “ How can we provide evidence to confirm this is accurate? ” ask, “ In what ways could we falsify our assumptions? ”
Amazon does this ruthlessly. Every major initiative undergoes a ” Premortem ” —executives imagine it has failed and then work backward to identify why. If they can’t find a good reason, they proceed. If they can, they rethink
It’s the opposite of traditional hypothesis testing. And it works
2. Test the Most Dangerous Assumption First
In 2012, Airbnb was still struggling. Its hypothesis: that People would rent homes from strangers online
Instead of building more features, they ran a simple Test. They hired professional photographers to take better listing photos. The result? Bookings shot up
The insight: People wanted to rent, but they didn’t trust low-quality images
This small test confirmed a key assumption—and led to Airbnb’s explosive growth
3. Look for Disconfirming Evidence
In 2008, hedge fund manager Michael Burry believed the U. S. Housing market was a bubble
Everyone thought he was crazy
Instead of seeking evidence to confirm his theory, he did the opposite—he searched for proof that he was wrong. He couldn’t find it. The deeper he dug, the more convinced he became
He bet against the housing market. When it collapsed in 2008, he made nearly $800 million
Had he tested his hypothesis the way most people do—by only seeking supporting evidence—he might have dismissed his own insight
The Future Belongs to the Best Hypothesis Testers
Markets are unpredictable. Consumer behavior shifts. The best investors, entrepreneurs, and policymakers aren’t those who run the best tests
They’re the ones who start with the best questions
Look at OpenA I. T he world was racing to build better search engines and social networks. OpenAI asked a different question: What if artificial intelligence could do things better than humans? Instead of optimizing existing systems, they built ChatGPT
Today, that single hypothesis has reshaped the tech industry
The Final Test
Every decision we make is a hypothesis in disguise
Should we take this job? Should we launch this product? Should we invest in this stock?
Most people get stuck proving themselves right. The smartest ones try to prove themselves wrong
Because in the end, the quality of your answers depends on the quality of your questions
And asking the right question is the hardest test of all