What this article will teach you: The decision-making advice you’ve been getting is backwards. Instead of eliminating biases, you need to clarify what you’re actually deciding. This simple shift will transform how you make choices—from what to order for lunch to whether to bet your company’s future.
The TL;DR: Stop trying to think better. Start trying to see better. The biggest decision failures happen when smart people solve the wrong problem perfectly, not when they solve the right problem poorly.
The Night Wall Street Almost Ended
It’s 2 AM on September 14, 2008. Dick Fuld hasn’t slept in 72 hours. The CEO of Lehman Brothers is staring at two pieces of paper that will determine whether the 158-year-old investment bank survives until morning.
Paper one: File for bankruptcy. Ugly, but clean.
Paper two: Sell everything—the buildings, the people, the relationships—to whoever will take them. Also ugly, but maybe survivable.
Fuld’s team has run every analysis imaginable. They’ve brought in outsiders to challenge their thinking. They’ve stress-tested assumptions. They’ve followed every decision-making best practice taught in business schools.
And yet, Fuld is about to make one of the most catastrophically wrong decisions in financial history.
Not because he was biased. But because he never answered a more basic question: What exactly was he trying to save?
Your Brain on Bias Training
If you’ve attended a leadership program in the last decade, you’ve been taught that good decisions come from eliminating bad thinking. Overconfidence bias. Confirmation bias. Anchoring bias. Sunk cost fallacy. The list goes on.
The promise is seductive: Learn to spot these mental traps, and you’ll make better choices.
There’s just one problem. It doesn’t work.
Here’s what actually happens when smart people focus on eliminating biases: They get so busy debugging their thinking that they forget to understand what they’re thinking about.
The Theranos Board Knew All About Groupthink
Elizabeth Holmes wasn’t stupid. When she built Theranos, she knew that insular thinking kills startups. So she assembled the most impressive board in Silicon Valley history.
Henry Kissinger. George Shultz. James Mattis. Sam Nunn. These weren’t tech bros who’d rubber-stamp anything. These were distinguished outsiders with sterling reputations and no reason to go along with a bad idea.
For years, they provided exactly what bias training promises: independent perspectives, tough questions, rigorous oversight.
While Theranos burned through $900 million on technology that never worked.
The board had eliminated groupthink. But they’d never clarified what they were actually governing. Was Theranos a healthcare company? A technology company? A regulatory play? A marketing phenomenon?
Without that basic understanding, all their independent thinking was just sophisticated confusion.
The JCPenney Disaster: When Being Right Goes Wrong
Ron Johnson thought JCPenney customers were being manipulated.
The data was clear: People say they hate promotional pricing. They’re frustrated by artificial sales and fake markdowns. They want honest, straightforward prices.
So in 2012, Johnson eliminated JCPenney’s promotional strategy entirely. No more “50% off” signs. No more sale events. Just everyday low prices.
He’d overcome the sunk cost fallacy by abandoning decades of retail strategy. He’d fought anchoring bias by ignoring historical pricing data. He’d avoided confirmation bias by hiring consultants who challenged conventional wisdom.
The result? JCPenney lost nearly a million customers and $985 million in revenue in one year.
Johnson’s bias-free analysis had missed something crucial: JCPenney customers weren’t buying products. They were buying the experience of getting a deal.
They wanted to feel smart, successful, skilled at finding value. The promotional complexity wasn’t a bug—it was the feature.
Johnson had perfected his thinking while completely misunderstanding his problem.
What Your Brain Actually Does When You Decide
Here’s what neuroscientists have discovered about how people make good decisions under pressure.
Firefighters don’t eliminate biases when they enter burning buildings. They don’t methodically weigh options while correcting for overconfidence.
Instead, they’ve trained their attention to focus instantly on what matters: structural integrity, heat patterns, escape routes. Everything else becomes background noise.
This isn’t bias elimination—it’s clarity of purpose applied to perception.
The firefighter knows exactly what they’re optimizing for: save lives, minimize risk to the team. That clarity acts like a filter, making relevant information jump out while irrelevant details fade away.
Great decision-makers don’t think better. They see better.
The Netflix Moment
In 2010, Netflix faced a choice that would define its future.
DVDs generated 60% of revenue and 80% of profit. Wall Street loved the margins. Customers loved the selection. Everything about the DVD business was working beautifully.
Except that Reed Hastings could see it was doomed.
Not because he had better data than his critics. Not because he’d eliminated more biases. But because he understood what Netflix was actually choosing between: being a DVD company with a streaming side business, or being a streaming company that happened to rent DVDs.
Once that choice became clear, the decision made itself. Even though it meant cannibalizing the most profitable part of the business.
Hastings wasn’t operating with superior analysis. He was operating with superior clarity about what Netflix was protecting: future relevance over current comfort.
The Three Questions That Actually Matter
Most decision training focuses on how to think about choices. But the real challenge is understanding what you’re choosing between.
Before analyzing any options, ask yourself:
What are we actually deciding? Not the surface choice, but the deeper question. Are we choosing between products, or between visions of who we want to be?
What would we regret most? Jeff Bezos used this when deciding whether to start Amazon. He projected himself to age 80 and asked: “What would I regret more—trying and failing, or never trying?”
What kind of organization do we become with each choice? Every significant decision is really an identity decision. It shapes not just what you do, but who you are.
These aren’t bias-correction techniques. They’re clarity-building tools.
Why Smart People Keep Making Dumb Decisions
Gary Klein has studied decision-making in high-stakes environments for decades. His conclusion: Most catastrophic failures don’t result from faulty reasoning. They result from situation misassessment.
The pilots who crashed Air France 447 didn’t make computational errors. They misunderstood what was happening to their aircraft and responded perfectly to the wrong problem.
Banks that collapsed in 2008 didn’t miscalculate risk. They misunderstood what kind of risk they were taking. They thought they were managing statistical probabilities when they were actually making bets on social and political systems.
This is why bias training often backfires. You can’t reason your way out of problems that stem from seeing the wrong problem in the first place.
The Quibi Question
Jeffrey Katzenberg and Meg Whitman raised $1.75 billion for Quibi by presenting flawless market research.
They’d identified the bias that led entertainment executives to dismiss mobile viewing. They’d overcome generational prejudice by surveying younger consumers extensively. They’d fought technological skepticism with superior production values.
Their data showed clear demand for premium short-form content designed for mobile consumption.
Quibi collapsed in six months.
Not because their analysis was wrong, but because they’d never clarified what they were actually creating. Were they competing with Netflix? TikTok? YouTube? Podcasts? Mobile games?
Without that fundamental understanding, all their bias-corrected research was just expensive confirmation of the wrong hypothesis.
The Commitment Test
Here’s how you know when you’ve achieved real clarity: hesitation disappears.
Watch any great athlete in competition. They don’t eliminate biases in real-time. They commit completely to their read of the situation.
A quarterback doesn’t throw to the “objectively best” receiver. They throw to where their understanding of the defense tells them to throw.
This commitment isn’t recklessness. It’s the natural result of seeing clearly enough to act decisively.
Business leaders who struggle with commitment are usually struggling with clarity. They haven’t understood what they’re actually deciding, so they can’t commit fully to any choice.
What Actually Works
The companies that navigate major transitions successfully don’t just analyze better. They understand better.
They see that every significant choice is ultimately about identity: Who do we want to become?
Netflix chose future identity over present comfort. Amazon chose long-term customer obsession over short-term profits. Apple chose elegant simplicity over technical specifications.
These weren’t bias-free decisions. They were value-clear decisions.
The Real Problem with Bias Training
The bias-elimination approach treats decision-making like debugging software: identify the errors, patch them, optimize performance.
But the most important organizational decisions aren’t software problems. They’re identity problems.
They require understanding who you are, what you value, and who you want to become. This understanding can’t be achieved through better analysis or bias correction.
It requires something more fundamental: the willingness to see situations as they actually are and make choices based on what actually matters to you.
Stop Debugging, Start Seeing
Before your next major decision, don’t ask what biases might be affecting you.
Ask what you’re actually choosing between at the deepest level.
The answer won’t eliminate your biases. But it will make them irrelevant.
Because when you see clearly what you’re protecting and why it matters, the choice often becomes obvious.
That’s the difference between thinking clearly and seeing clearly.
And in a world that rewards decisive action over perfect analysis, seeing clearly is the only skill that actually matters.
Your biases aren’t the problem. Your clarity is.