In April 2020, Jeffrey Katzenberg and Meg Whitman launched Quibi.
The credentials were impeccable. Katzenberg had built DreamWorks. Whitman had run eBay and HP.
They had raised $1.75 billion before a single episode aired. The research was thorough, the content was premium, and the thesis was clear: short-form video for the mobile commuter, consumed on the go.
Three weeks after launch, the world stopped commuting. Covid-19 had arrived.
Within six months, Quibi had shut down. One of the most rigorously prepared media launches in recent memory, undone by an event no reasonable process could have predicted or prevented.
In the post-mortems that followed, the question was framed the wrong way: what did Katzenberg and Whitman get wrong?
The honest answer is: not much. The decision was sound. The outcome wasn't.
And the failure to separate those two things is the mistake this article is about.
That confusion — between the quality of a decision and the quality of its result — is what leaders get wrong when they try to improve their decision making. If you want the wider picture on what a decision actually is, that's a good place to start.
Why Judging a Decision by What Happens Next Is the Wrong Measure
Most people judge decisions by what happens next.
That's the wrong measure.
And it quietly distorts every decision review, every post-mortem, and every lesson you think you've learned.
If a decision worked out, it was good. If it didn't, something went wrong. That's the default. It feels logical. It's deeply unreliable.
Outcomes are shaped by forces you don't control — market conditions, competitor behaviour, timing, chance. A good process doesn't insulate you from those forces. It gives you the best possible odds of navigating them.
That's all it can do.
The Default That Leads Even Careful Thinkers Astray
There's a name for this pattern.
Poker player and decision researcher Annie Duke calls it "resulting" — judging the quality of a decision by the quality of the result. It's one of the most stubborn biases in how leaders think about their own performance.
Psychologist Daniel Kahneman calls it outcome bias: the tendency to evaluate a decision differently depending on how it turns out, even when the information available at the time was identical.
The same call, made with the same data, gets labelled smart or reckless based entirely on what happened next.
This isn't just an academic point. It changes how honestly you can learn from your own decisions. And it changes how fairly you assess the decisions of everyone around you.
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What Actually Separates a Good Decision From a Bad One
If outcomes aren't the measure, what is?
A good decision is a choice made with the best available information, through a sound reasoning process, toward a clear objective.
The outcome is a separate question. It may confirm the decision was right. It may not. Either way, it doesn't change what the decision was.
Think of it across two dimensions: process quality and outcome quality. Four combinations are possible.
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Smart Luck — Good Outcome, Poor Process
The call worked out — but not because of anything you did well.
Think of a product launch approved on instinct, with no market research and no stress-testing. It happens to land in a gap competitors missed. Sales exceed target.
Everyone calls it a great decision. It wasn't. It was a fortunate one.
The lesson most teams take from Smart Luck is that the process was fine. It wasn't — and the next time it runs, the luck may not hold.
A Good Decision — Good Outcome, Good Process
The right result via the right reasoning. This is what you're aiming for.
But note — the outcome alone doesn't confirm it. A good outcome can arrive via Smart Luck just as easily as via sound thinking. You still need to examine the process.
A Bad Decision — Poor Process, Poor Outcome
The reasoning was flawed and the result was bad. This is where most post-mortems focus.
It isn't actually the most instructive quadrant — because the failure is visible and gets corrected. What's less visible is the pattern that produced it: assumptions that went unchallenged, options never properly considered, pressure that compressed the process.
Richard Branson's launch of Virgin Cola in the US is a clean example. The product outsold Coke and Pepsi in the UK, so the US expansion seemed logical. What the process failed to account for was Coca-Cola's response.
As Branson later admitted, they hadn't thought through what would happen when they parked their tank on the lawn of the world's most powerful brand. Coke assembled a team, pressured distributors, and pulled Virgin from the shelves. Virgin Cola achieved 0.5% US market share before closing.
The lesson got taken. But the wrong one — most coverage focused on the outcome rather than the process flaw that made it inevitable.
Good Process, Bad Outcome — Where the Real Learning Lives
The reasoning was sound, the work was thorough, and it still went wrong.
This is the opening story. Quibi did everything right. The decision to launch was defensible on every dimension available at the time.
This quadrant forces you to separate what you could control from what you couldn't — and to see that a rigorous process is worth protecting even when it produces a painful result.
Consider a hiring decision. You define the role carefully, interview thoroughly, check references, and appoint someone who seems right. Six months later, their circumstances change and they leave.
Was it a bad hiring decision? No. It was a good decision that produced a poor outcome. The process that generated it is worth repeating.
The outcome is information — not a verdict on what you did.
The same logic applies to a strategy call, a product bet, a market entry. Outcomes carry signal. They tell you whether the context matched your assumptions. But only examining the process tells you whether your reasoning was sound.
Poor decision-making at work almost always looks like this — not bad intentions, but bad process. Or worse: a good process mistakenly abandoned because the outcome was poor.
When a Bad Process Produces a Good Outcome — and Why That's the Most Dangerous Result
A good outcome doesn't make it a good decision.
A bad outcome doesn't make it a bad one.
The outcome is information. The decision is a process.
Smart Luck is the quadrant most leaders never examine — because there's no visible problem. The project landed. The hire worked out. The bet paid off. Why look closer?
Because the next time the same process runs, the luck may not hold.
If you've mistaken the outcome for evidence that the process was sound, you'll run it again with full confidence. That's where expensive mistakes come from. Not from obvious failures — from invisible ones that happen to go well.
The process gets laundered by the outcome. Over time, leaders build false confidence in thinking patterns that have never actually been tested — they've just been lucky.
And that confidence is hardest to shake precisely because nothing has gone wrong yet.
How to Put This Into Practice
Start with the process, not the result.
When you review a decision — your own or your team's — ask: what information did I have at the time? Was my reasoning sound given what I knew? Did I consider the right options?
The outcome gets examined separately, as evidence about the environment rather than a verdict on the thinking.
Resist the urge to revise your reasoning after the result is known. Hindsight bias — the tendency to believe, in retrospect, that the outcome was more predictable than it was — is how Smart Luck becomes invisible.
When you catch yourself thinking "we should have seen that coming," ask whether that signal was genuinely available before the decision was made. Usually it wasn't.
In team debriefs, separate the two conversations explicitly. "What happened?" is a different question from "How did we decide?" Run them together and the outcome contaminates the process review every time.
A simple discipline: spend the first half of any debrief on process only. No outcome discussion until the reasoning has been examined on its own terms.
One more thing. Not deciding is also a decision — and it carries the same process-outcome problem. Leaders who avoid difficult calls often do so because a previous well-reasoned decision produced a bad outcome. The lesson they took was wrong. The process wasn't the problem.
The Leader's Guide to Decision Making is built on this distinction. Every stage — from framing the decision to stress-testing assumptions — is designed to improve the quality of your reasoning, not to guarantee the quality of your results.
And if you're not sure which decision making framework to reach for, start there.
Think about a decision you've made in the last six months that you'd call a mistake. Was the process flawed — or just the outcome? The answer matters more than you might expect.
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