The Assumption killer
Your strongest convictions are your biggest blind spots.
“The greatest impediment to discovery is not ignorance, but the illusion of knowledge.”
— Daniel Boorstin
You’ve studied your competitors long enough to understand them. You know their playbook. You know their bad points and what they can’t do. You know what they will and won’t do. You’ve built mental models. You have confidence.
That confidence is at which intelligence can wither and die.
Because confidence means you stop questioning. You stop looking for disconfirming evidence. You stop considering alternatives. You’ve decided what’s true, and now you’re just collecting evidence to confirm it. The longer in the tooth you get in your industry, the more you have decided you know what’s going on.
Your competitor would never do X because they’re focused on Y. Your competitor can’t afford Z because their margins are too thin. Your competitor won’t enter that market because it doesn’t fit their strategy. You’re not learning these things. You’re assuming them.
The moment you’re certain, you stop thinking.
The Assumption Trap
Every intelligence analysis is built on assumptions. Assumptions about competitor motives. Assumptions about customer priorities. Assumptions about market forces. Assumptions about what’s possible and what’s not.
Early on, you recognise these as assumptions. You test them. You look for evidence that contradicts them. You’re sceptical.
Then something confirms your assumption, and you graduate it to a fact. Now it’s no longer an assumption. It’s knowledge. You stop testing it. You stop looking for contradictions. You organise all future intelligence around it.
Confirmation bias turns assumptions into convictions. Convictions become blindness.
The Cost of Certainty
Certainty feels good. It’s comfortable. You know what you’re dealing with. You can plan. You can decide. Uncertainty is anxiety. So you resolve uncertainty by deciding something is true, then ignoring contradictions.
Your competitor is resource-constrained. That’s certain now. So when they make moves that require resources, you explain them away. They’re not really spending that money. They’re shifting resources from somewhere else. They’re over-extending. Your assumption explains everything because you won’t let evidence contradict it.
Your market is mature. That’s certain. So when new entrants appear, you explain them away. They’re not real competitors. The market will reject them. Your customers are loyal. Your assumption protects you from noticing change.
Certainty is the enemy of learning.
The Pattern Completion Problem
Your brain hates incomplete information. It fills gaps with assumptions. It sees patterns where none might exist. It connects dots that aren’t connected. It makes sense of chaos by imposing order.
Intelligence analysis should question this.
It should say “we don’t know” more often than “we know.”
It should say “evidence is mixed” instead of picking the interpretation that fits existing beliefs.
Most intelligence teams do the opposite. They complete patterns. They resolve ambiguity in the direction of existing assumptions. They fill gaps with what they expect to find instead of admitting they don’t know.
When Competitors Challenge Expectations
Then a competitor does something that contradicts your assumptions. Something you were certain they wouldn’t do. Something you didn’t think was possible.
Your response is usually to explain it away. It’s a mistake. They’re desperate. It won’t last. They’ll reverse course. Anything except “Maybe my assumption was wrong.”
Instead, you should ask: What would make them do this despite my assumptions about them? What do I not understand about their situation? What am I missing?
That competitor you were certain was resource-constrained just launched an expensive growth plan. Maybe they found new funding. Maybe they’re willing to lose money. Or maybe they’re borrowing from somewhere. Maybe they’re desperate. Instead of defending your assumption, investigate why it was wrong.
The Expert Trap
The more you study something, the more certain you become. You have sources. You have patterns. You have history, and of course, you understand your industry. You’ve become an expert.
Expertise is useful. Expert certainty is dangerous. Because experts are often most confident about things that are about to change.
The experts on horse transportation in 1900 were certain about their market. In 2000, the newspaper experts were certain about their model. The experts on video stores in 2010 were certain about their future. Their expertise made them blind to change because expertise is usually concerned with understanding how things work now, not how they might work differently tomorrow.
The Productive Doubt
The best intelligence professionals maintain a healthy doubt. They hold strong hypotheses without certainty. They test those hypotheses constantly. They’re ready to abandon them the moment evidence demands it.
They sound uncertain to those who want and need certainty. “Here’s what we think is happening, but we’re watching for signals that would change our view.” “Our analysis suggests this direction, but we’re alert to these specific indicators that would prove us wrong.”
Uncertainty sounds weak. It’s actually the sound of honesty. It’s the only position that allows you to learn.
Building in Disconfirmation
Smart intelligence functions look for evidence contradicting their conclusions. They don’t just collect supporting evidence. They ask, “What would prove our assessment wrong? What signals would we need to see? What data would change our minds?”
Then they monitor for those signals.
This is harder than confirmation bias. It requires discipline. It requires humility. It requires accepting that you might be wrong about things you’re confident about.
Most intelligence teams don’t do this. They look for confirming evidence and call it analysis. They’re not analysing. They’re just arranging facts to support existing beliefs.
The Assumption Audit
Every intelligence analysis should include an assumption section.
State clearly what you are assuming to be true. Here’s what you need to see to change that assumption. Here’s what would disprove it.
Put the assumptions in writing. Make them testable. Make them falsifiable. Then actually test and monitor them instead of just collecting confirming evidence.
Never hide assumptions, and most analyses do. They’re integrated into the story so thoroughly you don’t see them. That’s not rigour. That’s manipulation disguised as analysis.
Thought-Provoking Question
“What are you most confident about regarding your competitors, and what would it take to prove you completely wrong about it?”
Practical Advice
Build a “disconfirmation protocol” for every major intelligence conclusion. Take your top three convictions about competitors or the market. For each one, write down:
- What evidence would contradict this?
- Where would that evidence come from?
- How would we know if we were wrong?
Then set up monitoring for disconfirming signals. If you find them, you change your analysis immediately. If you don’t find them after a year, your assumption is probably right. But you’ll have to test it rather than just assume it.
Rotate intelligence analysts on competitor accounts annually. The analyst who’s studied a competitor for three years is too invested in their own conclusions. They see what they expect to see. Bring in a fresh analyst who looks at the same data and sees different patterns. Compare their analysis to the incumbent analyst’s. The differences will reveal where certainty has blinded the first analyst and where a new outlook reveals blind spots.
Create a quarterly “what we were wrong about” review. Look back at the intelligence conclusions from a year ago. Which ones didn’t hold up? Which predictions didn’t materialise? Which assumptions proved false?
Celebrate the ones you were wrong about because being wrong and admitting it means you’re learning. If you were never wrong, you’re either perfect (unlikely) or you’re not taking enough intellectual risks in your analysis (more likely).
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