I was in a planning meeting when someone asked a VP, "Why did we prioritize the Chicago market over Denver?"She paused. "We ran some analysis. We got a recommendation. It felt right. So we went with it.""But what analysis?" the director pressed."I... don't remember the details. It was solid though."
Nobody challenged the decision at that point. But you could see it in everyone's face: nobody was entirely confident it was right.
That's a black-box decision. And it happens constantly in business.
What Makes a Decision Black-Box?
A black-box decision is one where:
1. You can't trace the reasoning. Someone made a recommendation, but you don't know how they arrived at it. Was it analysis? Intuition? Pattern matching? Bias?
2. You can't verify the sources. Where did the underlying data come from? Is it current? Is it reliable? You have no way to know.
3. You can't see the trade-offs. Every decision has pros and cons. But in a black-box decision, you don't know what was weighed or why certain factors were prioritized.
4. You can't challenge the assumptions. What if the underlying assumptions were wrong? You have no framework to test them.
5. You can't defend it later. If the decision goes wrong, you can't explain what you were thinking. That's a governance nightmare for boards.
Real Examples of Black-Box Decisions
"We analyzed the market and think we should acquire Company X."
Translation: Someone did analysis (but who? what data? how current?). No visibility into reasoning. Board uncomfortable. But they approve anyway because "the executives seem confident."
"ChatGPT says we should pivot our go-to-market strategy."
Translation: A chatbot gave an answer. It sounded smart. Nobody asked where it came from or what assumptions it was making. Now the team is executing on a recommendation nobody fully understands.
"The data shows we should hire in Denver, not Chicago."
Translation: Someone ran analysis. But which data? From when? What factors were considered? Cost of living? Talent pool? Regional partnerships? You don't know. You just know what the recommendation was.
The Hidden Costs
Black-box decisions don't just feel bad. They have measurable costs:
Lower confidence. Your team executes without fully understanding why. Motivation suffers. Execution wavers when obstacles appear.
Slower pivots. If the decision turns out wrong, you don't know which assumptions to challenge. So you blame the execution, not the strategy. Real problems don't get fixed.
Governance risk. Boards are demanding to know how decisions were made. Regulators want audit trails. If you can't explain your reasoning, you're vulnerable.
Bias amplification. When reasoning is hidden, personal biases influence decisions silently. No one catches them. Bad decisions repeated.
Talent loss. Smart people want to work in organizations where strategic thinking is visible and valued. Black-box decisions feel arbitrary to them. They leave.
A Better Way: The Three Questions Test
Next time you're making a strategic decision, ask yourself these three questions. If you can't answer them clearly, you need better advisory.
Question 1: Who recommended this, and what's their specific expertise?
If the answer is "I got it from a chatbot" or "I read it somewhere" or "my gut told me," that's a red flag. You need to know who (or what) is recommending and whether they actually have relevant expertise.
Question 2: What data supports this, and how current is it?
"Data from last year" is not the same as "data from last week." "Analyst reports" is not the same as "market research from your actual customers." If you can't point to specific sources, you're making assumptions disguised as facts.
Question 3: What are the trade-offs, and what could go wrong?
Every decision has costs. If you're not explicitly acknowledging what you're giving up to pursue this strategy, you haven't thought it through. Good decisions include clear-eyed assessment of what could go wrong.
If you can answer these three questions clearly, you have good advisory. If you can't, it's time to improve your decision-making process.
What Better Advisory Looks Like
When you have better advisory, decisions start looking different:
"Our market analysis shows Chicago is better than Denver. Here's why: talent pool is 40% larger, partnership ecosystem is stronger, cost of living is lower. However, Denver offers faster growth potential and less competition. We're recommending Chicago for the next 18 months, but we should revisit this if Denver market conditions change. Here's what could derail this: if a major competitor moves to Denver..."
See the difference? Specific reasoning. Data sources. Trade-offs acknowledged. Assumptions transparent. Team confidence high. Board comfortable defending it. Everyone aligned on what to monitor for changes.
The Takeaway
Black-box decisions are the norm in most organizations. But they shouldn't be. Not for decisions that matter.
You deserve to know the reasoning behind your decisions. Your team deserves to understand what they're executing. Your board deserves to see the audit trail.
The next time someone gives you a recommendation, ask: "How did you arrive at this? What data supports it? What are the trade-offs?" If they can answer clearly, you have good advisory. If they can't, push back. Keep pushing until the reasoning is visible.
That's the difference between decisions you make and decisions you understand.
💡 This week: Audit one recent strategic decision. Can you answer those three questions clearly? If not, what would you need to understand it better?
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