“Who made this decision?”
Think back to a time when you sat in a conference room or in a virtual meeting. The executive team made a decision and it’s trickling down to your team.
As the decision is being described, a quiet question pops into your head:
“Who made this decision?”
What do you do next?
Do you keep silent, telling yourself you will gather more information later?
Do you speak up and challenge the logic in the moment?
Do you open slack or teams and message your teammates trying to figure out what is happening?
Do you fully agree, without hesitation?
Now imagine if we removed the people from the room.
If all you had was a slide deck, could you summarize the decision clearly? What would it say?
In many organizations, leadership teams rely on polished decks to present decisions, with very little detail about how the tradeoffs were made or who owns the outcome. In that sense, decisions are often marketed more than they are explained.
And when decisions fail to start, or fail to complete, this is usually where trouble begins.
The biggest mistake leaders make is assuming the decision problem is PEOPLE, when it’s really the SYSTEMS those people are operating inside.
In my experience, I have done all of these things. I have stayed silent and gathered information behind the scenes. I have challenged decisions openly. I have opened Slack or Teams to ask trusted colleagues what they think. And I have fully agreed with decisions, without hesitation.
As a data-driven leader, I use data to validate decision logic. Sometimes the data supports the decision. When it does not, I almost always see invisible forces tipping the scales:
Power dynamics override evidence
Fear of consequences silences dissent
Misaligned incentives distort judgment
Time pressure forces premature closure
Ego shows up as “confidence”
Ownership is unclear, so no one truly decides
These are the traps intelligent, savvy, data-driven leaders fall into again and again. Culture quietly drives decision making, which makes it difficult to see where decisions are actually breaking down.
Leaders and their teams are working hard, to deliver and to stay competitive. Most people want to do a good job. But when priorities shift every week, every sprint, or every month, energy drains, ownership erodes, and disengagement follows.
Do you know the hidden costs of bad decision making?
Let’s look at how this shows up across organizations.
Marketing Team: where decisions quietly leak money
The marketing team has a $500,000 annual budget. Campaigns are approved quickly. Metrics are considered “good enough”. No one challenges the underlying assumptions about audience, channel, or message.
Hidden costs
15-30% of campaign spend wasted on misaligned targeting or messaging
20-40% rework on creative, landing pages, or attribution analysis
2-4 weeks of lost momentum before the issue is recognized.
When metrics are “good enough”, teams stop trusting performance data. Analysts become reporters instead of advisors. When the campaign underperform, leadership overcorrects in the next planning cycle. Money quietly leaks out of the system.
There was no bad execution here. The loss came from decisions made early, driven by flawed framing. A 20% misallocation on a $500,000 budget results in a true cost of $100,000.
In marketing, bad decision framing quietly leaks money. In engineering, it turns into technical debt. In operations, it shows up as inefficiency and drag.
For a software engineering team, decision shortcuts almost always compound. Scope decisions driven by urgency or politics create an environment where tradeoffs are implicit and defects are deferred. Over time, teams spend 20–50% of their effort reworking, refactoring, or working around past decisions. Fixing issues after release can cost two to five times more than addressing them during design. Roadmaps lose credibility, velocity slows, and senior engineers disengage. What looks like speed in the moment becomes hundreds of thousands of dollars a year spent paying for earlier choices.
In operations, the cost is quieter but often larger. Decisions are deferred to “see how it plays out,” ownership is ambiguous, and exceptions pile up. Teams rely on workarounds and institutional knowledge instead of clear process. Efficiency drops by 10–25%, error rates spike during periods of uncertainty, and cycle times stretch by weeks. Leaders are often surprised by failures that were entirely predictable. The financial impact can easily reach seven figures through lost productivity and missed opportunity.
Different teams. Same pattern.
When decisions are shaped by invisible forces instead of clear ownership and explicit tradeoffs, the cost does not show up as a single line item. It shows up as rework, delay, disengagement, and erosion of trust.
And by the time the numbers appear, the decision has already been made.
When decisions fail, organizations usually look for the wrong explanation. They look for execution problems, skill gaps, or accountability issues.
What they rarely examine is the system the decision was made inside.
Until leaders learn to see those systems clearly, they will keep asking smart people to solve problems that were never theirs to fix.
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