The answer up front: Messy decision-making costs more than bad decisions do. Slow approvals, unclear owners, and re-decided decisions drain time invisibly across every team. McKinsey estimates the waste at roughly $250 million a year for a typical Fortune 500 company. The fix isn’t smarter people. It’s better decision infrastructure.
Nobody schedules a meeting called “Let’s Waste Q3.” It happens anyway, one soggy decision at a time.
Here’s the thing about a burst pipe: you fix it immediately. Water everywhere, everyone panics, a professional shows up within the hour. A slow drip behind the wall? That one runs for years. Nobody sees it, nobody owns it, and by the time you smell it, you’re replacing the floor.
Bad decisions are burst pipes. They’re dramatic, they’re visible, and organizations are surprisingly good at cleaning them up. Messy decisions are the drip. And the drip is what’s eating the building.
What does messy actually look like?
You already know, because you’ve lived it this week:
- A decision gets made in Tuesday’s meeting, then quietly re-decided in Thursday’s, because the right person wasn’t in the room on Tuesday.
- Nobody can say who owns the call, so it escalates. Then it escalates again. A $500 question burns $5,000 of executive attention.
- The decision gets made, but not written down. Three months later, a new hire asks “why do we do it this way?” and the honest answer is: nobody remembers.
- Work starts before the decision is final. The decision changes. The work gets redone.
None of these show up on a P&L. There’s no line item for “re-litigated the pricing call four times.” That’s exactly why it compounds. Decisions have downstream costs, and most organizations pay them in silence.
How big is the leak, really?
Bigger than intuition says. In McKinsey’s survey on decision-making, 61 percent of managers said most of the time they spend on decisions is used ineffectively. Not some of it. Most of it. McKinsey’s math on what that means for a typical Fortune 500 company: more than 530,000 days of lost working time a year, roughly $250 million in wasted labor cost.
You’re not a Fortune 500? Good news, your leak is smaller. Bad news, so is your margin for absorbing it. A 40-person company runs on the same physics: if your managers spend a third of their time on decisions and most of that time is friction, you’re paying a full-time salary or three for the privilege of going in circles.
The drip doesn’t show up as a cost. It shows up as “why does everything take so long here?”
Why don’t smart people fix this?
Because everyone assumes decision quality is about the people, and the people are fine. Companies hire sharp folks, then drop them into a system with no memory: no record of what was decided, no owner per decision, no way to tell a two-way-door decision (cheap to reverse, decide fast) from a one-way-door decision (expensive to reverse, decide carefully). The talent isn’t the problem. The plumbing is.
That’s the whole idea behind decision infrastructure, and it’s less exotic than it sounds. It means the important decisions in your business have a visible owner, a written “what we decided and why,” and a speed that matches their stakes. That’s it. No platform purchase required to start. A shared doc and some discipline will outperform most enterprise software here.
Where does AI fit in?
Carefully, and second. AI is genuinely good at the drudgery around decisions: pulling the data into one place, surfacing the pattern a human wouldn’t have the hours to find, remembering what was decided last quarter when everyone else has moved on. We run our own company this way, so this isn’t theory.
But pour AI into messy decision plumbing and you get faster mess. The order of operations matters: make the decision visible first, then let AI make it faster and better informed. (That ordering is worth its own article. It’s next.)
What should a leader actually do this week?
Pick your three most expensive recurring decisions. Not the big strategic one-offs, the ones that come back every week or month: pricing exceptions, hiring approvals, what gets built next. For each, answer three questions. Who owns it? Where is it written down? How often do we re-decide it?
If any answer is “unclear,” “nowhere,” or “constantly,” you’ve found your drip. Fixing one is usually worth more than a quarter of new productivity tooling.
And if you want a second set of eyes, that’s precisely what our audit does: find the one leak worth fixing first.
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Quick questions
What is decision infrastructure? The basic system around your decisions: a named owner for each recurring decision, a written record of what was decided and why, and a pace matched to the stakes. Simple to describe, rare in practice.
Is this an AI problem or a process problem? Process first. AI multiplies whatever system it lands in, so it pays off most after the decisions it supports are visible and owned.
Where do I start if everything feels messy? Start with recurring decisions, not dramatic ones. They repeat, so one fix pays you back every week.
Sources: McKinsey & Company, “Decision making in the age of urgency” (survey of ~1,200 managers; 61% report most decision-making time used ineffectively; ~530,000 days and ~$250M/yr modeled for a typical Fortune 500).
