In the companies I’ve watched up close, execution speed is one of the most loved words. People talk about agile teams, sprints, delivery. They reward whoever ships fast. They evaluate managers on how much they make happen in a quarter. Speed has become, in many contexts, the main signal of competence.

There’s something true in this. Slow execution is almost always a symptom of problems. But there’s also a trap that’s hard to recognise once you’re inside it. Execution speed, by itself, doesn’t guarantee you’re going in the right direction. It only guarantees you arrive there sooner, whatever direction it turns out to be.

When the upstream decisions are clear, speed becomes a multiplier. A team that knows exactly what it’s building and why can ship fast and accumulate results. When the upstream decisions aren’t clear, speed does the opposite work. It multiplies errors, friction, rework. You travel far, but across a terrain that wasn’t the one you wanted to cross.

I saw this clearly in a company I followed for a few months. They had a product team considered top tier. Weekly release cadence. New features every two weeks. Their delivery numbers were above the industry average. Their operational meetings ran smoothly. From outside, it was a textbook case.

From inside, the picture was different. The features being shipped changed direction every two or three months. A feature A was born to serve a certain customer segment. Three months later it was reworked for a different segment. Six months later it had been almost dismantled because they’d found out the original segment was the right one, but they’d rewritten it in the meantime. The release velocity was real. The learning velocity, in practice, was zero. They were running back and forth across the same patch of ground.

When we looked at the problem up close, the diagnosis came on its own. The strategic product decisions, the ones that should have declared who we make this for, and why, weren’t being made. They got pushed to the next quarter, the next user research, the next round of feedback. In the meantime the team kept executing, because no one wanted to stop the machine. Speed had become an excuse not to decide.

Here’s the subtle point. When people get used to being measured on execution speed, deciding becomes an activity that slows things down. So it gets avoided. Postponed. Delegated to later iterations, hoping the decision will emerge from the data. But data doesn’t decide for us. It shows what happened, not what should happen. For that you need a choice, and a choice requires a moment when you stop.

Stopping, in a company fixated on speed, looks like losing ground. It looks like admitting you’re stuck. It’s exactly the opposite. It’s the only way to avoid building speed in the wrong direction.

There’s a mental test I propose to teams in this condition. Look at what you’ve shipped in the last six months and ask yourselves: of all this, how much is still alive, used, a stable part of the system? How much has been modified, replaced, dismantled, shelved? If the ratio leans toward the second, speed isn’t producing value. It’s producing work.

There’s a side effect to this kind of accumulation. People working in speed-without-direction teams burn out in a specific way. It’s not the physical exhaustion of too much work. It’s the cognitive exhaustion of watching their work get modified constantly without anyone really explaining why. After a year of this regime, the best people start looking around. They leave not because they’re working too much, but because they see their work isn’t accumulating into anything solid.

Speed is an amplifier. It isn’t a direction. When the decisions have been made, the amplifier helps. When they haven’t, the amplifier just causes more damage in less time.

The question to ask isn’t how do we accelerate execution. It’s have we decided what we’re executing, before accelerating?