Second-Guessing & Double-Checking

Thirteen minutes before Apollo 11 was due to land on the moon, a yellow light began flashing in the cockpit. The number it displayed read 1202. Neither Armstrong nor Aldrin knew what it meant, so Armstrong radioed mission control for a read.

The call went to Steve Bales, a 26-year-old guidance officer, who had seconds to decide: go or abort. He double-checked.

In a simulation weeks earlier, a similar alarm had sounded, and Bales made the opposite call — he second-guessed the whole landing and recommended an abort. It was wrong, and everyone agreed almost instantly. What mattered was why: he’d treated something he could have looked up and double-checked as a judgment. So afterward, engineer Jack Garman wrote out every alarm code the computer could display and taped the list under the plastic on his console. When 1202 came up for real, Garman found it in seconds — “overloaded, not failing, still good to land” — and Bales radioed Houston one word: go.

Double-checking worked because Bales had something to check against.

There are two reasons someone might ask to look at your work again.

Double-checking turns you back toward the work — the research, the model, the assumption buried in the data. It asks: did we build this correctly?

Second-guessing revisits the judgment. It asks a harder question: was the choice itself the right one?

A speaker doing a tech check before a keynote is rigor. A CEO reopening a signed acquisition after new evidence surfaces is judgment adapting. Both are legitimate. Both can also become a way of not deciding.

Here’s the case for looking again.

Three researchers — Deborah Mitchell, Jay Russo, and Nancy Pennington — noticed something curious in 1989 about how we think about the future. Ask people to list reasons an outcome might occur, and the list is modest. Tell them it’s already happened, then ask why, and the list grows by 30 percent.

Gary Klein turned that idea into what he calls the premortem, where you gather your team and declare your plan a failure before you begin. Then ask the room to brainstorm why the plan failed. What caused the failure? What were the warning signs that the failure was coming? What can we do in the future to mitigate that failure? Certainty about the outcome pulls out risks that people had been keeping to themselves.

Garman created his list from similar reasoning: determine what could go wrong when you’re thinking clearly, so that when crunch time rolls around, it’s a lookup rather than an on-the-spot creation cooked up after reason and judgment have fled.

That’s checking again as an instrument — methodical, organized, pointed back at the work.

Second-guessing has a harder case to make. The hardest calls to change are the ones you’ve already made — watching money leave, we loosen our own standards until spending more starts to make sense again.

Researchers call this escalation of commitment. One meta-analysis on the topic compiled decades of studies and confirmed what most of us learned from plenty of mistakes: The more you invest in a decision, the harder it becomes to reverse course. Even harder when reversing course requires you to admit you were wrong. The sunk cost isn’t only money, time, and effort. It’s identity.

Good decision-making means having the confidence to reopen a choice when the facts change. Wisdom is knowing that person might be you.

So here’s a question worth putting to your team: are we looking at this again because something in the world changed, or because the discomfort of choosing hasn’t gone away?

At some point, the data analysis ends, and you have to make a choice. Every leader I respect can tell you exactly when that moment came for them—not as a theory, but through a decision where they learned it the hard way.