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# What leaves when your best person walks out the door?
- URL: https://www.builttorun.tv/what-leaves-when-your-best-person-walks-out-the-door/
- Published: 2026-11-04T16:52:34.000Z
- Updated: 2026-11-04T17:37:07.000Z
- Author: Leighton Healey

[Spotify](https://open.spotify.com/show/0342v7Wmmth6H1ULqo2rZF?ref=builttorun.tv) · [Apple Podcasts](https://podcasts.apple.com/us/podcast/built-to-run/id6798737017?ref=builttorun.tv)

I often think about the person everyone calls when a job gets complicated.

Maybe you already have a face that popped into mind. 

They know which questions to ask. They spot the detail a newer employee walks straight past. They can look at a situation and tell you, “We’ve seen this before. Here’s what we need to do.”

Now imagine that person retires, or leaves unceremoniously.

Their completed jobs are still in your system. So are their notes, maybe some of their training materials too. But how much of the thinking behind those decisions could someone else actually use?

[Scott Klososky](https://www.linkedin.com/in/scottklososky/?ref=builttorun.tv) is a speaker, writer, and consultant that focuses on how organizations can harness Artificial Intelligence to level up their operations. In our conversation, he made a distinction that puts words to something I've felt for a long time but never seen so succinctly articulated: data is what your organization collects; knowledge is what your organization understands.

Let me double-click on this, because 99% of businesses I see are not thinking in this way:

Data is what your organization collects, knowledge is what your organization understands.

This is a mindset shift that could have huge consequences for large service businesses. Many of the most sophisticated organizations have years of records and still need the same three people to explain what to do next.

Scott had a way of making a big conversation about AI feel very practical. And this part brought me right back to the field. The installer who knows why a job needs a different approach. The manager who notices a problem before it becomes a callback. The Safety Manager who can see a potential hazard from a mile away.

Those people have spent years developing that judgment. If we want the rest of the team to benefit from it, we need to make time to understand how they think.

### Harnessing the Judgment of Your Best People

Here’s where I’d start.

Pick one experienced person and ask them to walk you through a recent job that required some judgment. Choose something where the usual instructions weren’t quite enough.

Ask:

- What did you notice that someone newer might have missed?
- What options did you consider, and why did you choose that approach?
- When would you stop and ask for help?

Capture their explanation, including the conditions that would change their answer. Then ask a less experienced teammate to talk through how they’d use it on a similar job.

Where they get stuck is useful. It tells you what still needs explaining.

You’ve now got one piece of experience you can build into training and make available where that work happens.

### Give Your Best People Room to Teach

There’s a human side to this that matters a great deal.

When someone has become the person everyone relies on, their expertise is often a big part of how they see their contribution. Asking them to share it should feel like an opportunity to develop the team and extend the impact of what they’ve learned.

And we have to give them time to do it. It’s hard to explain your thinking when your phone is ringing and another crew is waiting for an answer.

The full conversation above also gets into how leaders should decide where AI belongs and where human judgment and relationships matter most.

For this week, though, I’d keep it small: one person, one recent decision, and enough time to get beyond “that’s just how I do it.”

Leighton