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Burn Notice
TL;DR
There’s a kind of burnout HR leaders learn to fear over time. It’s neither loud nor does it show up in exit interviews or engagement scores. It’s the quiet kind that hides inside competence and reliability. And that’s why it’s so difficult to address it.
Episode 11 is about that version. The one where your best people don’t disengage. They just stop extending themselves. And by the time the data catches up, you’re already too late.
Kelly starts noticing a subtle shift among LumaCore’s highest performers. Nothing is ‘wrong’ on paper really. Engagement scores are stable. Output hasn’t dipped. But something feels off. Instead of waiting for the quarterly data to confirm it, Kelly connects small signals early and steps in before burnout turns into attrition.
The Situation
Kelly was analyzing 1:1s on Klaar and something felt off. She couldn’t put her finger on it but there was definitely something off about it. After all these years, Kelly had learned to trust her “HR instinct” even though her rational mind was pushing her to brush it off.
Four conversations in one week. Different teams. Same tone.
“Can we move my 1:1s to biweekly? I’m unable to keep up with a weekly cadence.”
“I’m fine. Just tired. Sorry that I couldn’t log-in after work on the day of the release.”
“I don’t need anything right now but I don’t have bandwidth for anything more as well.”
“No new ideas to contribute.”
These people were not underperformers. In fact, they were the people managers leaned on when things broke. The ones who made chaos look manageable.
Maya picked up on it too - she was exceptionally astute. “They’re not disengaged,” she said. “They’re… pulling inward?”
Kelly nodded. “They are all from different departments right?”
“Yeah. Product, Engineering, Quality and Design.” Maya mentioned.
“Wait, so they are all from the broader Tech BU?” Kelly asked.
“Oh yeah, that’s true. Didn’t think of it like that” Maya admitted, almost annoyed that she did not pick up on this rather obvious connection.
“Is there anything else that they share in common?” Kelly asked. She could sense that she was getting closer to identifying the pattern but wasn’t quite there yet.
“Not really. I checked. Their engagement scores are all okay. Some of them joined us two years back while a couple have been with us since inception. Split between different genders too and nationalities.” Maya was sure she had looked at everything.
“Hmm..interesting.” Kelly mentioned while being deep in thought. “What are their performance ratings on Klaar?”
Maya opened Klaar. “Wow, they are all top-rated. But that’s a good thing right?”
“We are not looking at good or bad - we are trying to establish a connection.” Kelly had what she needed. “These people are headed for a burn-out.”
The Spiral
Daniel wasn’t convinced when Kelly raised it. “Burnout?” he said. “Nobody’s quitting.”
Lena looked up. “What are we seeing that the data isn’t?”
Kelly didn’t open a dashboard. She opened her notes. “First up, I need all of you to realize that not everything will show up as data. Now these people are still delivering,” she said. “They’re just stopping the extra work. No volunteering. No pushback. No curiosity. These folks have been the top performers in the Tech BU and have been rewarded with more work. When they highlight challenges, it’s only on them to solve them.”
Parker added a little defensively, “Engineering always gets tired after big pushes.”
“This isn’t post-release fatigue,” Kelly replied. “This is cumulative. And I’m not pointing fingers at you - this is a part of work but it needs to be dealt with.”
Daniel crossed his arms. “So what’s the actual risk?”
“That we’re waiting for lagging indicators,” Kelly said. “And these people don’t fail loudly. They will leave quietly.”
The Pivot
That evening, Kelly went back to something she rarely had time to read closely - 1:1 notes. Not scores. Not summaries. Actual manager check-ins captured over time.
In Klaar, the engagement pulse was steady. No red flags. No alerts. But the 1:1 sentiment had clearly shifted.
Shorter conversations captured by the KlaarBot. Less specificity. Fewer future-oriented comments. More “all good” language where there used to be stretch and debate.
This wasn’t retrospective data. This was a drift. Maya leaned over her shoulder. “That’s subtle.”
“Yes,” Kelly said. “And that’s why it matters.”
The Reframe
Kelly didn’t send a company-wide message. She asked managers to have candid conversations with these and similar people. Not about wellness. Not about resilience.
About work-load. But she had to be careful because the company was indeed chasing audacious goals.
Not “How are you feeling?”
But “What are you carrying that you feel shouldn’t be a part of your role?”
Kelly sat in on a few of those conversations. They were uncomfortable at first, but then surprisingly honest.
One person admitted that she hadn’t taken a real day off in months because she was the escalation point. Another said he was covering for a role that was never backfilled. A third said she didn’t want to complain because “things are going well.”
Kelly listened. None of this would have shown up in a quarterly survey.
The Meeting
Daniel pushed back again. “This feels subjective,” he said. “We can’t run the company on vibes.”
Kelly met his eyes. “We’re not. We’re running it on patterns. Lena, have we not lost people like this before?”
Lena nodded slowly. “We have. I’d re-hire them in a heartbeat.”
Kelly added, “And we called it unexpected?”
Lena nodded again.
Daniel exhaled. “So what changes?”
“We stop rewarding invisibility,” Kelly said. “We intervene before exhaustion turns into exit planning.”
“And if managers resist?”
“They will,” Kelly replied. “That’s how you know it’s real work.”
The Aftermath
Nothing blew up. No Slack threads. No announcements.
But a few weeks later, something shifted.
A high performer asked for help earlier than usual.
Another declined a stretch project without apologizing.
A manager flagged a team that had been running hot for too long.
Maya stopped by Kelly’s desk. “You know what’s different?”
Kelly smiled faintly. “We didn’t wait for permission from the data.”
The Pattern
Burnout doesn’t announce itself with disengagement and your top performers don’t wait for you to interpret lagging indicators. High performers don’t raise red flags. They lower their expectations of how long they can last.
Predictive HR isn’t about better dashboards.
It’s about noticing drift before damage.
If you wait for clean data, you’re already late.
Kelly Recommends
If you want to catch burnout early, look beyond scores:
Watch who stops pushing back.
Notice who absorbs work without visibility.
Read how 1:1s are changing, not just how they’re rated.
The future usually whispers before it breaks.
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