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Hiii y'all,

Woo, we made it to Wednesday! Goodbye for now, September. 👋

I don’t know if it’s the weather change or something in the air, but TBH I’m not really feeling it so far this week.

That’s totally okay though, because judging by the general energy out there…I don’t think anybody else is either. Love that for us! 😅

Maybe that’s why today’s lead story hit a nerve: people are accepting one job and finding out they’ve apparently been hired for its weird, much busier cousin.

We’re getting into that, plus my convo with Doug Melton about what happens after you collect all that people data, and why employees are giving AI in payroll a very reasonable side-eye. 👀

Time to dig in!

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🗞️ Here's the Tea:

😒 Workers say they are frustrated by bait-and-switch job descriptions

The TL;DR: In a survey of more than 1,000 U.S. employees, 18% said their current job is significantly different from the one they were hired to do. 1 in 5 said their day-to-day expectations are often unclear or unpredictable!!! The job description apparently had a plot twist…surprise!

My POV: Most people can accept that jobs change, but if the role shifts and nobody tells the person doing it, how do you think that affects trust??? 👀

HR should check whether or not hiring managers are describing the work accurately, then make sure employees hear about changes before they discover them by opening their inbox on Monday.

🎙️Mic Drop Moment:

“There is no universal single decision on how to optimize employee performance.”

On the mic this week: Doug Melton is the Global Chief Commercial Officer for Human Capital at Aon, where he uses data to examine employee health through performance and retention,. This ultimately shapes how he makes consequential decisions without perfect information.

Pin this:

• Get leadership to agree on the question and what they’d be willing to do with the answer.

• More data won’t rescue a decision nobody wants to make.

• Test your assumptions about what employees need…one benefits package won’t motivate everyone the same way.

• Go back and measure whether your people initiative worked. Yes, even after launch.

My H*ly Sh*t Moment: One of the biggest tests of a data-driven culture is what leaders do when the data recommends something inconvenient!

▶️ Press Play

📊 Data Is My Love Language:

Stat: Nearly half of workers say they don’t want AI in payroll

My spiral: Payroll is a funny place to ask employees to trust a tool they can’t see.

People might tolerate AI drafting a meeting recap, but their paycheck is where system mistakes stop being a funny little tech hiccup!

I’d want employees to know exactly where AI is involved and have a real person they can reach if their pay ever looks wrong.

This is another area where trust can be broken in an instant if we’re not thoughtful about how we implement tech!

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• John Baldino: How to own mistakes, repair trust, and stop calling unresolved conflict handled.

• Jessica Winder: What it’s like in HR’s loneliest seat, and what this moment is asking of us.

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🗣️ UNMUTE YOURSELF

Think about the opinion you usually save for the walk back to your car after an HR event.

You prob have a spicy take on something that you’d defend if somebody pushed you on it!

What’s one workplace belief you hold that most HR people would disagree with?

🛠️ TRY THIS TOMORROW:

I think it’s common practice now to default to the idea that the right tech can solve all of our problems.

I also think there are problems out there that can’t be solved this way! Taking the time to figure out the difference is worth it:

In your next leadership meeting, ask: “What problem are we pretending technology can solve?”

👂 OVERHEARD IN SAFE SPACE

This has been a surprisingly controversial topic on LinkedIn, so I would be curious what the consensus is among HR folks! 👀

Read what members had to say here.

See ya on Friday!