|
In Q4 of last year, an HR leader I know attended a tense performance review meeting. One engineering manager wanted to give an employee an 'exceeds expectations' rating because their output had doubled. Another manager disagreed, pointing out that the increase was just from using ChatGPT, while the employee's poor design choices had caused two production errors. Because the team lacked a framework to resolve this kind of conflict, the discussion quickly broke down into an argument about fairness. If you haven't faced this situation yet, you will soon. In an AI-driven workplace, performance reviews often turn into arguments your current goal system can't solve. I recently published a four-part framework covering outcomes, verification, judgment, and capability in this article. In this edition, I'll focus on how to guide your team through the goal-reset process in the AI era. Both Managers Are Right and That’s the ProblemMost performance disputes moving forward will boil down to the same issue: your goals measure output volume, but AI has taken over most of that work. One manager looks at the numbers while the other looks at the decisions behind them. Both are right, yet they are describing the same employee. Until the goals change, you will keep settling disagreements that have no correct answer in your current performance system. Stop trying to resolve these disputes during the review cycle. You cannot fix a broken measurement system through calibration. Instead, acknowledge that your current system is transitional, document where the goals failed, and use that data to drive your reset. The Reset Is a Change Program, and You Own ItRolling out new goal categories is simple; managing the change is hard. When you reset targets, your team will worry that you're just raising the bar to justify layoffs. In today's climate, that's their default assumption. Here is how to handle it:
What This Does for Your Seat at the TableDo this right, and you’ll earn more credibility than any other project you deliver this year. You’ll head into executive meetings armed with role-specific productivity data that no one else has. You’ll know exactly who is worth promoting. And when the board asks how AI is affecting your output, you’ll have a clear, evidence-based answer. This changes the conversation during headcount planning, allowing you to make strategic decisions about funding growth rather than just making reflexive cuts. Action Items for This Week
That’s it for this week. If you are in the middle of a reset and hitting roadblocks, just hit reply and let me know where you are stuck. I read and respond to every email. |
I help 7-figure companies become 9-figure ones by turning HR into rocket fuel for their growth. Subscribe to my free bi-weekly newsletter to learn how.
The People Platform that Lives Where Your Team Work Measure engagement, recognize great work, run reviews, and automate the HR busywork. Native to Slack and Microsoft Teams. Modular. Try it free in 60 seconds, no sales call required. Start free now Read on my website The criteria I Use Before Deploying Any AI Tool in HR I ran a workshop recently where I built a working HR AI chatbot in about 20 minutes, live, in front of a group of HR people. None of them had ever built an AI tool before....
Read on my website The People Platform that Lives Where Your Team Work Measure engagement, recognize great work, run reviews, and automate the HR busywork. Native to Slack and Microsoft Teams. Modular. Try it free in 60 seconds, no sales call required. Start free now When a Manager Asks You to Fire an Underperformer In 2022, I was the VP of HR at a 65-person gaming peripherals company when the CMO called me and said he wanted to fire his Paid Ads Specialist (let’s call her Jennifer). The...
Read on the website The last two editions of this “layoff analysis” series covered Block's 40% cut and Atlassian's 1,600-person restructuring. Both generated incredible feedback and conversations, so I'm keeping this going. This time, Snap is in the hot seat. If Block was a story about overhiring and Atlassian was a story about a broken cost structure, Snap is something worse: a company that keeps making the same workforce planning mistakes over and over again, repackaging each round with a...