Business leaders say they want data. HR teams work hard to deliver it. But when we finally show up with the numbers, something strange happens:
“We don’t trust the data. We don’t agree with it.”
💥Just like that, the conversation shifts.
Not toward workforce planning, not toward decisions — but into an endless loop of questioning accuracy, challenging sources, and undermining insight.
🔍 It’s Not Just HR
Let me be clear—this isn’t unique to HR. Marketing teams, product teams, even finance sometimes face the same issue. I’ve seen marketing dashboards questioned over attribution logic. I’ve seen sales leaders debate CRM numbers until no one remembers the actual goal.
But HR feels it more acutely, because people data has historically been treated as “soft.” And once trust is lost, even the most insightful analysis is dismissed.
🎯 The Purpose of People Analytics
Let’s be clear: the point of People Analytics is not to produce perfect numbers.
It’s to drive better business decisions.
Forecast workforce needs.
Spot retention risks.
Support org design.
It’s not about reporting for the sake of it. It’s about impact— People Analytics is a decision-enabler. It provides context, trends, and direction. It doesn’t have to be flawless to be useful. But too often, we aim for perfection — and get stuck.
📉 The Trust Problem
I’ve seen it myself: a solid dashboard, well-presented, instantly shot down.
Not because the insight is wrong.
But because someone remembers a number being slightly different two months ago.
It’s frustrating. But it’s real.
🔹 Only 37% of business leaders fully trust HR data (Gartner)
🔹 Over 50% executives still view ~60% of their workforce data as “not consumable” (Dayforce)
Many leaders default to gut feel, even if their decisions contradict what the data says.
Why?
Because data trust isn’t built by logic.
It’s built by experience.
When the first few dashboards feel inconsistent, trust erodes.
And every future insight walks in with a credibility deficit.
⚠️ The Risk of Over-Critique
Of course, healthy challenge is welcome.
We should ask where numbers come from.
We should want to improve data quality.
But here’s the line:
If every discussion becomes about the numbers themselves, instead of what they tell us — we’ve missed the point.
When leaders pick at decimal points or sample sizes, rather than asking “What should we do about this?” — the analytics loses power.
Worse, the HR team stops bringing insights forward.
Why present anything if it’s going to be torn apart?
🧭 Directionally Correct > Perfect
Let’s be honest: perfect data is rare.
Different systems, shifting definitions, messy inputs — they’re part of the job.
In many cases, demanding perfection is a subtle form of resistance. When we get stuck in debates about decimal points, we avoid talking about uncomfortable truths:
- Your top talent is leaving.
- Your succession pipeline is empty.
- Your hiring funnel is broken.
We’re not presenting data to win a compliance prize. We’re presenting it to provoke reflection and inform decisions. Sometimes “good enough” data that points to a trend is exactly what we need to take action.
Think about it: if the high performer attrition rate is 15.2% vs 14.9% — does it materially change the decision to investigate turnover drivers? Probably not.
🔮 How We Rebuild Trust
So how do we stop the cycle of doubt?
Here’s what works in my experience:
1. Set expectations early: Frame data as directional, not definitive. Say it out loud: “This gives us a strong signal, not an absolute answer.”
2. Co-create metrics with business leaders: Let them help define what matters. When they’re involved in building it, they trust it more.
3. Be transparent: Show definitions, explain calculations, share limitations. Trust grows when people see behind the curtain.
4. Link to business goals: Don’t just present the data — present the implications. “Here’s what this means for cost, revenue, growth, risk.”
5. Build Data Literacy in HR and Beyond: If HR doesn’t understand the numbers, how can we expect leaders to? Upskilling teams in analytics, dashboards, and interpretation is key. Confidence builds credibility.
6. Keep showing up: Trust builds through repetition. Reliable insights, delivered consistently, start to shift perceptions.
7. Empathize with Skepticism — Don’t Fight It: When someone challenges your data, don’t go on the defensive. Ask: “What part doesn’t sit right with you?” or “What would make this feel more reliable?” Use the challenge as a clue, not a conflict.
🚀 Final Word: Don’t Let Perfection Kill Progress
If we want people analytics to be taken seriously —we need to lead with humility, transparency, and business relevance.
Yes, clean data matters. But so does trust, context, and how we show up as strategic partners.
Because at the end of the day, our job isn’t just to build dashboards.
👉 It’s to help the business make better decisions about its most important asset: its people.
And that starts by making trust the default—not the exception.
📩 Want to stay ahead of the curve?
If you found this useful, subscribe to my People Analytics Insider newsletter for:
- Exclusive case studies (like the bias audit we did for a Fortune 500 company)
- Templates (data governance checklist, HR metrics guide)
- Deep dives on turning analytics into action
🚀 Ready to upgrade your people analytics in your firm? Let’s check out the HR metrics you should be tracking
