How to Use Metrics to Track Improvement Progress

A lot of people think HR is hard to quantify. They’re not wrong. But they’re not entirely right either. You have to translate fuzzy terms into sharp metrics. “Improved employee experience” → Moved engagement scores from the 50th to the 25th percentile “Better hiring process” → Increased offer yield by 20% and reduced time to fill by 10 days The key? Track what matters—and explain why it matters in business terms. Here are a few of my go-to People KPIs and how I frame them: 📉 Time to Hire Why: Signals candidate experience + hiring velocity Target: <30 days from application to signed offer Tip: Track by recruiter, hiring manager, and role to surface friction 📈 Offer Acceptance Rate Why: Measures whether your comp, brand, and process are landing Target: >85% accepted offers Tip: Segment by source and team to spot drop-offs 🧭 Voluntary Regrettable Attrition Why: When your best people leave, it's a signal—not noise Target: <15% annually (varies by industry and average tenure) Tip: Cut by team, tenure, and manager to uncover hotspots 🌟 Talent Mobility Rate Why: Internal movement = career growth + retention Target: >15% promoted or transferred annually Tip: Combine with development plan adoption to build a stronger pipeline 💬 Employee Engagement (eNPS + Pulse) Why: Predicts performance, CX, and attrition risk Target: eNPS >30; Pulse trending up Tip: Segment by manager, function, and identity group Metrics like these turn HR from a gut-feel function into a strategic advantage. What are your favorite People KPIs? I’d love to hear what you’re tracking—drop your best one below 👇

Your dashboards are green but your problems keep getting worse. You're tracking revenue per employee, units produced, and efficiency percentages. All trending upward. But customers still complain about quality. Equipment still breaks down unexpectedly.   Operators still struggle with changeovers. Here's why most metrics miss the mark: They measure what happened yesterday. Not what will happen tomorrow. They focus on outputs. Not the inputs that create those outputs. These 8 KPIs actually predict and prevent problems: 1. OEE (Overall Equipment Effectiveness) Shows equipment reality, not just availability 2. First Pass Yield Reveals true process capability 3. Total Cost of Quality** Captures the real price of problems 4. Employee Suggestion Implementation Rate Measures engagement that drives improvement 5. Setup/Changeover Time Determines your flexibility advantage 6. Supplier Quality Performance Prevents problems at the source 7. Safety Leading Indicators Predicts incidents before they happen 8. Customer Complaint Resolution Time Shows responsiveness that builds loyalty Each metric drives specific behaviors. OEE pushes systematic waste elimination. First Pass Yield forces quality at the source. Cost of Quality makes prevention profitable. The best manufacturing teams measure fewer things. But they measure the right things. And they act on every single number. Stop measuring your past. Start predicting your future. Question for you: If you could only track one KPI for the next 90 days, which would drive the biggest change?

Most HR teams are drowning in vanity metrics that don't actually solve problems. Here's the framework Jessica Z. uses to cut through the noise: --- 1. Health Metrics (What's happening now) - Headcount - Sick days per month - Basic attrition rates These tell you where you are, not where you're going. --- 2. Operational Metrics (Your team's SLAs) - Time to fill roles - Interview-to-hire conversion - Probation pass rates Track these consistently to spot trends and improve processes. --- 3. Success Metrics (Problem-solving mode) This is where it gets interesting.  You identify a specific problem, create a hypothesis, then track metrics to test it. --- Real example from data: People with "strong" interview feedback kept failing probation. Wait, what? 🤔 Problem statement: Their interview process isn't predictive of actual performance. Hypothesis: Interviewers are giving inflated positive feedback. Success metric: Distribution of interview scores (they wanted a normal bell curve, not everyone getting 8-10/10) --- They tracked: • Health: Overall attrition • Operational: Probation pass rates • Success: Interview score distribution Result? Found interviewers were afraid to give honest feedback. Fixed through calibration training. --- Most teams only track the first two buckets. The magic happens in bucket three - where you actually solve problems instead of just measuring them. 📎 Full convo with Jessica (and more metric breakdowns) linked in the comments. #PeopleMetrics #HRAnalytics #DataDrivenHR #PeopleOps #HiringInsights