Most HR SaaS platforms get sold on features. They should be evaluated on data. Here are the 12 metrics that tell you whether your HR tech stack is working.
Why Metrics Beat Features
Vendor demos are optimized to impress, not inform. You see the best-case UI, cleanest data, smoothest workflows. What you do not see is whether the platform actually improves outcomes that matter. The right set of KPIs lets you evaluate your current stack objectively, benchmark against industry data, and make the internal case for new investments or replacements.
Recruiting Efficiency
1. Time to Fill
Definition: Calendar days from job requisition approval to offer acceptance. Benchmark: 36-42 days for knowledge workers. What it tells you: Pipeline velocity. High TTF usually indicates insufficient sourcing volume, stage bottlenecks in scheduling or feedback collection, or unclear hiring criteria causing restarts. If your ATS does not surface stage-level time data, you cannot diagnose where the slowdown is.
2. Offer Acceptance Rate
Definition: Percentage of offers extended that are accepted. Benchmark: 85-90% is healthy. Below 75% signals a problem. What it tells you: Alignment between what the role was sold as and what candidates experienced in the process, plus competitiveness of comp. A declining OAR is often the first leading indicator of a compensation problem.
3. Sourcing Channel Efficiency
Definition: Hire rate and cost per hire by sourcing channel. What it tells you: Where your recruiting budget is going vs. where your hires are coming from. Most talent teams are surprised to find employee referrals generate 2-3x the hire rate of LinkedIn at a fraction of the cost. Requires your ATS to capture source data consistently at application.
4. Pipeline Conversion Rate by Stage
Definition: Percentage of candidates advancing from each stage to the next. What it tells you: Where in your funnel you are losing candidates and whether those losses are by design (filtering) or by default (drop-off, ghosting, slow process).
Quality of Hire
5. New Hire Performance Rating at 90 Days
Definition: Manager assessment of hire performance at first formal review, expressed as percentage meeting or exceeding expectations. What it tells you: Whether your selection process is identifying candidates who actually perform. This is the most direct signal of recruiting quality and the most underused metric because it requires connecting ATS data to performance system data.
6. New Hire Retention at 12 Months
Definition: Percentage of hires still employed at their one-year mark. Benchmark: 85% is healthy. Below 75% warrants investigation. Early attrition costs 50-200% of annual salary depending on role and is largely preventable.
7. Hiring Manager Satisfaction Score
Definition: Survey score from hiring managers on their recruiting experience, collected 2-4 weeks after a hire closes. Low scores usually indicate communication gaps, slow pipeline, or poor candidate quality.
Retention
8. Voluntary Attrition Rate
Definition: (Voluntary departures / Average headcount) x 100, annualized. Benchmark: 8-12% is typical in stable tech orgs in 2024-25. Your HRIS should calculate this automatically. If you are doing it in a spreadsheet, that is a data infrastructure problem.
9. Flight Risk Score Accuracy
Definition: If using AI attrition prediction, what percentage of employees flagged high-risk actually leave within the predicted window? Most vendors do not publish validation data. A model with 55% precision is barely better than random and can cause harm if driving management decisions.
Platform Adoption
10. ATS Active Usage Rate
Definition: Percentage of open requisitions with meaningful activity in the past 14 days. Low adoption is the number-one reason ATS data is unreliable. The real pipeline living in spreadsheets and inboxes is the tell.
11. Structured Interview Compliance Rate
Definition: Percentage of interviews where a structured scorecard was completed before a hire or no-hire decision was logged. Most orgs that have scorecards have low compliance. Structured interviewing only works if people actually use it.
12. HRIS Data Completeness Score
Definition: Percentage of employee records with all required fields populated. Every people analytics use case depends on clean, complete HRIS data. Incomplete records are the root cause of most people reporting failures and they accumulate silently.
Building Your Metrics Dashboard
- Months 1-2: Get Time to Fill, Offer Acceptance Rate, and Voluntary Attrition calculating reliably.
- Months 3-4: Add Sourcing Channel Efficiency and Pipeline Conversion by Stage.
- Months 5-6: Close the loop with New Hire Performance and Retention at 12 months.
- Ongoing: Add platform adoption metrics as you enforce usage standards.
Bottom Line
The goal is not dashboards. It is decisions. If your current stack cannot produce most of these metrics without a manual export and a spreadsheet, that is your argument for why it needs to change.