“Done right, people analytics allows you to keep your people and your organization successful and effective, even in a constantly changing environment.”

Quote from MIT’s “People analytics, explained” (2020) by Tam Harbert. One barrier to using HR data in decision‑making is the lack of a simple methodology. Recent trends—especially AI—can blur the lines and push companies to either do nothing or rush ahead without foundations.

1. What question or problem are you solving?

A problem is a gap versus a standard. Before calling it a problem, define why it is one—against a target or OKR. Example: you set a quarterly attrition ceiling of 10%. If you’re at 15%, that’s a problem.

You won’t analyze the same data for different issues. If hiring is slow, look at speed and process quality. If exits are high, analyze retention metrics like attrition or tenure.

2. Collect and analyze the right data

Avoid bias: “Identify and gather the variables needed to properly test your hypotheses, while accounting for alternative key factors.” — Tam Harbert

Common approaches:

• Manual extraction: pull data from HR tools and compile in spreadsheets.
• Business Intelligence tools: involve technical teams to extract from HR systems into analytics platforms.
• Plug‑and‑play HR analytics: platforms like Reflect let non‑analysts explore and interpret data.

3. Share the results

Don’t keep insights to yourself. Share with:

• Your team: train colleagues and gather feedback.
• Leaders: people topics sit high on the corporate strategy agenda.
• Managers: they’re your best internal relay.

Use the PISCAR format:

• Problem identified
• Impact on the company
• Standard/Objective not met
• Causes
• Actions
• Results

4. Take action and track consequences

Implement actions based on analysis, then monitor outcomes. Example: if inflexible work conditions drive exits, introduce flexible remote work and measure the effect.

Data analysis legitimizes, strengthens, and demonstrates the effectiveness of HR decisions.

5. Our view of HR data

Simplicity, Accessibility, Sharing.

Terms like people analytics or HR data analysis ultimately reflect a simple need: understanding what’s happening in your organization.

When we built Reflect, we focused on:

• Simplicity: analyze the right indicators for the right topic to surface insight in seconds. Example: turnover linked to probation‑period breaks in Sales; X salary increases in Q1; recruiting speed dropped after a key departure.
• Accessibility: smooth UX for users without a data‑analyst background. BI tools often require weeks of training.
• Sharing: transparency and knowledge transfer. HR was long misunderstood; today managers and leaders need training on people topics. Sharing actionable indicators—like team salaries—builds autonomy and accountability.