Where do you stand?

McKinsey’s foundational article “How to be great at people analytics” offers a helpful matrix to locate your current stage.

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Stage 1: Poor data

Characteristics:

• No HR software
• No data governance policy
• Low‑quality, inconsistent data

How to reach Stage 2

• Implement core HR tools: ATS for recruiting, HRIS, payroll, performance, learning, and eNPS/climate surveys
• Adopt a clean, organized approach to data collection

Stage 2: Good data

Characteristics:

• You’re becoming data‑driven and see the need to track data more precisely
• Access and analysis are still difficult and ad‑hoc

Observation:

• Most SMEs and mid‑market companies (up to ~5,000 employees) are here—motivation is high, but processes and reporting have gaps

How to reach Stage 3

• Deploy reporting and analytics technologies

Two paths:

• Build internally (Excel or BI tools)
• Use a specialized solution like Reflect

Stage 3: Strong data

Characteristics:

• Dashboards and indicators are reliable, accessible, actionable, automated—and shareable

Sharing matters:

• Data sensitivity is a real HR constraint. At this stage, share relevant indicators with stakeholders (executives, Works Council/CSE, employees, investors) for their respective scopes.

How to reach Stage 4

Once you’ve mastered automated, descriptive reporting, you can develop advanced analytics.

Stage 5: Reliable predictions

Reality check:

• McKinsey experts rarely see teams fully succeed at this last stage. It requires big data, machine learning, and predictive modeling at scale.

Aim:

• Extremely granular analysis of massive datasets to recommend precise actions.

Example:

• “Increase Paul’s salary by €1,200 and move him to Sales under Caroline Jean; otherwise, he is likely to leave in eight months.”