Climbing the Staircase of People Analytics: Why Every Step Matters

MARIA NOLAZCO MASSON

MARIA NOLAZCO MASSON

— 3 min read

Introduction

Data has become one of the most powerful assets in modern HR, driving better decisions, stronger strategies, and a more informed understanding of the workforce. But effective People Analytics is not about jumping straight to predictive models or advanced dashboards. It’s about walking—firmly and intentionally—through each step of a staircase, where each level builds the foundation for the next.

In this article, we’ll explore what that staircase looks like, why you can’t skip steps, and how to build a resilient, scalable People Analytics practice grounded in data integrity and strategic insight.

The People Analytics Staircase: An Overview

Imagine a staircase with five levels:

  1. Data Collection – Capturing accurate, consistent employee data
  2. Data Quality & Management – Cleaning, validating, and structuring that data
  3. Descriptive Analytics – Understanding what happened and identifying patterns
  4. Diagnostic & Predictive Analytics – Understanding why it happened and forecasting what’s next
  5. Strategic & Prescriptive Insight – Using data to shape strategy, guide decisions, and influence outcomes

Each step depends on the one before it, and trying to leap forward too soon risks building insights on an unstable foundation.

Step 1: Data Collection – Capturing the Right Information

Before you can analyze anything, you need reliable input. This starts with:

  • Clean and structured HRIS data
  • Accurate headcount, job changes, compensation records, and employee lifecycle events
  • Survey responses and engagement data
  • Time and attendance tracking
  • Learning and performance management inputs

Many companies skip this step or assume it’s complete because "we have an HR system." But without consistent data entry processes, you’re already compromising everything that follows.

Step 2: Data Quality & Management – Cleaning, Structuring, and Owning It

Raw data is never ready for analysis. It needs to be:

  • Cleaned (no duplicates or outdated entries)
  • Merged across sources
  • Stored securely and ethically
  • Maintained with a clear governance model

Walking firmly here means building a culture of data ownership across HR teams and ensuring regular audits, definitions, and clear documentation.

This is where trust in the People Analytics function is built—or lost.

Step 3: Descriptive Analytics – What’s Happening in Our Workforce?

Now, with clean data in place, you can begin to answer foundational questions:

  • What is our turnover rate?
  • How does engagement vary across teams?
  • Where are we losing people in the first 6 months?
  • How many internal moves are we seeing year over year?

These questions are not complex, but they are highly valuable—especially when paired with visualization tools and regular reporting rhythms. This step enables better conversations between HR and leadership.

Step 4: Diagnostic & Predictive Analytics – Why Is It Happening, and What Might Come Next?

This is often where organizations try to jump too soon. But only with a strong foundation can you begin to ask:

  • Why are high performers leaving one specific function?
  • What are the leading indicators of early attrition?
  • Which teams show engagement dips before turnover spikes?

Predictive modeling adds immense value—but it’s only trustworthy if the inputs are clean, well-defined, and understood. Otherwise, the model’s output becomes just another guess with a more complicated wrapper.

Step 5: Strategic & Prescriptive Insight – Using Data to Drive People and Business Strategy

At the top of the staircase, People Analytics is no longer just a reporting function. It becomes a business enabler—fueling workforce planning, budget allocation, DEI strategy, and leadership development.

At this level, you’re answering questions like:

  • Where should we invest in upskilling based on upcoming business needs?
  • Which locations or functions are over-resourced or under-leveraged?
  • What’s the ROI of internal mobility initiatives vs. external hiring?

When built step-by-step, these insights are not just technically impressive—they’re actionable, trusted, and connected to business value.

Final Thoughts: Walk Each Step, Don’t Leap

People Analytics is not about speed—it’s about intention, clarity, and trust. Each step of the staircase matters.

  • Skipping the groundwork leads to bad insights and lost credibility.
  • Taking the time to build each level ensures data becomes a true strategic asset, not just a dashboard.

The most effective People teams understand that the goal is not the tool or the output—it’s the question, the decision, and the impact.

So ask yourself: Which step are we on today, and how can we move forward—deliberately and confidently—to the next?

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