Best Practices in People Analytics

Learning Outcomes

  • Identify people analytics best practices
Two people sitting in front of a screen with charts and diagrams on it.

People analytics expert Patrick Coolen has been researching and validating people analytics best practices for a number of years. In a LinkedIn post, he presents a crowd-sourced version of the 10 Golden Rules of HR Analytics. We have selected a few key highlights below.[1]

Focus on business relevance

Focus your research on critical business issues. For example, consider what keeps executives awake at night? To be able to generate relevant questions, ask business leaders to identify challenges and opportunities. Also confirm their willingness to act on the research findings—regardless of their agenda or interests.

Generate actionable insights

Insights are of no value if the organization fails to act on them. What group is responsible for implementation and evaluation depends on the organization, but developing consultancy skills and an ability to speak in business terms—and craft a compelling story—will likely improve success.

Involve legal & compliance

Work with your legal department or representative to ensure compliance with privacy legislation, contracts and other regulations. Specifically, it’s a good practice to request legal approval for projects and review of results prior to release. At a minimum, be clear on the goal of the research and aware of what data—or at what level (e.g., individual)—data is off limits.

It’s a process

Understand that analytics is a process. It takes time to hone in on the research question, develop the model and select and validate data, etcetera. In fact, these preliminary steps can consume 75% of the project timeframe.

Illustration of four arrows in a row

Lesson learned: don’t set a delivery date until you’ve confident you can deliver. For perspective, here’s Coolen’s 4-step approach to the people analytics process:[2]

  1. Intake and Design
    • Contracting senior management
    • Contracting legal
    • Determine business question
    • Determine data sources
    • Approving research proposal
  2. Data Cleaning
    • Data collection
    • Connecting datasets
    • Descriptive analyses
    • Design models
  3. Data Analyses
    • Run models
    • Discuss intermediate results
    • Decide on extra analyses
    • Run final models
  4. Sharing Insights
    • Discuss final models
    • Interpret insights
    • Create business presentation
    • Discuss with business
    • Advise business on insights
    • Incorporate insights in strategies or activities

Success requires balance

HR analytics success requires a team with a blend of capabilities and skills, including an understanding of business challenges, HR processes and technology and analytical and consultancy skills. A defining capability is curiosity.

Learn More

For a visual perspective, see Coolen’s capability wheel diagram in his “A practitioner’s view on HR analytics” post.

Practice Question

  1. Coolen, Patrick. "The 10 Golden Rules of HR Analytics (crowd Version)." LinkedIn. September 16, 2016. Accessed August 06, 2019.
  2. Ibid.