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6.1: Why It Matters: People Analytics and Human Capital Trends

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    46994
  • Why learn about people analytics and human capital trends?

    Illustration of a woman standing in front of a chart. The chart shows two lines with a generally upward trajectory.

    The quantity of “big data”—data sets that are too large or too complex for traditional data processing applications[1]—is growing exponentially. By 2020, it’s estimated that 1.7 MB of data will be created per second for every person on earth.[2] In 2019, the size of the “global datasphere,” or quantity of new data captured or created globally,[3] is projected to be 41 zettabytes. By 2025, that number is forecast to be 175zettabytes. To put this in perspective, see Cisco’s Visualized: A Zettabyte graphic.

    Well . . . so what? Consider this: What if, instead of simply reporting human resource metrics and attempting to trouble-shoot a “black box,” you applied predictive analytics to employee data to identify probable causes and change outcomes? And that is precisely what Experian did when faced with a turnover challenge.

    Turnover and Data

    In 2016, Experian’s global human HR management found that the company’s resignation rates were 4% over the industry benchmark.[4] This was not only a staffing issue; the company determined that every 1% increase in turnover cost the business approximately $3 million and that the churn was constraining growth and innovation. Additionally, higher turnover diverted HR staff from core culture- and employee-building initiatives.

    In order to identify employees who were a flight risk, Experian built a predictive model that factored in 200 attributes, including team size and structure, supervisor performance and commute distance.[5] The model identified both risk factors and flight risk triggers, one of the latter being a move that increased the employee’s commute. Analytical insights, combined with good management practices, allowed management to address issues on both an individual level and at scale. Business impact: attrition was reduced by 4% globally, saving the business $14 million over two years. Experian Group HR Director Mark Wells observed that applying analytics not only saved the company millions, it has become “the backbone of how we make the best decisions for our people. We’re now better able to anticipate and predict what our employees value and that’s helped us to retain talent that keeps Experian innovating.” Experian has also turned their predictive model into a “Workforce Analytics for Retention” service.

    Being able to see into the black box of employee motivations and behavior is powerful. However, the ability to change HR outcomes is transformational. In this module, we’ll explore that potential, including people analytics and human capital trends and implications.


    1. Van Vulpen, Erik. "15 HR Analytics Case Studies with Business Impact." AIHR Analytics. July 30, 2019. Accessed August 06, 2019.
    2. "Data Never Sleeps 6.0." Domo Resource. Accessed August 06, 2019.
    3. "Global DataSphere." IDC. Accessed August 06, 2019.
    4. "Case Study: Experian Predictive Workforce Analytics." Experian. 2019. Accessed August 06, 2019.
    5. Van Vulpen, Erik. "15 HR Analytics Case Studies with Business Impact." AIHR Analytics. July 30, 2019. Accessed August 06, 2019.
    CC licensed content, Original
    • Why It Matters: People Analytics and Human Capital Trends. Authored by: Nina Burokas. Provided by: Lumen Learning. License: CC BY: Attribution
    CC licensed content, Specific attribution