Talent Analytics

5 Truths about Workforce Analytics

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At HR Tech World in Amsterdam this week, David Green shared our latest insights into the analytics readiness of organizations in Europe and the rest of the world. You can see how your organization stacks up in terms of workforce analytics readiness in our white paper: HR analytics readiness: How does Europe compare to the rest of the world?

This research got us thinking about the broader role of both analytics and the workforce. We’re living our working lives in a mixed reality that presents remarkable opportunities along with unprecedented challenges. Opportunities are coming from digital technologies. You can now start watching your CEO give an all-hands broadcast on your MacBook, leave work and carry on where you left off on a mobile device, just like with Netflix and Amazon Prime. Intranet comments on the presentation can be quickly distilled into a report so the CEO can gauge reactions. Opportunities like this abound for those who rapidly integrate technology into work routines and realize there is no finish line for digital transformation.

Challenges come from more threatening operating conditions. Environments that were once simple, stable and munificent are now complex, dynamic and threatening.(1) The average life of an S&P 500 company in the 1920s was 67 years, today it is just 15 years.(2) Much of the turbulence is caused by political uncertainty from events like Brexit. But it is also caused by digital technologies like cryptocurrencies, blockchain, and platform based market places like Amazon, Uber, and Airbnb that disrupt industries.

To compete effectively firms should cultivate assets with four qualities: assets need to be valuable, rare, hard to imitate, and difficult to substitute.(3) The best examples were once thought to be physical: land, buildings, and factories. Today people are also considered to be among the best examples. People are harder to manage than physical assets. Buildings and factories have predictable lives over the course of which value is amortized. But people perform variably, and leave when they’re not happy. They are not assets under generally accepted accounting principles.

HR needs to reach a place where workers are more predictable, and workforce analytics can help. In the book, The Power of People: Learn how successful organizations use workforce analytics to improve business performance, we discussed how to get started. Our new paper with HR Tech World examines the readiness of HR to deliver workforce analytics projects. Notwithstanding availability of great advice, there’s no guaranteed path to success in analytics beyond general mantras such as ‘focus on the business not, on HR.’ What’s best depends on context. This left us asking what points about analytics we do consider generalizable and ‘true.’ We came up with five, and list these realizing they might be mildly provocative.

Truth #1. You don’t always need analytics in HR

This is true when you’re dealing with standard problems. What candidate attributes should I focus on in a selection? What are the determinants of turnover? It is unlikely your local studies will overturn decades of research in journals like Personnel Psychology. Sometimes an opinion might even be preferred over analysis when the two disagree, depending on whose opinion and whose analysis you are comparing. Some people’s intuition about data can be better than other people’s actual analyses.

Truth #2. Research design compromises are the most expensive of compromises

Decisions about workforce analytics projects are based on considerations of politics, expedience, and rigor. Research design compromises are often the first to be made, but they turn out to be the hardest to recover from. If the research design is not strong, no amount of statistical sophistication will save you. There is a hierarchy of effectiveness when it comes to research designs that allow causal conclusions (a term used loosely here). We summarize the hierarchy in our Decoding Workforce Analytics white paper.

Truth #3. The utility of data on workers in HR analytics is inversely related to its novelty

New measurement approaches like wearable technology are now infiltrating HR. As indicators of observable variables like geographic location or counts of widgets produced, these technologies work well. As measures of psychological attributes like emotions their effectiveness is unclear. For this reason, novelty should invite scrutiny. To illustrate, consider a questionnaire measuring emotion compared to a wearable wristband measuring emotion. The questionnaire gets a low novelty value and the wristband gets a high novelty value. Truth #3 reverses the ordering when it comes to utility, so the questionnaire has more utility than the wristband.

Truth #4. You can’t influence your workforce without knowing who they are.

Knowing your workers, in terms of their knowledge, skills, abilities, and other attributes is critical in workforce analytics to improve firm performance.(4) Without this information, you cannot effectively align workers with appropriate roles and opportunities, compose teams based on skills similarities and differences, and make effective predictions about the future performance of your workforce. The best way to get information on your workforce is through standardized psychometric tests measuring general mental ability, personality, interests, and work competencies. This information can then be used for workforce analytics efforts at individual, team, and organizational levels of analyses.

Truth #5. Workforce analytics need to involve transparency and two-way influence

Workforce analytics involves influencing worker behavior to improve outcomes for workers and organizations. Organizational development experts understand that the best way to get a large group of people to behave differently is to involve them in decision-making processes. This is especially relevant for workforce analytics efforts in HR where employee interpretations about organizational intentions will play a significant role in determining cooperation. To maximize cooperation between organizations and workers in workforce analytics, involve workers in your decision-making processes.

With these truths in mind and the desire to embrace workforce analytics firmly in place, attention can be turned to assessing your readiness for bringing analytics to your HR function. See how you compare. Download the new IBM Smarter Workforce Institute white paper: HR analytics readiness: How does Europe compare to the rest of the world?


(1) This description of environments borrows from the strategy literature, for example. Miller, D., & Friesen, P. H. (1983). Strategy‐making and environment: the third link. Strategic Management Journal, 4(3), 221-235.

(2) Foster, R., & Kaplan, S. (2011). Creative Destruction: Why Companies That Are Built to Last Underperform the Market–And How to Successfully Transform Them. Crown Business.

(3) Barney, J. B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view. Journal of management, 27(6), 643-650.

(4) Ployhart, R. E., & Moliterno, T. P. (2011). Emergence of the human capital resource: A multilevel model. Academy of Management Review, 36(1), 127-150.

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