I have argued over the past decade that the Human Resources (HR) function has the potential to become one of the leaders in analytics. The key word, I thought, was potential. Not anymore. A recent global survey on which I collaborated with Oracle suggests that HR is right up there with the most analytical functions in business — and even a bit ahead of a quantitatively-oriented function like Finance. Many HR departments are making use of advanced analytical methods like predictive and prescriptive models, and even artificial intelligence.
This is a big change from a decade ago, when I began to study the use of talent analytics. (Jeanne Harris, Jeremy Shapiro, and I published an article in HBR on the subject in 2010). At that time, the only really sophisticated HR analytics capability we uncovered was at Google and perhaps Harrah’s (now Caesars). There was a fair amount of reporting going on, but not much prediction. Few HR organizations even had a dedicated analytics person. “HR analytics” typically meant a debate about how many employees the organization had, or the best way to measure employee engagement.
Even before the new survey results came out, I suspected that things were very different today. Most large companies have at least a small people, talent, workforce, or HR analytics group. There are many conferences devoted to the topic. It’s very common for organizations today to model workforce growth, attrition, engagement, and other key variables.
The survey involved 1,510 respondents from 23 countries across five continents. It included senior managers, directors, and VPs from from HR (61%), the Finance function (28%), and general management (10%). I was hired to help design, analyze, and report on the survey. All of the executives were from companies with $100M in revenue or more. Detailed results are here.
While it’s obvious that HR is moving in an analytical direction, I did not expect the very high level of sophisticated analytical activity in the survey. Here are some highlights:
51% of HR respondents said that they could perform predictive or prescriptive analytics, whereas only 37% of Finance respondents could undertake these more advanced forms of analytics.
89% agreed or agreed strongly that “My HR function is highly skilled at using data to determine future workforce plans currently (e.g. talent needed),” and only 1% disagreed.
94% agreed that “We are able to predict the likelihood of turnover in critical roles with a high degree of confidence currently.”
94% also agreed that, “We have accurate, real-time insight into our employees’ career development goals currently.”
When asked “Which of the following analytics are you using?” “artificial intelligence” received the highest response, with 31%. When asked for further detail on how respondents were using AI, the most common responses were “identifying at-risk talent through attrition modeling,” “predicting high-performing recruits,” and “sourcing best-fit candidates with resume analysis.”
This level of self-assessed capability for HR analytics was high in almost every geography and every specific question, but it was somewhat lower in Asian, European, and Australian organizations. It was generally highest in the U.S., the Middle East, and Latin America. Across industries, it was lowest in the “hospitality, travel, and leisure” and “media and entertainment” categories. Particularly high industries included financial services, energy and utilities, professional services, and wholesale distribution.
Why is HR more comfortable with advanced analytics than Finance, which has always been a function based on numbers? I have noted for years that Finance organizations and the CFOs who lead them have found it difficult to move past descriptive analytics and reporting — which they do very well — to more advanced analytics. There are certainly exceptions to this rule, but it helps explain why the growth of advanced analytics has been faster in HR.
But no function in a business stands alone with regard to data and analytics. One reason that Oracle surveyed both HR and Finance executives is that those two functions have an increasing need to collaborate. Workforce expenditures are often among an organization’s highest costs, and a company’s financial situation will dictate fluctuations in the size and makeup of the workforce. The survey found high levels of collaboration and mutual respect between HR and Finance, and a growing need for collaboration. For example, 82% of respondents agreed or strongly agreed, and only 5% disagreed, that “Integrating HR and Finance data is a top priority for us this year.” However, several interviews conducted after the survey revealed that there is still much opportunity for greater sharing of data and collaboration on analytics.
Of course, not everything is rosy in the world of HR analytics. I was quite interested to see that the function’s use of analytical tools surpasses the ability to interpret and act on them. When respondents were asked about the area of “most needed to develop or improve” analytical skills for HR, the highest-ranking choice was “acting on data and analytics to solve issues.” “Cultivating quantitative analysis and reasoning skills” and “advising business leaders by telling a story with data” also ranked highly. My experience is that these skills are equally lacking in other functions. Perhaps it is another sign of HR’s analytical maturity that it is facing the same human skill shortages that have long bedeviled analytics users across companies.