What is happening to people analytics? A 15 year trend - PART TWO
Directionally Correct Newsletter, The #1 People Analytics Substack
By: Cole Napper, Jin Yan, & Ben Zweig
This article is written to discuss: how the skills of people analytics and the impact of the field have changed in the last 15 years, and what skills are important now.
Thank You
First, a big thank you to Revelio Labs (Jin & Ben) for your willingness to research this topic with Revelio’s data capabilities.
Context
This is PART TWO in a series on what has been going on in people analytics in the last 15 years. In PART ONE, we explored the trends of employment in people analytics and whether people analytics is considered a luxury at the moment. In this article, however, we intend to explore what it takes to be effective at people analytics. Namely, what background, skills, and impact are necessary to be successful in people analytics.
This article will be formatted into a series sections comprised of:
Expectations - What we think is/was happening
Facts - What is/was actually happening (including “Methodology”)
Commentary - What we think are the implications to people analytics
We intend to diagnose what is going on in people analytics, and why, within the context of what occurred in the field over the last 15 years. This article series will likely turn into a chapter in Cole’s forthcoming book, so be on the lookout if you’d like to see where more where this came from. We hope you enjoy it.
What background and skills do people analytics practitioners have?
EXPECTATIONS:
In preparation for this article, we met to discuss how we thought the backgrounds and skills of people analytics practitioners changed over the last 15 years. In regards to backgrounds, we think that people analytics practitioners are much more likely to hold advanced or specialized degrees, such as a PhD, than regular HR practitioners. Likely due to his background in I/O psychology, Cole also believes a large minority (which was probably a majority in the past) of the field of people analytics came from I/O psychology. Regrettably, we won’t be testing this hypothesis in this article.
We want to be more nuanced in discussing skills in people analytics. We break down our expectations of the skills needed to do people analytics into three time periods:
Pre-2015
2015-2022
2022-onward
Pre-2015 we believe the skills most relevant in the field are basic tools like Microsoft Excel, Access, and Powerpoint (or the equivalent in GSuite). Some more advanced users may have been using SPSS or SAS at the time.
From 2015-2022, we expected skills would start to transition away from spreadsheet tools into more sophisticated tools like SQL and SQL server/data warehousing tools, R & Python for open source coding languages, and even proprietary people analytics vendors who entered the field during that time period.
From 2022-onward, we expected the skills to be roughly the same as before, but with an increased focus on GenAI tools, automation tools such as low-code, no-code tools, and perhaps a decrease in coding and/or presentations being completed by humans – opting to use AI enhancements instead.
FACTS:
Compared to other HR specialists, people analytics practitioners are more likely to obtain a doctoral degree.
When comparing the skill composition between people analytics practitioners and other HR specialists, we find that analytical skills are overrepresented among people analytics practitioners. Specifically, the share of people analytics practitioners with data analysis skills is 32.8 percentage points higher than that of other HR professionals.
Focusing on the trend of skill gains in technical areas, people analytics practitioners have overwhelmingly acquired Microsoft Office and research skills. The share of those with coding skills, such as Python, R, and SPSS, has increased only slightly. Surprisingly, however, there has been a decline in the share of practitioners with SQL skills. Generative AI skills have also yet to gain traction within the profession.
COMMENTARY:
As you can see in the first chart, it was not a surprise to see that people analytics practitioners' educational backgrounds were almost 6x more likely to hold a doctorate than regular HR practitioners. With the advanced skills that are sometimes required to be a people analytics practitioner, this was an expected finding. Many of the early pioneers of people analytics had doctoral degrees in fields like I/O psychology and labor economics, and those credentials appear to have persisted.
In the second chart we see that compared to the rest of HR, people analytics practitioners are considerably higher on “data analysis/analytics skills”, “data warehousing/data mining”, and “business analysis/business process improvement” skills. This finding was to be expected. What was a little more surprising was seeing that people analytics practitioners were less than 10 percentage points higher on skills related to “SQL” and “research” than the rest of HR. We would assume people analytics practitioners would be significantly more represented in those spaces than the rest of HR, but apparently they are not.
And that leads us to the last chart, which was most surprising of all. This chart shows the trend in people analytics skills from 2015 thru 2023. We expected to see more advanced skills in people analytics (e.g., SQL, Python, R, Gen AI, etc.) increase in prevalence over time. Yet, what was the skill that saw not only a sizable increase (along with “Research”) but was also the most prevalent skill of all? Microsoft Office!? Not to mention, the prevalence of SQL skills actually went down over time; coding skills (i.e., Python, R, SPSS) didn’t move during that time period, hanging just north of 10% of people analytics practitioners; and the expected upturn in GenAI skills lately? Almost non-existent. Wow, just wow.
Perhaps if we take the charts at face value, maybe the field of people analytics is predominantly made up of folks who are increasingly using Microsoft Excel to do some basic research. Nothing more, nothing less. Needless to say, this is not what we were expecting to find, but perhaps this relates to why the field of people analytics has seen such deep cuts in the last two years and why people analytics might be seen as a “luxury” after all (as seen in PART ONE). Maybe we aren’t staying ahead of the curve like we have in the past.
Does people analytics impact the bottom line?
EXPECTATIONS:
Examples of research showing the linkage between HR performance and business performance abound. Cole has written extensively in the past about the need for people analytics functions, in addition to all of HR, to add value to the business and maximize their utility. Yet, it stands to be seen whether people analytics functions contribute to the bottom line of the organizations in which they reside. This is a difficult proposition to test at scale, but we will do our best.
As a consequence, we posit that companies without a people analytics function will be perceived as less valuable than those with a people analytics function – this seems only plausible, right? Moreover, it stands to reason that companies with people analytics functions that are more “mature” or “prestigious” will be perceived as more valuable than those with less resources and less maturity.
FACTS:
Using Revelio Labs’ prestige model, we calculated each PA team’s average prestige score. PA teams scoring below the average were considered less prestigious, while those scoring above the average were considered prestigious. In total, we identified 1,824 companies with a prestigious PA team and 2,125 with a less prestigious one. We then compared employee sentiment ratings across companies with a prestigious PA team, a less prestigious PA team, and no PA team. Companies with prestigious PA teams scored the highest in all categories. Additionally, companies with less prestigious PA teams scored slightly higher than those without a PA team in almost all categories, except for CEO and senior leadership ratings.
COMMENTARY:
Yes, yes, we know correlation doesn't imply causation (we’re looking at you, McKinsey). We found a correlation between companies with “prestigious”/”mature” people analytics functions and companies being rated more highly across the board. This doesn’t mean people analytics is the cause. Yet, it’s quite the pattern, right? No people analytics team = lowest ratings. Less prestigious team = medium ratings. Prestigious team = highest ratings across the board. That’s quite a trend.
On a another note, we made some calculations that you might find interesting:
There are almost 4K people analytics teams (3949) in the US,
Which means the average people analytics team is roughly 2.75 people in size (if the total people in the field is 10K+)
Only 46% of people analytics teams (1824) are considered prestigious, with 54% being less prestigious
With these findings in mind, organizations with people analytics teams less than three people are likely suffering the consequences of underinvestment in people analytics. You don’t need a “mega”-people analytics team to be prestigious, but you definitely cannot be tiny. With investment in people analytics headcount, though, comes the need to pay back that investment with a return. That leads us to our recommendations on what to do now.
Recommendations
STEP ONE: Add real value & break the cycle
In Part One, we concluded with:
“In the second article in the series, we intend to address recommendations on what people analytics can do to not be seen as a “luxury function", and how we can break the linkage between the “rise of people analytics” and the “era of low interest rates” – considering that interest rates are still at recent highs. No one knows what the future holds in regards to interest rates, global economic conditions, and the like; therefore, it would be wise to have plans for growth and success of people analytics roles regardless of what economic conditions the future holds.……..That withstanding, it’s worth re-emphasizing that it’s time for people analytics to break the linkage to interest rates, dollars, or any other variable that is not related to driving value for organizations.”
Do you really want your employment prospects tied to something outside of your control, like interest rates? We don’t. It’s time to take back control of our destiny by adding value.
We need to focus on bringing value to the top and bottom lines of organizations. This is the only way that we can assure the future of people analytics is bright regardless of economic conditions. As Cole has been known to say, “It’s very hard to lay off a team that’s paying for themselves 10x every year” (in reference to his “we must pay for ourselves 10x every year” rif). Every people analytics team should set this as a goal for themselves, and Cole is in the process of writing a book to show you how.
STEP TWO: Mature the people analytics function
Prestigious and skilled functions make a positive difference in organizations. Here are three components for how people analytics can mature their functions.
For internal people analytics functions: Be better
Before writing this series, we thought the field of people analytics was past solely using Excel for basic research/reporting. We thought we were better than that. Apparently we are not. We need to invest in advancing our skills to push the field forward. Whether it be coding languages, machine learning, GenAI, or whatever drives value in the business, at one point people analytics was on the “bleeding edge”. We need to return there, and it will take all of us. We must be more than just dashboards.
For vendors: Invest in the community first
It’s simple math that if the community is shrinking, the pie from which to draw value from is getting smaller for everyone. If you are a vendor, and your goal is to only extract value from the community, that goal may pay off in the short term, but will fail in the long term unless we get the pie growing again. Vendors need to invest in the community first. We need to get the pie growing again for everyone. The rising tide lifts all boats. It takes all of us to make this happen.
For educators: Teach impact, not just research
Whether it be formal educators through graduate programs, or online certifications, or YouTube videos, or books and articles like this series, we need to be teaching new entrants to the field (and probably many incumbents as well) what it means to make an impact with data. It’s about more than people liking your work. Your work must have a tangible ROI. Yes, we mean real dollars, not just theoretical impact. John Boudreau, Wayne Cascio, and Alexis Fink wrote an excellent book called “Investing in People”, which is a great place to start to learn how.
STEP Three: Let’s get back to growth
Although we can acknowledge that trends in this space haven’t been going our way lately, we must also commit to making a change. The field needs to get back on track to assuming leadership in HR, democratizing analytics in the business, and expanding the field of people analytics professionals. Let’s get back to growth, together.
I hope you like this article. If so, I have a few more articles coming out soon. Stay tuned. If you are interested in learning more directly from me, please connect with me on LinkedIn.
Cole’s recent articles
What is happening to people analytics? A 15-year trend PART ONE
Don’t Be a Copy-Cat: People Analytics as the Antidote to HR Strategy Copy-Cats
What’s Old is New: The Quest for Excellence in Workforce Planning
For access to all of Cole’s previous articles, go here.
Thanks Cole! If you could please write another one as a collective of how exactlyPA practitioners in their organisations made impact and added value, it would be great to know that!