People Analytics, A Complex Domain, Is About To Be Transformed by AI.
We just completed a large study of People Analytics and the results are striking. Only 10% of companies directly correlate human capital data to business in a systemic way, with many data, technical, and operational issues in the way. Yet as our research found, AI is about to totally change this market. Here’s the story.
Early in my career I attended HR analytics conferences and found hard working analysts doing amazing things, wondering why nobody listened to them. Today, 25 years later, these folks continue to do amazing work, yet are still frustrated in their progress.
Here’s the problem: companies are talent constrained. Despite impending automation from AI, every organization is trying to find new skills, hire frontline workers, and fill its leadership pipeline as baby boomers retire. Healthcare workers are going to be short 2 million clinicians in the next three years; retailers and manufacturers have similar challenges.
As these workforce challenges loom, we’re now flooded with data to help. Companies use platforms like Eightfold, LinkedIn, Lightcast, and Draup to pinpoint talent, identify salary needs, and find critical skills with laser precision. So theoretically we should have analytics in HR that’s as powerful as any CRM or financial planning system.
Well we don’t. After billions spent on HCM platforms, fewer than 10% of companies can correlate or directly linking HR and people data to business metrics. And this is a problem.
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I just read last week that Salesforce is going to hire 1,000 new sales reps to sell their AI agents. (A strange move: hiring sales reps to sell a system that eliminates the need for sales reps.). Mark Benioff, a savvy leader, would probably like to know exactly what skills these 1000 people need, what background they should have, and how many of them can be redeployed internally. Does he have that information? I doubt it.
This is the problem everywhere. We spend billions on HR software yet the People Analytics team is often stuck doing science projects to understand retention, skills gaps, or other important, but internally focused problems. How many companies can measure and monitor human capital with the rigor they use with their supply chain, financial operations, or customer retention?
The answer is about 10%. In some sense this is progress: the last time we did this study it was far lower. But this is not high enough. Given that payroll is the largest discretionary expense in the company, shouldn’t we be measuring people impact with laser precision? Of course we should, it’s just very hard to do.
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Why is it so hard? For several reasons.
- First, the data is sprinkled all over the place in different employee systems (most companies have 30-40 HR-related and productivity systems).
- Second, the data is not clearly defined, so it takes a lot of effort to figure out the real retention rate when there are seasonal variations, family changes, and many other factors.
- Third, we have very little correlation between business systems and HR systems.
Consider the promise of ERP. The reason we purchased Workday, SAP, Oracle or another ERP was to bring this data together. Well it is in one “platform,” but the vendors have not been very good at giving us out of the box correlations. Try doing a simple report: “sales attainment correlated to years of experience.” I bet it takes you a week to even get the right data. So no sales manager will ever even try.
Things are about to change, and fast.
As our new research points out, People Analytics is one of the “last mature areas of HR. And it’s for the reasons above plus the fact that some companies just don’t think “data-centric” enough.
Enter AI: the most integrating, systemic, and easy to use data management technology we’ve ever seen.
I remember when SQL was pioneered – we spent millions on tools like Business Objects, MicroStrategy, and Essbase. We built data warehouses and data extract tools. We hired data scientists and built predictive models. Well AI can do almost all of this for us, with an interface that does not require a PhD to operate.
I am not saying that HR and HCM data management is easy: it’s not. But with the new tools like Visier, Workday Illuminate, SAP Joule, OneModel, CruncHR, and Galileo, this whole domain is about to change.
Imagine if you “threw” your sales data by employee into Galileo and then “tossed” in the employee history database, the compensation data, and the training history. If you label the data correctly the AI will immediately let you ask “what is the relationship between sales revenue and tenure, training history, managerial span of control, and salary?” You’ll get a good answer. (I’ve done this in Galileo.)
The AI may not know that some sales reps have plum territories and some don’t, and it may not know that some sales leaders are great and others are problematic. But you’ll get the basic information fast and then you can “throw” this other data in to make the answer better.
I’m not kidding. I’ve been doing data analysis and data management for 30+ years and these new tools are as groundbreaking as the spreadsheet was compared to an HP calculator.
Our research explains all this in detail, and also shows you how internal skills, culture, and practices like consulting, storytelling, and business partnership are also needed. For the first time in my career we can get out of our offices and spend less time doing data cleanup, model-building, data extraction, and charting. Let’s let the AI do this for us.
This is all very new, by the way. New AI tools like Vee from Visier, Galileo, Joule, Illuminate, and others are barely a year old. But they’re advancing at light speed. Your new job is to manage the data (Corpus) and spend more time understanding the big problems to work on.
We call this “Systemic Analytics” – looking at the “system,” not just one isolated part. What role does recruitment play in turnover? A lot. What role does work schedule play in productivity? A lot. Every human capital factor is related – and there are hundreds of variables to consider. Once we get all this data into one easy-to-use system we can ask the AI to show us what’s going on.
Bring People Analytics To The C-Suite
Here’s a simple question: at the end of the quarter look at what your CEO and CFO talk about. Something like “revenue was 6% behind plan in the US but 8% above in Asia.”
Wouldn’t you like to know what are the people issues behind that variation? AI is going to let us answer that question. So now every quarter the CEO can say “our employee productivity is up 11% in Asia, thanks to the new hiring practices and pay model we built.”
The 10% of companies doing this deserve a lot of credit. As our research details, these companies are hiring businesspeople into HR, giving them consulting roles, and arming them with data tools to dig in. And yes, they’re suffering from the same data quality issues as others, but they’re fixing them.
They’re defining People Analytics as a Business Analytics function, not a PhD group to study psychology. Those issues matter too, but they are only contributors, not where the big action is. And they’re understanding HR topics like retention, engagement, leadership, and skills trajectory in detail. And they’re getting a huge payoff.
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I can’t wait to tell you all about where this is going. Get your hands on Galileo, join us at the Visier user conference, or join our corporate membership (totally AI-powered now, Galileo included) and you’ll see how you can superpower your human capital operation.
Additional Information
People Analytics Certificate Course in The Josh Bersin Academy
