IDC has been turning its research lens on the growing discipline of human resource analytics and, in 2017, released its IDC MaturityScape: Workforce Analytics Adoption 1.0 study. It has started surveying organizations to assess the sophistication of their efforts according to five stages of maturity
Kyle Lagunas, IDC’s research manager for emerging trends in talent acquisition and staffing, explained preliminary findings that showed low levels of adoption and what organizations and HR departments must do to move up the maturity ladder.
Can you describe the adoption rates of human resource analytics?
Kyle Lagunas: We identified five different stages of maturity. The first one is ad hoc. Data might be descriptive, but it’s a little difficult to get — answers to simple questions like head count. Then, you move into opportunistic, where folks are trying to dabble in analytics and get a little more familiar with it but it’s for their eyes only. It’s a little more consumable, but they’re not quite ready to report on it to the organization.
[The next level is] repeatable. We’re ready for action, we’re more comfortable with data, we’re more comfortable with analytics and we are leveraging our ability to advise the business to make more strategic decisions or just to keep our asses covered. But we are using the data in everyday processes.
Managed is the next stage. We’re [able to] look ahead, not just to get a sense of where we are or what we have. We’re also comparing ourselves to others. We’re looking forward.
Optimized — the highest level of maturity — is prescribing the course. We really are charting … the future of the organization, leveraging our insights from our existing workforce, the viability of that workforce, as well as labor shortages in various global regions.
The majority of people are either at stages one or two. They’re either ad hoc, or they’re opportunistic.
Why the low level of adoption?
Lagunas: First is that HR as a function is transforming itself. For decades, the HR function has been administrative. It’s been treated as a cost center rather than as a business driver. A lot of the time, the culture was policy-focused and averting risk.
Legacy behaviors [and] culture in HR have become a bit of a barrier to adoption. It’s not like there’s a lack of tools out there. You can’t take a single HR tech demo without seeing a reporting/analytics module.
What’s more rare is finding an HR organization that has a culture where data is core, where data and analytics are part of the form and function.
Instead, the data pieces are usually the headaches. Like, ‘Oh, God, here we go. We’re getting audited for this.’ Or, ‘We need to produce a report for this next year’s funding.’ It’s usually an exercise and an arduous one.
What do organizations need to do to start moving up the maturity ladder in human resource analytics?
Lagunas: Expect that this is not an all-or-nothing proposition. I think people are very daunted by the idea of analytics because it is pervasive. The scope of these practices can be very far reaching and can be quite intimidating.
You can start with where you’re comfortable. You’re not alone. [Most] companies are just getting started.
Where does the analytics know-how exist? Some companies have centers of excellence or centralized data science teams. Some departments might have a data scientist of their own.
Lagunas: In an SMB environment, which makes up the bulk of HR organizations, you might be lucky to have one dedicated tech resource, and that is often your systems person. That might also be your data guru, and they might be managing your intranet or your HR self-service environment. You’re lucky if you have one really strong person here, but they’ve got other things on their plate.
These are the folks that build out these really robust Excel spreadsheets and pivot tables where they can produce a report … relatively quickly. When they leave, the business is kind of [out of luck] because they don’t have that resource backfilled. There is that really pervasive skills gap in HR that is increasingly important to overcome.
You might see in other enterprise environments a dedicated HRIT resource [or] a shared resource across an enterprise. You might have system leads for each region.
What we’re talking about here is not just changing HR culture or getting HR to be tech-savvy and data-savvy. It’s not just that. We’re talking about the HR of the future — digital HR.
Some of the tech expertise you mentioned sounded generic to IT. Is that the most likely resource to help HR move into analytics more, or is there any hope that a subject matter expert could get assigned some analytics specialists?
Lagunas: Yes and yes. I think there’s an opportunity for HR to learn from their counterparts across the business.
If we look in talent acquisition as an example, increasingly, our KPIs, our metrics, are reflective of the marketing department. We’re talking about lead generation; we’re talking about email campaigns and candidate relationship management and recruitment marketing automation [and] employer brand.
If we look at procurement … operations … or IT, we’ll start to learn more from our colleagues across the company and start to cultivate our own unofficial [centers of excellence] where we just come together and learn.
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