It never seems to fail that following the HR Technology® Conference in October, there’s an increase in blogs, articles, and overall commentary on HR analytics.
The articles usually follow this trajectory:
- Why aren’t organizations investing in analytics? First we bemoan the fact that so few organizations are investing in HR analytics: only 12% of organizations in the latest Sierra-Cedar HR systems survey adopted any form of Workforce optimization applications such as workforce analytics, workforce planning, or predictive analytics solutions, and this number hasn’t changed much in the last few years.
- We have solutions. Articles then show up pointing out the improvements in solution and service provider approaches and tools. With the plethora of options available today, lack of tools shouldn’t be the holdup for adopting analytics in organizations.
- Let’s blame HR. Of course, somewhere along the line we start looking at HR skills and capabilities. Articles point out that HR isn’t capable of building a team with business acumen, storytelling, visualization, HR process knowledge, and good analytics skills.
- Let’s blame the data. We then move into articles blaming everyone for poor data management practices; now this is a real issue—and it causes more pain than most people realize. Some of it is caused by lack of system integrations, but most of it is simply a lack of communication. In any discussion about big data and enterprise-wide systems, the first and most important conversation must start with data categorization and alignment.
- Desperation sets in. We throw up our hands and point out that if HR doesn’t step up to the plate, then they won’t be involved in real business-changing discussions. HR analytics is a stellar opportunity to be strategic and show the value proposition of HR, but it can quickly be reassigned to the finance department, the operations team, or [gasp] the marketing department if HR is unwilling or unable to make the transition.
Don’t get me wrong: all of the writing on the topic of analytics is valid, important, and you should spend time pulling out the incredible nuggets of insight that are shared in these articles (some of my favorites this year were from Karen O’Leonard, Andrew Marritt, and Ken Crawford). But this year, we’d like to ask a different question: Can we identify the qualities of a data-driven HR organization?
This question actually started as a great conversation around a dining room table in Washington, D.C. between Lexy Martin, our research team, and me; we were discussing the concept of the Quantified Self and wondered if it could be applied to organizations. In 2007, Wired editors Gary Wolf and Kevin Kelly coined a new term, “Quantified Self,” to describe the growing group of like-minded individuals interested in capturing, documenting, and eventually learning more about their personal lives and habits from massive amounts of data available through devices carried or worn on a daily basis. The concept of the Quantified Self assumes that people who know more about themselves are literally more self-aware and will take action to make changes. Could organizations take this quantification concept, apply it to their workforce decisions, and increase business and financial outcomes?
The Sierra-Cedar HR System Survey, now in its 17th year, gathers information from over 1,000 organizations across the globe that is validated against publicly available financial and market data. The longevity of the Survey affords us a historical perspective that allows us to look back to year-over-year factors that have an impact on business outcomes. Tracking the adoption and deployment of HR analytics solutions, we gather data on process maturity as well as the type and amount of data HR organizations are capturing. Using this data, was it possible to identify HR organizations that were themselves data driven? Could we prove that organizations that gather more data, share that data openly, and leverage it in processes and decision-making see improved outcomes from their efforts? The short answer was “yes.” The actual work, however, involved months’ of analysis.
Defining the Quantified Organization
First, we had to define the Quantified Organization. Starting with key lessons learned from our 2013–2014 Survey results about Business Intelligence (BI) adoption, we determined that a Quantified Organization would be one that invests in HR technologies, processes, and practices that enable it to improve workforce operations and achieve organizational goals. Through HR practices and technology adoption, Quantified Organizations support an environment of data-driven decision making.
We then identified several selection criteria. These were based on an organization’s leadership in four areas:
- Business Intelligence process maturity
- Managers’ direct access to HR analytics and BI that supports workforce decision making
- More data sources regularly juxtaposed with workforce data
- More overall categories of HR metrics
After weeks of data cleansing, statistical analysis, and validation efforts, we found a small-but-valid group of organizations that had a set of shared characteristics concerning their approach to leveraging data in their HR operations. Organizational size and overall HR technology spending didn’t matter. Our analysis found that the Quantified Organizations ranged in size from small (with workforce of just over 100) to very large (with workforces of 410,000). Many Quantified Organizations were also global organizations operating in an average of 29 different countries.
The Bottom Line
The bottom line of our analysis was that Quantified Organizations out-performed even the Top Performing organizations this year. They saw higher levels of financial performance, as well as positive HR and Talent outcomes, but the most dramatic difference in outcome analysis was in the Return on Equity (ROE) outcomes. There are more details in our report, but for me—as a researcher and former practitioner—the exciting thing was seeing the diversity of organizations that fell into this group.
There is more research to do, as many factors have an impact on an organization’s overall success, but there is enough data to now say that the data-driven HR organization is real, and that it isn’t tied to a single type of technology, organizational makeup, or industry. Becoming a Quantified Organization is achievable for any organization willing to take an honest look at their data and analytics and use that information to make workforce decisions. Like the Quantified Self, it is more aware of its actions and the impact of those actions on the organization. You can’t hide from yourself when you take an honest look at the data.