Over the last decade, “analytics” has become a widespread buzzword in HR (and elsewhere) and an increasingly important concept for HR’s future (see a great and ongoing summary of this work by David Green: https://academy.myhrfuture.com/). When talking about analytics, we use many different terms or concepts: scorecards, dashboards, predictive analytics, data science, evidence-based decisions, metrics, human resource accounting, cloud (or big) data, forecasting, or workforce modeling. At times, all these diverse ideas overwhelm us and actually impair our progress that could come through using analytics. For these ideas to have sustainable impact, we must organize them by answering three relatively simple questions.
Why analytics? Analytics is a way to access and use information to make better decisions. In a digital, connected, and transparent world, people have nearly unlimited access to information. In a business setting, we want to turn this ubiquitous information into improved decision making, and that requires analytics. This analytics process is a bit like turning the thousands of words in a dictionary (information) into a well-worded, cohesive story or essay with real impact (sound decisions). Thanks to work by Dick Beatty, we have seen decision making through analytics start with a focus on an HR scorecard and evolve into insights, then intervention, then business impact. Without analytics, unlimited information is fruitless in improving decisions and actions. HR professionals wisely invest their budget, time, and energy on analytics because they can improve decision making.
What analytics? In our research (see Victory Through Organization), we have found that HR analytics—that is focused on assessing only HR work through HR scorecards—has only moderate impact on both customer and investor outcomes and business results. In fact, the book my colleagues and I published in 2001 (HR Scorecard) would be out of date today. HR professionals should focus less on measuring HR and more on analytical tools and methodologies that have business impact (e.g., predictive modeling, statistical insights). Business impact comes from focusing on the results or value created from an HR activity.
In a recent seminar, I asked HR participants to write what they wanted to learn from the workshop. Their answers centered around HR practices (e.g., succession planning, career management, agile talent, workforce planning, culture change, leadership development, and so forth). Many wanted “analytics” about these HR practice areas. To probe for impact, I asked them to fill in the phrase after “so that . . . ” behind each desired learning. The “so that . . . ” query required them to think of the impact of the HR activity on stakeholders outside the boundaries of the organization (customers or investors). This shifted the analytics focus from activity to impact.
Analytics without impact is a like writing a story or essay without an audience. The story or essay may have good words and even sentences and plot line, but unless targeted to an audience, it lacks purpose and impact. Likewise, HR analytics needs to provide information that has impact by focusing on key business stakeholders. As HR analytics moves beyond scorecards on HR practices and insights from big data to real business impact, the information is more focused on improving the business.
For example, measuring employee engagement moves to impact when it is linked to customer engagement and financial results. Too often, some of the enthusiasm for employee experience is about the experience and not the real value: the impact of this experience on key stakeholders such as customers and investors. This logic for all HR practices is shown in the following figure.
How analytics? If analytics matters (why) and links to business impact (what), the challenge is to make analytics happen (how). My colleagues and Ihave worked with dozens of companies endeavoring to create analytics capability that delivers business value. Often the desire to perform analytics for decision making with impact lacks focus because so many things to measure and actions to take make knowing where to start unclear. As we have worked to implement analytics for impact, we have identified ten actions or criteria HR professionals could take to assess their HR analytics. These ten criteria and actions help HR professionals focus on a starting point and know how to move forward with analytics work. While a total score over 70 indicates a good analytics capability, this assessment can also help HR professionals identify specific actions that could improve their organization’s analytics capability.
Assessment of HR Analytics Efforts
Obviously, information-rich decisions are more likely to be effective than information-poor decisions, but navigating the firehose of knowledge available requires analytics. And knowing how to use the right analytics to turn information into improved decision making comes from answering the why, what, and how questions of analytics. The how question is certainly difficult to answer for each organization with all the ways of talking about analytics. So the ten-item assessment helps HR professionals determine their overall analytics capability and identify improvement areas to truly make better decisions and enhance business results.
So, what analytics do you do on your HR analytics?
Dave Ulrich is the Rensis Likert Professor at the Ross School of Business, University of Michigan and a partner at The RBL Group, a consulting firm focused on helping organizations and leaders deliver value.