HR Analytics: Not Just a Numbers Game

July 30, 2014 Ray Rivera



A Three-Part Series — Part Two 

In the previous blog entry, HR Reporting: Still Getting a Bad Rap, we described how HR reporting once was chastised for containing too little useful data, but now gets criticized for containing too much. In either case, it is easy for businesses to blame shortcomings in human capital transformation on the data.

Data accumulation is of course, not an end in itself. Regularly collected, readily accessible, high quality data is the fundamental input for analytics, and a critical element for transforming the black box of performance into a glass box. Information technology can make data collection and retrieval easier. But even businesses with the most sophisticated IT systems struggle to know what to do with all the data they have, and lack thorough knowledge to measure the behaviors that matter most to business performance.

Structure alone does not give data meaning, but it sure helps

How are such knowledge gaps possible, with so many organizations staffed with highly-trained analysts possessing deep knowledge of their businesses? A major reason is structure is still lacking, of a sort that goes beyond bringing order to a chaotic data set. Organizations frequently track metrics that simply do not measure business outcomes, not out of willful negligence, but rather from a lack of practical wisdom in identifying the few key performance indicators out of hundreds that measure workforce efficiency and business impact definitively.

More systematically, organizations struggle to create common scorecards and reporting methods that can cascade into lines of business, and facilitate communication across all stakeholder functions. In this scenario, because something is measured is it presumed to matter, even though there may be no justification for the measurement other than that it is readily available.

The measures that businesses do find useful often suffer from inconsistent definitions and questionable relevance to industry benchmarks, interfering with an ability to refer to industry standard metrics and functional benchmarks for comparative analysis. Some of the inconsistency stems from metrics that require great latitude of subjective judgment. Yet whatever the reason, the unfortunate result is that workforce measures are perceived as low value, a condition that becomes self-perpetuating as measurement rigor becomes neglected further.

Finally, most organizations have only a few persons who have a complete skills set to perform HR analytics: mastery of quantitative and research design methods, abstraction techniques, business acumen, communications skills, and most importantly, conversance in the foundational sciences of HR (e.g., I/O psychology, psychometrics, organizational sociology, managerial economics). A lack of skills is compounded by the fact that HR and line of business leaders also lack tools that enable independent analysis, ensuring that communication seldom happens between persons in the organizations most able to make an impact.

A little knowledge is a good thing, even if there is a lot of it

An effective way for businesses to address these concerns is by making use of a comprehensive library of delivered metrics, industry benchmarks, and HR strategies, all of which alleviate managers from having to reinvent the wheel. Simultaneously, such knowledge management techniques allow managers and analysts to determine whether the figures they are viewing are reasonable, or at least fall within a range which could be considered believable. Additionally, a metric catalogue helps provide consistency and standards that allow comparisons, and provide analysts guidance in measuring the most relevant phenomena, for example KPIs aligned to strategic goals, or benchmarking coverage across business processes.

A library also supports an HR team that may lack all the competencies needed to perform advanced forecasting, by providing a baseline set of analytical practices that can bring increased visibility to cross-functional processes. Such visibility can also help to bring about improvements to data quality, which in turn can eliminate further measurement errors and promote sharper analyses.

Finally, interactive visualizations are a means to make analytical insight more readily consumable by stakeholders, by embedding in-context transactions to guide decision making, and providing dashboards to focus attention on areas of greatest need.

Next up: Strategic workforce planning

Running an effective HR analytics program, one that consistently yields compelling results, is not trivial. But HR analytics is not just a numbers game. Beyond simply enlightening managers of the workings of their organizations, analytical insight ought to provide guidance for strategic workforce planning, which is the real payoff for HR analytics. In the next entry, we will discuss how to apply HR analytics results to aligning the workforce with business objectives, and how HR can apply both reporting and analytics to crafting workforce strategy.
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