Go beyond surface indicators to reveal root cause for HRO successes and failures.
We’re almost there. After examining the complexities of metrics in previous columns, in this issue we present definitions and examples for the rest of the HRM metrics taxonomy. With these definitions and your metrics spreadsheet, you’re ready to do a baseline assessment of the state of your current HRM policies, programs, and practices, as well as of your current HRM delivery system (HRMDS). These cover not only the traditional terms of costs and volumes but also the far more meaningful terms of business outcomes. If you’re planning to outsource one or more processes or move aggressively to comprehensive HRM BPO, beware the service level agreement that focuses only on costs and volumes, error rates, turnaround times, etc., and doesn’t commit your provider to helping you achieve your business outcomes.
HRM administrative and strategic process outcome metrics Far more powerful than process activity metrics, outcome metrics begin to get at the real reason for doing HRM processes, and the real emphasis for a software vendor’s or outsourcing provider’s analytical “pitch” is likely to begin here, especially with the more strategic aspects of these processes and the related metrics. Benchmarks are available for some of these metrics, but they tend to be from the proprietary sources of various vendors and consultants. However, as the outcomes become more important to measure, it becomes harder to find good benchmarks, and your best benchmark may be your own improvement over time in areas critical to achieving your business outcomes.
Much more analysis, including trending and/or data mining, is needed to categorize these outcomes as desirable within the larger business context; that’s where the next group of metrics begins its work. These metrics include the number of new hires (but not their quality), attrition rates (but not whether it’s good or bad attrition), payroll errors (but not the source or impact of those errors), and the number of background checks completed with only driving violations (but no indication of to what extent driving violations are cause for concern), etc.
HRM administrative and strategic process activity pattern recognition metrics These are the metrics used to begin diagnosing process issues. Are the volumes indicative of desirable program utilization or of under-or over-utilization in the face of program design flaws? Is the number of safety/health incidents showing a day/time pattern, a pattern related to changes in work rules or total compensation plans, or one related to labor-relations negotiation schedules? Are there patterns in the volumes, types, and/or timing of HRM grievances/complaints that point to problems with specific programs, practices, and/or individual managers? This is where we begin to look at the processes to understand why something is happening and whether it’s desirable.
HRM administrative and strategic process outcome pattern recognition metrics Looking for patterns on the outcomes is investigative reporting. Given specific levels of turnover, are they good or bad? Well, it depends: low turnover among poor performers is bad; low turnover among good performers is good; high turnover among poor performers is good, and high turnover among good performers is bad. To find causal factors, these outcome patterns point the way—e.g., do all the workers hired by manager X perform at a higher-than-average level? Is there something special about X’s selection process or management style? Is there something special about X’s applicant pool or the nature of the work being done? The real purpose of business outcome metrics is to get at the causal factors around excellent outcomes and then to design processes so as to achieve those excellent outcomes consistently and by everyone.
HRM administrative and strategic process activity and process outcome pattern prediction metrics Predicting patterns, whether for administrative or strategic processes, and especially for their important outcomes, is the Holy Grail in business outcome metrics, but it is very difficult to generalize examples of these metrics. The types of metrics that help predict future patterns in administrative or strategic process outcomes are those which are early enough in a complex workflow to serve as warning signs. For example, if there’s a well-defined campus recruiting process, it’s obvious that if not enough students are seen during a campus visit, there won’t be enough invited back to lead to enough offers. But a more subtle predictor of success is the number of students who present themselves during the campus visit who have a demonstrated interest in, familiarity with, and preparation for the work that the organization does. Rather than having a full schedule during the campus visit with all students, isn’t it far better to have a lighter schedule but with very high-quality prospects?
