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The value of the metric depends on several things, she says, including:
- Having a clear definition of what we are trying to measure;
- Having a valid method to quantify the concept; and
- Utilizing comparison data, including a baseline for your organization and data from other sources, which will give you information to use in comparing your organization’s performance to that of other organizations.
It is also important to remind ourselves that the value in metrics is not how many metrics we measure, but that we are measuring the key metrics for our organizations. This may include metrics that measure the operational effectiveness of HR and metrics that measure employee engagement and performance in relation to achieving company goals. The first group may include the ratio of HR staff to total employees, time to fill, cost per hire, measuring complaints and legal issues, and the demographics of the workforce. The second group might include turnover, retention of top performers, quality of hire, and employee engagement.
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We hear a lot of talk about dashboards or scorecards that provide a snapshot of key metrics. Again, it is important to select metrics that are key measures for your organization. It is equally important to continuously review whether the metrics are working. Are they giving you the information needed to manage the business and drive change?
Time to Fill
Time to fill an open position is a fairly standard metric and is one measure of the operational effectiveness of an HR department. It is relatively easy to develop baseline data for your organization and to benchmark your data against data from other surveys. Organizations that are drilling down on this concept to measure time to fill based on the level of compensation, or level of a position, or the department or supervisor are likely getting information that is even more useful.
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Skewed Data
An interesting situation developed at one employer where the CFO looked at the time-to-fill metric and then wanted an explanation from the HR director about why it was taking so long to fill jobs compared to other companies. During the period measured, there was one position that was very difficult to fill because of the special skills required, and the time to fill for that position was 78 days; and in another situation, the hiring manager was out for 3 months on leave, and the position was effectively on hold during the period being measured. These numbers skewed the data because they were outliers. The same could happen with any data set that looks very strong at the aggregate level. The takeaway? Keep in mind that a metric really only identifies an area that may warrant further investigation, as it did in this case.
In a white paper titled Myths, Best Practices, and Practical Tips, the author, William A. Schiemann of the Metrus Group, included an interesting hierarchy of measures. The first was simple efficiency, or how many new job requisitions were actually filled. The second went a step further and looked at recruiting and retention of top talent and answered the question, Are we retaining the right people? The third level was identifying measurements to determine if the talent hired was the talent needed to meet customer needs.
Tomorrow, we’ll discuss more recruiting metrics, plus an introduction to BLR’s research report HR Metrics Best Practices: How Big Data Drives Big Decisions.