Thoughts on the most Popular Current Metrics
This is part one of two on recruiting metrics. Today I will discuss why the metrics we currently use are ineffective and not very useful. Next week I will present the metrics that I think actually do matter.
Over the past few decades, there has been a growing focus on quantification and measurement. Every academic and commercial entity attempts to measure even those things that are perhaps better left to judgment or that need nuanced thinking and contextual understanding.
We believe we can hold people accountable more readily to a set of numbers than to good judgment or opinion. But unfortunately, just because we can measure something does not mean it is useful. As Jerry Muller says in his book The Tyranny of Metrics, “There is often unexamined faith that amassing data and sharing it widely…will result in improvements of some sort…”
We rarely question the metrics we use- we just assume that they are valid. We report them because everyone else does, and rarely does anyone question them or challenge the assumptions they are based on. The recruiting metrics we generally use do not give a useful picture of the effectiveness or strategic capability of the talent acquisition function.
Measuring the effectiveness of people as opposed to sales, production throughput, or widgets produced is difficult. It is subject to biases, manipulation, and potential misuse that are not found when measuring inanimate objects or subjects where numbers are natural.
So, is it right to measure the effectiveness of recruiting by counting numbers and time? The semi-standard primary set of metrics that recruiters use – cost per hire, time to fill, and quality of hire – seem valid and important at first glance. But I argue that these are neither useful nor effective metrics. Nor do they hold much interest to leaders.
Let’s examine the commonly reported metrics and see if they show how well recruiters are finding, attracting, and influencing potential candidates. Do these metrics give leadership a good picture of how well recruiting is helping to shape the strategy and future of the organization?
Cost Per Hire
Cost per hire, as usually reported, is a metric that I find particularly questionable for several reasons.
Measuring cost is an example of the Band Wagon Fallacy – everyone measures cost, so it must be useful, and we are expected to report it. It is also relatively easy to measure, which may partially account for its popularity.
But is it actionable? What can you do to reduce that cost significantly? In most cases, very little because a significant portion of the costs is fixed, including salaries, general overhead, equipment, and licenses. Does senior leadership care more about cost or about the contributions a new employee makes? Hiring people cheaply or limiting the reach of recruiting lowers costs but also lowers the ability to find and attract the best candidates.
Recruiters can and should monitor their costs and work to keep them reasonable. But focusing as much as we do on cost diverts attention from more important considerations. Whatever it costs in time or money to influence and ultimately hire a person that invents a new product, procures a patent, fixes a major problem, or comes up with a great idea is money well spent.
Speed or Time to Fill
Speed is important when you are in competition for talent. Recruiters who can find and attract top candidates and make offers quickly are highly sought. But speed needs to be qualified with words like speed to present, speed to find, speed to screen, or speed to offer.
Choosing the measure of speed that recruiters can control is critical and should not be overly complicated or get bogged down in trivial details. Focus on what elements of speed pays the highest dividends.
Time to fill is not a good measure because it is not entirely in the control of recruiters. Candidates take time to respond, managers take time to provide feedback, and administrative issues cloud the issue. Recruiters only control one element of speed, and this is the only metric that should be reported: the time to present a qualified candidate to the hiring manager.
Quality of Hire
This brings us to the quality of hire, which many consider the most important metric. But is it?
Not really, and not because I don’t think quality is important. The challenge is defining what we mean when we say that one candidate is “better” than another and who determines it.
Quality of hire cannot be measured with numbers as we measure manufactured products that have exact specifications. In manufacturing, quality is not about perfection or opinion; it is about reducing variations from one product or another. In the context of recruiting, this would mean reducing the variations/differences in skills between candidates as much as possible for a similar position. Taken to the extreme, this means hiring people who are virtual clones of each other.
This is the inherent danger of using artificial intelligence to determine who is the best candidate. A.I. can only match people to jobs based on specific data such as degree, skills, or previous experience. We assume these are the best indicators of quality or performance, but research suggests that they are not. It is not possible to define human quality in a way that can be objective, consistent, or meaningfully connected to the recruitment process.
The hiring manager and, ultimately, the output of the employee decide the quality of a candidate. This can only be determined months or even years after someone is hired. Every hire is judged by a different standard according to the manager and the circumstances of the job.
So, without a defined, consistent, and objective measure correlated to quality, we are left with subjective judgment. We all have been in situations when one manager thinks an employee is great, and another manager feels the opposite.
Many intangible factors, such as general ability, personality, and motivation, maybe more important. But these are hard to measure and may not be what makes that employee in that job successful.
The measures below are often considered as quality of hire and are also flawed.
Time to Productivity
Another flawed metric is measuring how quickly a new hire is productive. The assumption is that productivity is more important than judgment or innovation, or learning. A corollary assumption is that the faster they become productive, the better they are. This may be true when discussing someone assembling a product, for example, but it may take an engineer much longer to understand what is needed and decide how to help. The challenge is to define what productive means.
It is very hard to impossible to measure productivity for many positions, such as managers, human resource personnel, accountants, or those positions where the output is not tangible and requires judgment and experience-based decision-making.
And how is recruiting responsible for productivity? The variables that influence productivity include the manager, training, the work environment, the new employee’s teammates, and the corporate culture. There are too many variables to tie productivity to the recruiting process.
Performance
Some recruiters measure quality by looking at a new hire’s performance rating (assuming your firm still has performance ratings). This is a post hoc ergo propter hoc fallacy. It does not follow that recruitment leads to poor or good performance.
There are many variables that affect performance far more than recruitment. Performance ratings are subjective and depend as much on personality and the relationship the new hire and the manager have with each other than on actual performance. Many organizations have recently abandoned performance ratings because they are not objective, increase employee dissatisfaction, and do not help improve performance.
Turnover
And finally, I often see turnover rates used as a measure of quality. Whether someone leaves is much more likely to be caused by the relationship with the manager, economics, the corporate culture, lack of opportunity, or some other factor than because of the type of person recruited.
I have only highlighted a few of the commonly used metrics, but I hope that you agree that these are flawed and not very useful. Next week I will present the metrics that I believe really make a difference and are useful.
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