It is becoming increasingly important for HR to use data, numbers and statistics to show trends in people management and employee engagement. The first of a series of articles on the subject looked at using data in an economic downturn. In this second article, Andrew Mayo looks at the different types of data available to HR professionals.
It was in Mark Twain's 1906 autobiography that the phrase "lies, damned lies, and statistics" first appeared, although he attributed it to Benjamin Disraeli. Numbers have a magical air of objectivity about them and I would be the first to encourage HR professionals to use them more. But although we will inevitably sometimes use them selectively to make a point, we should be conscious of what we are doing. It is complex in HR, as we use many different kinds of measures, some of which start with opinions.
What are "workforce analytics"?
Workforce analytics includes all data and ratios derived from our HR database of employees. It works with facts, always assuming that the data in the system is correct. One frequent difficulty is consistent job categorisation, which is essential for workforce planning. Another is the lack of useful breakdowns on reasons for leaving and absence, important information when looking at engagement and other people management initiatives.
The data enables us to calculate ratios and trends, which provides us with much more useful information than the cold numbers themselves. Turnover and absenteeism are presented as ratios, but are not always calculated in consistent ways. Three- or six-month "moving averages" are generally recommended. Other useful ratios may be: per person, eg training days; per annum, eg promotions; and between job families, eg front-line staff or technical support.
Percentages may be used too, such as for disabled employees, ethnic minorities, those with more than five years service and so on. Indeed, the possible combinations are many; the question is how to decide which ones to include in reports. The answer is:
- those that support a strategic goal;
- those where we know we have a problem; or
- those that support a change initiative.
An important truism to remember in this and other areas is that "the average is the enemy of truth". One must beware of consolidating figures too much and hiding important variations and details.
Costs and proving a return on investment
Some of these figures can be turned into costs and this is always eye-catching for line management. An HR department should ensure that it has at least one person in the function who is competent at costing.
As a judge of training awards for many years, I have regularly been horrified at the naivety of many attempts to prove a return on investment. Formulas for calculating the cost of excess (there is always a baseline we expect as normal) absenteeism and turnover should be established and used consistently.
We may have some target ratios where the deviation from the target represents a cost we can assess. Some traps must be avoided - if turnover is resourced internally, it is a much lower cost. And much short-term absenteeism is not a real cost (= extra money going out of the bank) if no extra overtime or labour is deployed to cover. Otherwise, the cost is the loss of value that arises from the person not being there, and this is often very hard to evaluate.
Costing comes into its own when we attempt to do justifications or return on investment for projects and programmes. Many HR initiatives do not have direct impacts on costs or revenues, even though they aim at "business improvement". One should not try and measure an outcome where less than 50% of the impact on it is likely to be due solely to the effect of the project. The key is to set realistic measurable objectives that can be directly attributable. Some may be knowledge-based, but many will require the measurement of opinions and feelings.
We need to use surveys extensively in HR work - for example assessing: satisfaction and engagement; opinions about a policy or programme; internal customer satisfaction; cultural change; and 360-degree behaviour analysis. The design and presentation of such data requires both skill and integrity; it is easy to pull out bits and tell half stories to support a point of view.
How do you measure the contribution of individuals and teams?
The costs associated with people are usually readily available. But the contribution of the human effort in organisations is another matter. People are employed either to maintain or add value/benefits to stakeholders, or in roles which are about "keeping the place orderly". Many administrative jobs are in the latter category. Both categories are important, but how do we measure the contribution?
There are relatively few jobs where this is directly assessable for an individual, so we are more likely to look at teams and groups. Productivity therefore is a very important metric and often overlooked by HR. It is defined as "output/input". The easiest "input" is to use the number of full-time equivalents in the group being considered. (Technically, it is better to use the cost of the human effort, but this takes longer).
Profit is not a good "output" as it depends on many factors other than people: revenue, sales or "production (or service)" units are better. This a challenging and critical area for the public sector today, where measuring productivity has never been easy, but improving it is essential.
One of the most under-developed areas for measurement, yet very critical, is that of individual capability: knowledge, skills, behaviours experience and, I would argue, networks and contacts. We need good measures here to be able to assess human capital, in other words talent and potential, and to be able to judge the success of many learning programmes, and perhaps to justify pay decisions. Qualifications are an easy, but often too crude, indicator; we need tests and perceptions.
Measuring the effectiveness of the HR function
There is one other area that needs HR attention, and that is the many processes the function is responsible for. First, we should measure effectiveness: the successful achievement of desired outcomes. Secondly, we must consider efficiency: the effort needed to secure an outcome. The first is the most important. What actually, for example, does one see as the measurable outcome of the appraisal process? And how do we measure it? An example of efficiency is the cost and/or time taken per new recruit.
Finance has it easy, using one dimension of measurement. HR, on the other hand, is very complex, and the benefit to organisations of having relevant, reliable and strategically supportive people data will undoubtedly aid performance improvement. Indeed, it ought to justify a dedicated specialist, who can help the department as a whole.
Andrew Mayo is the author of "Human Resources or Human Capital?". His book discusses how to ensure the most effective management of these value-creating assets.