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Numbers can say more than a thousand words

For this very reason, the term “HR Analytics” has been on everyone’s lips not just since yesterday. Human Resource Analytics describes the analysis of HR-related data to optimize decision-making processes. These decision-making processes can generally relate to everything possible in the personnel area: to the recruiting of applicants, to the performance or satisfaction of employees, to employee loyalty.

Which indicators can be measured?

More specifically, in recruiting, the number of calls for individual job advertisements is an interesting key figure, as is the number of applications for these job advertisements. Furthermore, companies can measure the source from which these applicants come and thus also where particularly qualified applicants come from. For the second example, it can be said that employee performance can be determined based on sales or profit per employee. The error rate at work or downtime (due to illness or the like) can also be taken into account in this context.

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From data acquisition to evaluation

Just capturing these numbers is not an exciting thing – every company probably already does that in one way or another. It only gets exciting when you go a step further and start establishing connections between numbers. For example, it is found that most qualified applicants apply through a company’s website. Further research shows that this is due to a large amount of relevant information about the position and the company on the website – as a result, applicants can better assess whether the position in the company suits them or not. In comparison, there was less relevant information to be found on the job boards, which is why less qualified applicants have also applied. The relevant content could also be adapted accordingly in other sources.

Take into account the context of the numbers

The analysis of HR-related data always needs to take into account the respective context. Correlations between different numbers do not always suggest causal relationships. Therefore, any influencing factors should always be carefully examined before changing a decision-making process. The fact is: if, after such examinations, you know which factors lead to which numbers (positive or negative), you can begin to influence these factors and consciously shape the result.

Avoid controls, seize opportunities

When you think of HR analytics, it is often obvious to think of the term “control” – especially when it comes to measuring absenteeism, for example. However, such evaluations can also be seen as an opportunity. If an employee is noticeably often ill, his workplace could be the reason for this, for example (keyword lighting or air conditioning). He may also be under or overburdened. A clarifying discussion can often lead to an improvement in the employee’s situation and to the fact that they will fall ill less frequently in the future. A new office chair may be purchased so that the employee suffers less from back pain. Without an employee-related evaluation of absenteeism, the HR or personnel manager might not have noticed that such a problem existed.

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Which numbers do you measure?

It is of course up to the respective company to assess which HR-related figures represent key performance indicators. Absenteeism is often expensive for the employer and therefore certainly relevant to evaluate. However, it can also be interesting to record the reasons for termination (if possible) to work on eliminating these reasons in the future. Low employee satisfaction is related to dismissals on the part of employees. The KPIs to be considered important should be specified. Then it is necessary to determine at which point the data will be evaluated.
A lot of employee-related data is recorded in the HR department. It remains to check which data has already been recorded (and evaluated) and which KPIs are still missing. It should also be taken into account which employee has the skills and the time to carry out these evaluations (regularly). Perhaps it makes sense to commission different employees with different special evaluations: one employee who records absenteeism in the system evaluates this data, while another evaluates applicant-related data in recruiting.

It is advisable to carry out evaluations at least quarterly, every six months, and to be carried out annually to determine medium-term changes. However, weekly and monthly evaluations can help to react more flexibly. Employee XY was sick three times in a month? In such a case, a semi-annual or annual evaluation does not help – you have to react and help quickly.

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