The hr analytics guide

You didn't go into hr to be constantly busy with statistics, yet hr analytics can be valuable within your hr policy. How do these insights help your business? And how do you turn them into actions? This guide will help you on your way.

Contents

  1. What is hr analytics?
  2. Why is hr analytics worthy?
  3. Concrete application: absenteeism due to illness
  4. Hr analytics in Officient

1. What's hr analytics?

What does hr analytics mean?

Hr analytics of people analytics aims to support hr decisions with results from statistical analysis of hr data. These analyses are performed on the basis of different types of hr data. On the one hand objective data such as personnel data or trends such as employee turnover and absenteeism. On the other hand, subjective data is also used, which for example contains information about the effectiveness of training courses or the involvement of employees.

If you combine this data about your human resources with other relevant figures, and use statistical methods to find connections between them, then you are talking about 'hr analytics'. Analysing those relationships helps you to improve your hr policy, so your employees perform better, perform better and stay in your company longer.

How do you go from hr data to hr analytics?

Ask the right questions
Technological progress makes it easier to measure and store your hr data. The question then arises: What can you do with this data? You can start analyzing on good luck, hoping to find random action points in the results. However, if you as an organisation want to take concrete advantage of these analyses, it doesn't work that way. Instead of starting from the hr data, you should start by asking the right questions. Asking the right questions offers the possibility to take specific actions based on different results. But how do you start by asking the right questions?
See the problem from different angles
De eerste vraag die moet gesteld worden is: "Welk bedrijfsprobleem wil je oplossen?". Door te starten vanuit de bron van een probleem, wordt duidelijk waar de prioriteiten moeten liggen.

Volgens Alec Levenson, onderzoeker en consultant in hr-optimalisatie, wordt de focus nog te vaak op het individu gelegd. Hij pleit voor een multilevel aanpak die ook teams en business units mee in rekening brengt bij je hr-analyse. Zo krijg je als bedrijf een vollediger beeld van de situatie, wat dan weer tot concretere oplossingen moet leiden. Individuele problemen hebben vaak achterliggende redenen die we moeten zoeken op een hoger niveau, namelijk de werking van het bedrijf.
Example: Why do you have to take the bigger picture into account?
Suppose you want to tackle absenteeism and your hr analytics show that Mark is often absent. By only focusing on his data, you might decide that he is no longer motivated, and then you take that into account.

If you also look at his team, you might see that the relationships in the team are soured. So you'd be better off tackling the bully, wouldn't you? By taking another step back, you'll come to the conclusion that there's no real bully policy in the company. In this case, previous actions are only temporary solutions. To ensure that such situations don't happen again, you need to make changes at the highest level.

In this way hr analytics helps you to come to results and action points to have a real impact on business performance.

How can you implement the findings?

What do we ultimately do with the results from those hr insights? Although it seems obvious that something will be done with them, this is the step that is often forgotten. The results are stored somewhere, but remain there as forgotten data. As a result, no concrete action is taken.

People analytics should not be isolated from the rest of the company. Consistent cooperation between different parts of the company is therefore necessary in order to achieve positive results.

Alec Levenson believes that if we want to achieve results with hr analytics, engineers and hr managers must work together. In that vision, engineers help to optimize the analysis processes and hr takes care of the communication.

What about personal data of employees?

Because hr analytics uses personal data of employees, among other things, it is important that it is handled in an ethical manner. This means that the process must be fair and transparent. Always ask yourself the question: what do I want to achieve with the results and who will benefit from this?

Furthermore, the decisions must always be accountable. Rules such as the GDPR ensure that employees remain protected against unethical practices.

2. Why is hr analytics valuable?

Hr analytics helps you achieve your goals

Just like the company's other data driven departments, your department contributes to the results. The benefits of hr analytics can therefore also be extremely valuable for other departments, and vice versa. New insights help you to make more targeted choices.
Look for cause-effect relationships between hr data and data about the organisation's core business
. For example, you will gain insight into the impact of training on business results, or better understand why a certain department does not achieve its objectives. This is all information that you can use strategically to take bigger steps forward as a company.

Data analysis is also very useful within hr. It can support the decisions and initiatives that you want to take from your gut feeling, with or without objective knowledge. Although hr is always human work: the information you obtain by talking to employees cannot be replaced by a database.

Bottom line is that both make each other more relevant: the value of hr rises through data, the hr data are strengthened by the data of employees.

Translate data into insights

Now that you know what hr analytics is, the resulting insights can help you to make choices in your business strategy. Please note: no matter how useful hr analytics is, you don't have to go all the way. Find out what your company needs most. Or get to work with the data you're already collecting. You can get more out of it anyway.
Operational reporting

Collect data about what you do. How many people have you recruited in the past year? What training did the employees follow? How much does everyone earn? Keeping these figures up to date systematically, in a well-organised way, is step 1.

Advanced reporting
Make it a habit to keep track of information that shows how things are going in and with your organisation. Nowadays there are tools that follow the evolution day by day for you. This saves you the time to put all the numbers in reports. For example, measure inflow and outflow, absenteeism, salary, costs and so on.

Strategic analysi
s
With statistical models you learn how HR data influence other data and vice versa. You link the activities of the HR department to the business results. For example: what impact does absenteeism have on customer satisfaction, or do satisfied employees improve sales results?

Predictive analysis (predictive analytics, predictive HR analytics)
With more advanced statistics and centralised data, you can also predict what you can expect in the coming period. You combine patterns and trends in the data with models that give you a view of the future. Based on these predictive analytics you can plan better: is it useful to repeat a certain course? For which functions will you need to look for new people in a year's time? Do you need to take action to maintain employee satisfaction?

From insight to action

Back to the reason to start with hr analytics: making your business more successful. So don't sit back once your report is on the table. It's also important that you clearly inform your colleagues and employees of what the analysis has taught you. The better they understand why the policy is evolving in a certain direction, the smoother the adjustments will be.

3. Concrete application of hr analytics: absenteeism due to illness

Hr analytics has become an integral part of today's hr policy. Measuring is more than ever knowing. And there is nothing more important than knowing how your employees are doing. After all, the success of your company is in their hands, and you want to avoid burn-outs at all costs. But how do you map out absenteeism? These 6 figures will help you on your way.

What does absenteeism mean?

Absenteeism is a behaviour in which an employee stays at home due to illness. This is also called absenteeism. It includes all types of illness in which an employee is absent. Usually, however, we speak of absenteeism only if someone is excessively often sick reports. There are four different types:
  1. White absenteeism: the illness makes it impossible for the employee to carry out his/her work. For example, surgery, flu, pneumonia. There is no choice to go to work: it just doesn't work.
  2. Gray absenteeism: the employee is indeed ill, for example, due to headaches or a cold. The choice of whether or not to work is strongly influenced by the employee and his/her doctor. Motivation plays an important role in this type of absenteeism.
  3. Black absenteeism: this is not an illness, but the employee decides not to come to work anyway. Black absenteeism is sometimes also referred to as fraudulent absenteeism.
  4. Pink absenteeism: occurs when a sick employee does come to work. This can cause colleagues to be lit up as well. Moreover, the employee cannot rest and therefore cannot heal. This results in reduced productivity.

Hr analytics to measure sick leave

To prevent absenteeism, you have to know what's going on first. Thanks to these 6 hr metrics you can calculate the absenteeism for your organization:
1. Absence rate
The absenteeism percentage calculates what percentage of working days were actually absenteeism. This is an interesting figure to keep track of every quarter or year, so you can closely monitor its evolution.

The formula = (number of days absence x 100)/ number of days per year on which you should work.
2. Absence frequency
The absenteeism frequency will give you insights into how often employees report sick each year. It will show you the average number of sick reports per employee.

The formula = number of sick leave reports per year/number of employees
3. Average absenteeism due to illness
The average duration of illness will tell you how long your employees are absent due to illness on average in one year.

The formula = total number of days absence per year/ number of work resumes per year
4. Keep track of numbers
Map out how long your employees are absent. Are you mainly dealing with long-term sick people or are you more likely to be absent for short periods of time? Compare this with known figures in Belgium. For example, our partner Securex issues an annual report on absenteeism. In 2018, for example, employees were sick for short periods of time for more days. On average, the number of long-term absences remained the same compared to the previous year. Is this also the case at your company? Or do your figures differ from the rest?
5. Look for possible patterns
Try to pay close attention to certain patterns in your absenteeism. Keep a record of the days on which people report sick. For example, a large number of sick reports on Wednesday afternoons may show that there is a problem with childcare.

Although you won't be able to change much about some things, it is also possible that the cause is work-related. For example, a poor work-life balance or a general dissatisfaction at work can cause your employee to choose not to come to work even though it may be possible. Therefore, keep a good record of these data, both on a personal and organisational level.

The Bradford factor

The Bradford factor starts from the observation that it is more expensive for an organization when an employee reports sick for several short periods, compared to less frequent but longer periods. After all, short, unplanned periods of illness are often more difficult for a team or organization to cope with.

In addition to measuring the total number of sick days per employee, the Bradford score gives insight into the impact of absenteeism.

The name 'Bradford' comes from the Bradford University School of Management, where the formula was developed in the 1980s.
How is the Bradford factor calculated?
The Bradford formula is: B = S² x D

Whereby:
  1. B = the Bradford score
  2. S = the number of different periods of illness for a given employee
  3. D = the total number of days of illness for a particular employee
The reference period is usually the last year, below you will find some examples:

Stef has been absent for 10 consecutive days during the last year due to illness.
The Bradford score for Stef = (1²) x 10 = 10.

Julie has been sick 2 times 5 consecutive days during the last year.
The Bradford score for Julie = (2²) x 10 = 40.

Kurt has been sick 10 times 1 day during the last year.
The Bradford score for Kurt is the highest = (10²) x 10 = 1000.

In Officient, the Bradford score is automatically calculated based on the available sickness data of each employee. Each day of illness is kept in the calendar that is sent to the payroll provider at the end of the month.
What is a good or a bad Bradford score?
In general, the higher the Bradford score, the worse. After all, multiple short, unplanned periods of illness weigh more heavily. Sometimes organizations link certain threshold values to the scores, each time with a corresponding action, for example:
  1. Score from 51: verbal warning
  2. Score from 201: written warning
  3. Score starting at 401: last warning
  4. Score starting at 601: sometimes leads to dismissal
Specifically, how are you going to work with the Bradford factor?
In addition to the total number of days of illness, the Bradford factor therefore offers an interesting measure of absenteeism. Nevertheless, the Bradford factor is sometimes criticized, especially if it is the only measure used.

Tackling absenteeism fits best within a broader policy. Loose actions do not always have a sustainable effect and employees sometimes react differently to actions taken. So always view the Bradford score as a useful first step towards further analysis of the problem and finding possible solutions.

4. Hr analytics in Officient

Hr analytics is not one of the main modules in Officient. But although we mainly focus on hr-administration, we still believe in the value of hr insights. We experience that they make it easier to report and, more importantly, to detect problems early. That is why we also offer insights into data on wages, persons and absences.