The recruitment market has been challenging for many industries in the last couple of years. Phenomena such as The Great Resignation or Quiet Quitting have seen many businesses face record challenges recruiting and retaining staff. It’s estimated that 40% of the global workforce are planning to quit their jobs. Which is presenting unprecedented challenges for recruiters and employers. And with the cost of a bad hire estimated to be as much as 30% of that employee’s first year salary it’s rarely been more important to understand your employees and the recruitment process in your company.
This means understanding the data behind the human story. Many organizations and HR departments will already have a great deal of data. So it might make you wonder- why do we need specialised analytics when so much is collected routinely? But without organization or direction, much of that data is of little use. HR analytics allows employers and recruiters to answer specific questions about employee turnover or behaviour, and spot patterns. In turn this can be translated into meaningful initiatives that identify and retain the best talent for a business.
So, how exactly can HR analytics effectively drive positive change in a company?
One of the key benefits of HR analytics is that it can be broken down into many blocks or metrics. So you can look at problems specific to hiring, turnover, or the mood and wellbeing of a team. The process works by measuring the state of a certain metric before a change in company procedure is made. Measurements are then taken after those changes.
1)Retaining and recruiting- In one company I looked at the percentage of offer refusals and learned that the focus on interview tasks was important to candidates. We then changed the interview process and as a result the percentage of refusals decreased. Analytics are also helpful for turnover. Say you’re seeing staff turnover mainly among a bracket of those who have been with you three to five years, this indicates that employees are reaching their development ceiling and not receiving the tasks or challenges they need. As a result they’re looking to other companies to provide those. Analytics can therefore identify the critical moments for retaining staff. It is also key for making informed decisions about talent acquisition and retention and streamlining that process. For example, there may be a situation where there are 70 vacancies in a workplace. The recruiting department is composed of ten people who can conduct three to four streams at a time. The average vacancy closing rate is two months. This means that there can be as many as 30-40 vacancies simultaneously over that two month period. Which creates a backlog. If it is a role that needs to be filled quickly many people would look at the above situation and conclude that the solution is more recruiters. But analytics can help you identify stages that candidates drop out of the recruitment process and adapt accordingly.
2) Budgeting- HR analytics can also help to budget. If you know that the average recruitment length is two months it is possible to factor the cost of this into your monthly forecast. It also illuminates the economic benefit of retention. The process means you can analyse which employees are key members of the team with overlapping blocks of tasks. It’s then possible to consider how much it costs to attract a new employee over retaining the current one.
3) Company wide issues- HR analytics can also help identify wider problems within an organization. Staff turnover is one such issue. In one company I asked for a report on turnover and it transpired that the turnover rate was 30%. This is a high figure. Consequently I automated the report and began including metrics such as: how long the employee had worked in the company, the departments they had worked in, and their reasons for leaving the company. The analysis showed that there were departments where specialists were leaving having worked less than a year, while the core staff had been working in these departments for more than five years. From this we concluded that the department was simply unreceptive to newcomers, which meant that there was an issue with on boarding and team atmosphere. By identifying these we were able to reduce the turnover rate to 17 percent in a year.
Are there any negatives or risks to HR analytics?
Before implementing a process you have to know why you are doing it and what data you are trying to find before you start. Without a clear objective it is possible to get misled by the data that is gathered. Another risk is that analytics requires the right tools, implementation and configuration. This entails time and resources. Therefore the best way to start adopting an analytics program is by beginning with small, specific tasks or problems within a company. Once you have done this it will be easier to implement a company wide program.
How do you begin to successfully implement HR analytics in your organization?
The first step is to define the problem that you’re solving. So this might be retention or understanding patterns in employee behaviour. It’s then possible to build a hypothesis of how to check this problem and define what numbers may tell us. So, for example, I wanted to understand how personnel were strengthening a team. I knew I would be interested in metrics such as hiring, turnover, recruiters’ KPIs and hiring satisfaction. Next I had to understand which of those numbers carried information of use and which did not. For example, what does the number of interviews for a department or role say? Is it better to look at the recruiter or the role itself? Once you have established your metrics the next step is to decide whether it is possible to automate these metrics and how reports will be issued.
Ethical concerns
Like any analytic or automated process it’s important to think about its ethical ramifications and consider which figures can be reported on or included in a company wide presentation. So for example, there may be departments that have a particularly high turnover of staff. But to report that figure without fully understanding it would be unethical. We cannot make assumptions on the face of the initial numbers and data we receive. Instead we need to dig deeper and gain a full understanding. Context is incredibly important. This is also true in regard to balancing the use of analytics in managing employees and maintaining a positive company culture. An example of this might be a questionnaire. If 300 out of 1000 people in the company report feeling overloaded this is not necessarily an indicator that this applies to the whole company. Figures are important but they need to be supplemented with personal communication and human interaction to understand problems that arise in a company.
How should you communicate your findings to stakeholders and employees?
Presentations and workshops both work effectively. Firstly, I lay out a theory which leads into a discussion regarding the problems there may be. Next I show examples from other analytics, research reports and figures. When presenting a report I start by explaining the problem, then the hypothesis I put forward and the method used. So for example, an employment report may illustrate an inability to fill hiring needs. So my hypothesis would be a long hiring cycle and salaries being offered below the market norm. The tools to analyze this are a salary review and the recruitment funnel. With this information it is then possible to build a complete diagram of the hiring process and find suggestions for improvement.
HR analytics is a powerful tool for understanding your employees. It means that you can make informed decisions about your workforce. These translate into better teams and ultimately into higher revenues. Integrating them can be challenging. But with many recruiters continuing to face challenges and hiring shortages it’s becoming ever more important to start to understand the numbers behind the people in your company.
