In the course of digitalization, companies are increasingly making more data-based decisions. The development towards a “Data Driven Company” is becoming the new status quo. For example, traditional reporting is becoming more and more dynamic through the use of modern business intelligence tools, right up to “self-service BI”, in which users can create analyses independently.
But the digitization trend has already reached human resource management as well. Recruiting in particular benefits significantly from the increasingly transparent and intuitive BI solutions. These allow users to present processes in an appealing and understandable way.
The recruiting funnel is the tool of choice in this context. This shows the number of applications for each step of the recruiting process. Conversion rates can be determined between the individual process steps, providing important insights into the recruiting process:
- Forecast: Based on the status quo, recruiting activities can be planned for the future
- Benchmarking: Comparison of different perspectives on the recruiting process can be compared with each other & clarify deviations, as well as outliers
- Control: The comparison of different time periods clarifies the effects of actions taken and makes them measurable
In principle, the recruiting process can be started and examined at any early stage. Thus, a recruiting funnel can already start on the career website with the first visit to the homepage and end with the submission of the application.
In this article, the process begins with the receipt of the application and ends with the hiring or rejection:
Abfig. 1: The diagram starts with the number of applications received and tapers off through the process steps up to hiring. The percentages refer to the conversion rate between the individual process steps.
Plan recruiting measures
Let us assume the following scenario: The annual plans show that the most recently recruited experts have made a gratifying contribution to the company’s development. In addition, plans show that two more positions will now be filled for the coming year. With the recruiting data from the status quo, it is possible to derive how many applications it took per process step to fill the two expert positions. Projecting the data into the future gives a number of applications needed to meet the target.
If data is now available for all future positions, it can be aggregated to form an overall picture. Possible bottlenecks and capacity limits become quickly apparent and recruiting activities can be prioritized based on data.
Figure 2: Aggregated key performance indicators (KPIs) provide an overview of all process steps and show important conversion rates.
Potential for improvement in the recruiting process
The data of an application contains a lot of detailed information. For example, each application shows where it came from, the applicant channel from which it was received, as well as the applicant’s salutation, or the desired entry/hierarchy level, to name just a few parameters. This detailed information is called “dimensions” in the BI context. With their help, key figures such as the number of applications per process step can be displayed in groups. Looking at the application start dimension, different dimension elements (online, direct approach, email, recruitment agency) can be compared:
Figure 3: Different dimensions enable a detailed examination of the recruiting process and a comparative analysis between dimension elements.
The comparison to the overall average, also called “benchmarking”, can clarify deviations. These can serve as a reference point to analyze certain processes in more detail and thus derive explanations for high deviation. If conclusive correlations can be deduced, measures can be taken to improve all processes in this respect.
Present and evaluate measures
Measures to increase the efficiency of the recruiting process are best assessed with a suitable frame of reference. In this way, specific targets can be defined and tracked with the help of a target/plan/actual analysis. Reference periods (Year-to-Date, Month-to-Date, etc.) are also suitable for measuring measures. The following illustrates that the initiative to generate more applications from LinkedIn was successful. There, it is hoped to record higher conversion rates:
Figure 4: Development of different application sources with a reference period (here: month to date).
Conclusion
Digitization has made extensive data available to HR. These should be used! Modern software solutions provide fast and valuable insights. The examples listed here are taken from our recruiting template, which is based on the recruiting software from the company d.vinci based.
Felix Rehm
Head of Business Unit Business Analytics
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