How Recruitment Analytics Optimize the Hiring Process

Recruitment Analytics: Optimizing the Hiring Process With Metrics

Recruitment analytics play an increasingly important role for HR professionals and their executives. When it comes to finding, selecting, and hiring employees, recruitment analytics help make more effective data-driven choices. In this guide, we explain what recruitment analytics are and how to use them for optimization of the company’s hiring process.

What Are Recruitment Analytics?

Recruitment analytics are tools and metrics used for identifying and interpreting employee search and hiring patterns. Suppose newcomers leave the company within the first three months. It could indicate a mismatch between the job description and the actual position, a recruitment mistake, or an ineffective onboarding process.

The standard data sources to retrieve the results of analytics recruiting professionals use include:

• Applicant Tracking System (ATS)
• Customer Relationship Management (CRM) software
• Human Resources Information System (HRIS)
• Satisfaction surveys
• Advertising sites used for vacancies’ promotion

Why Should I Use Data-Driven Hiring?

Recruitment analytics can answer various questions, such as:

• What sources offer the best candidates?
• What is the cost of hiring candidates for each position?
• What characteristics do the best candidates have in common?
• At which point in the recruitment funnel do most candidates drop out?

The ability to answer these questions can significantly improve the efficiency of decision-making in the recruiting process. Here are some advantages that make analytics recruitment irreplaceable for professionals:

Metrics allow you to see the real picture of what is happening in the company.

With their help, you can identify weaknesses in the process that require timely improvement.

The HR manager receives objective information, which simplifies recruitment process management.

The HR manager and company leader find common ground better since they operate with numbers instead of assumptions.

Key Recruitment Metrics

There is a wide variety of metrics used in recruitment analytics. Typically, companies prefer to track the following:

• Source of hire
• Time to hire
• Applicants per hire
• Cost per hire
• Candidate experience
• Yield ratio
• Retention
• Offer acceptance per hire
• Quality of hire

One metric cannot give a reliable overview of the recruitment process. It is essential to select recruitment metrics depending on the company’s needs. Read ahead for a detailed description of some of the most used recruitment metrics.

Average Time to Fill Vacancies

How much time do you spend filling vacancies? The count of the average time for filling vacancies starts when a job opening appears until the moment when the candidate receives and accepts the offer. Next, we calculate using the formula:

Time to fill = the number of days to fill all available vacancies for a certain period/total number of filled vacancies for a certain period

This recruitment metric can give the HR manager a sign to pay more attention to the recruitment strategy or try a different vacancy promotion method. To improve the time to fill, you can break down this metric by departments to see where issues are present.

Cost per Hire

Any business owner wants to know how efficiently the recruitment funds are being spent. Based on this metric’s data, you can conclude where to invest the budget, such as hiring HR employees or ATS, which will take your recruitment to the next level.

Internal and external costs determine the cost per hire (CPH) in recruitment analytics. The internal costs are the personnel expenses of the company, such as:

• Recruiters’ salaries and bonuses
• Bonuses for referral programs for company employees
• Interview costs (number of interviewers’ and managers’ working hours)
• Administrative costs associated with the interview
• Software costs
• The external costs include:
• Job advertising
• External bonuses for candidate recommendations
• Recruitment agency costs
• Paid recruiting tools

The CPH formula is as follows:

CPH = (internal costs+external costs)  for a certain period/the number of hired employees for a certain period

Yield Ratio

At each stage of the recruitment funnel, you filter out some candidates, while others prefer not to continue themselves. Knowing the yield ratio will allow you to understand what is common among the candidates who do not proceed to the next rounds of the interview and what is similar among those who succeed.

Yield ratio of stage N = number of applicants who completed the stage successfully/total number of applicants who entered this stage

The collected data and its interpretation are often used in a recruitment report.

How to Write a Recruitment Report

A recruitment report reflects the progress of the hiring process and the tools used in its duration. The responsible HR professional typically submits it to the higher managers. The recruitment report creation usually consists of five essential steps:

1. Basic information. Make sure the report contains the recruiter’s personal data and the date when the document was completed.
2. A list of the hired candidates. It is a part where the recruiter describes in detail the selected applicants, mentioning their full names, contact details, and job position.
3. Used resources. Here the recruiter mentions the budget spent on recruitment and other valuable data derived from the metrics.
4. Description of the encountered issues. If the HR specialists came across any problems throughout the hiring process, it is worth listing them in this section.
5. Conclusions. It is a summary of the report, concisely stating whether the expectations have been met and suggesting what can be improved in the future.

Recruitment reports allow you to:

• Find out how many interviews a recruiter conducted in a certain period
• Understand the effectiveness of job advertisements
• Determine the recruiter’s speed and overall performance
• Optimize the hiring expenses

Such reports are essential for proper recruitment analytics, as they help to systemize the data offered by the metrics.