What Is Recruitment Analytics? (Plus Types and Benefits)
The hiring process is extensive and requires a lot of data input to help you hire and onboard new employees. Using recruitment analytics is one way to gather the right data for the hiring process and organize it in a more efficient and productive way. Understanding what recruitment analytics is, how to use it and the types of analytics can help you make your hiring process better. In this article, we explain recruitment analytics, their benefits, the stages of recruitment analytics and the different types you can use.
What is recruitment analytics?
Recruitment analytics is the data you collect during the hiring or recruitment process. Using this data, you can identify important trends in your hiring processes, trends among new hires and other information to help improve the hiring process. Recruitment analytics helps organizations answer crucial questions about the hiring process, including:
- Where can the company find the best candidates?
- How much does it cost the company to search for, recruit, hire and onboard a new employee?
- What are some common traits or attributes that the company’s best hires have in common?
- What part of the recruitment funnel experiences the highest number of losses, and why?
- What part of the hiring process needs the most improvement?
- How effective is the onboarding process at assimilating new employees into the company culture?
Benefits of recruitment analytics
Analyzing recruitment analytics offers many benefits to the modern business, including:
Reduced onboarding costs
By analyzing your onboarding costs, you can create a more cost-effective recruitment process to save the company money. For example, if you’re using an expensive recruitment platform that doesn’t yield ideal results, you might look for another tool to help you find better candidates and spend less money. Recruitment analytics also help you understand financial trends in your recruitment process so you can reverse or improve them as necessary.
Better candidates
Using recruitment analytics helps you identify the best qualities each of your best hires brings to the job. By identifying these traits, you create a more complete profile of your ideal employee, making the hiring process simpler since you’re only looking for candidates with those qualities. For example, if all of your best hires have the same passion for their industry, you might look only for candidates who display a passion for the industry. By doing so, you’re replicating something that already works well for the company instead of trying something new. This can help increase the quality and consistency of your new hires.
More efficient hiring process
Recruitment analytics allows you to look at your hiring process on a larger scale through a collective of diverse data. By analyzing financial costs, candidate similarities, challenges in your hiring funnel and where you’re getting candidates from, you can identify setbacks and develop greater hiring efficiency. Recruitment analytics can help you see exactly where your recruitment process needs improvement so you don’t have to work through several channels to get a definitive answer.
More effective assimilation
When you analyze your recruitment process and fix the problems in it, you can create a more efficient and streamlined assimilation process for new hires. If a new hire can quickly adjust to the company culture, work schedule and duties, they may be happier long-term in their position. An efficient hiring process can make assimilation much simpler and reduce the extra workload that sometimes accompanies recruiting new hires.
More diversity
Recruitment analytics also helps you discover demographic information about your company, which can help you diversify your workforce with people of different races, backgrounds, genders and experience. A more diverse workforce is often more productive and diversity can help create a rich company culture. Using recruitment analytics allows you to find new candidates through different channels to ensure you’re keeping your workforce diverse.
Stages of recruitment analytics
There are three main stages of recruitment analytics to consider, including:
Operational reporting
The first stage of recruitment analytics is operational reporting. This stage includes several of your most well-known recruitment metrics, such as:
- Cost of recruiting new hires
- Number of applicants per job opening
- Number of interviews conducted
- Selection ratio
- Time to hire
- Manager satisfaction
- Time to fill
These metrics typically don’t require any specialized software or tools to measure. For example, you can measure the number of job applicants by opening your career site dashboard or physically counting and adding the total number of applications you receive. Operational reporting is only the starting phase of recruitment analytics and provides a base of core information for your recruitment process. From this base, you can build more specific, direct information from the other two stages.
Advanced reporting
Advanced reporting is the second stage in the process and involves much more specific information. This stage requires multiple sources of data and takes into consideration things like new hire behavior, attitudes and assimilation into the workplace. You might measure metrics like these during this phase:
- Cost of recruitment per job candidate
- Cost of recruitment channels
- Recruitment funnel conversions
- Employer branding
- Minimum slate
Metrics like minimum slate, or the minimum number of qualified candidates the hiring manager needs in order to being the interview process, help employers discover more about how the company conducts its hiring process. You can also learn how employees respond to the process and what recruitment channels are working for the business.
Analytics
The final phase of your recruitment analytics process is the analytics phase. This stage is where strategic and predictive analysis become components of the company’s hiring process. Using the data you gather during the first two phases, you can create predictive models for any part of the hiring process and use those models to enhance your recruitment strategy. For example, if you determine that your main recruitment channel might only produce three to five qualified candidates per month versus eight to twenty with another company, you might switch recruitment channels. You can also predict things like time to hire, create ideal candidate profiles and determine the future costs of hiring for certain positions.
Types of recruitment analytics
There are many types of recruitment analytics. Here are a few for reference:
- Time to fill: This is a measurement of the time it takes for the company to fill a vacant position.
- Time to hire: This metric tracks how much time elapses between the onset of the recruitment process and the onboarding of a new employee into the company’s workforce.
- Cost per hire: This is a measurement of the total cost of each hire, including any onboarding, recruiting or other costs.
- Source of hire: This metric tracks which recruitment channels produce the best hires for the company so you know where to focus your resources.
- First-year attrition: This metric tracks the attrition of new candidates in their first year, or how enthusiastic they are about their position during year one.
- Applicants per opening: This metric tracks how many applicants each job opening receives.
- Offer acceptance rate: This metric tracks how many candidates accept an offer of employment versus how many decline the offer.
- Sourcing channel cost: This metric tracks the cost of each sourcing or recruitment channel.