Hiring the right candidate is a tough job. A Monster study indicates that 9 out of 10 employers struggle to fill a position faster with 29% agreeing that the growing skill gap can be the foremost reason. With multiple stages of recruitment to developing a qualified pool of candidates and a continued effort to build a better employer brand, recruiters and hiring managers are constantly put to the test to justify the return on investment of their efforts. The pressure is further magnified when the cost of losing a good hire is $30,000 and onboarding a bad hire is $15,000, as detailed by a CareerBuilder study. Thus, recruitment analytics is crucial in transforming the hiring process into a more precise and strategic endeavor.
Whether analyzing the job description, tracking candidate experience, calculating time to hire, or identifying the quality of hires and cost per hire, several key performance indicators combine to become the core of recruitment analytics. Using these recruitment metrics, one can enhance their recruitment strategies and make more informed hiring decisions that lead to better quality hires every time. This blog expands further on the importance of recruitment analytics and throws light on how you can use it in your day-to-day recruiting practices.
Is Recruitment Analytics Necessary?
Analytics has been at the center of business processes and decision-making, across the globe, and one of the primary use cases of data analytics has been in recruitment. A Deloitte study further instills this fact, reporting as much as 71% of companies understand the importance of recruitment analytics in their organization.
So, yes. Recruitment analytics is key to a sustainable recruitment strategy, especially in the recent job market.
A well-planned recruitment analytics process can help you identify the loopholes in your hiring process and clear the air on critical hurdles that hiring managers often face. Troublesome stints like candidate drops, extended time to fill, and falling offer acceptance rates can be discovered and fixed in time with continued practice of data gathering, tracking, and analyzing.
Not just in hiring, but monitoring and maintaining consistency in your recruitment data analysis habits can help you attract more qualified candidates who align with the company goals and maximize the productivity of the organization. It’s simple, data can give you all the answers you need, provided you know how to track it. So, recruitment analytics is one of the pillars of your hiring process that will help you become a better recruiter.
Integrate Recruitment Analytics in Your Hiring Practices
Having a solid background in data management and analysis is not the primary requirement for an HR to be able to execute recruitment analytics into their hiring funnel. With several recruiting tools and applicant tracking systems at your disposal, getting a grip on the data that compliments your strategy shouldn’t be a complicated task.
The basic function of incorporating analytics into your recruitment practices is to gather data from a variety of sources including ATS, resume screening tools, career pages, CRM, application forms, interview softwares, and social media, among others. What you need to consider is the quality of the data that comes from these channels and what KPIs you need to track. The better the quality of data the higher the quality of insights you have.
For example – Skima AI provides comprehensive insights into your candidate pool, helping you uncover the best-fit candidate for a particular role. It uses AI and Machine Learning to analyze your candidate pool against a job role and identify the most suitable candidates. With a clear dashboard, one of the primary components of recruitment analytics, you can visualize everything for candidate relevancy to the quality of your pool and more. With such information, you can reduce the time to fill and refine your candidate database.
There are also ATS and HR software dedicated to recruitment analytics that delivers a centralized view of data coming from multiple sources, including tools like Skima, job boards, and more. An ideal recruitment analytics dashboard provides real-time updates to enrich your understanding of process performance and outcomes. It visually tracks your KPIs and key data points, offering a centralized location for monitoring and analyzing your HR department's impact on strategic business goals.
Deploying Recruitment Analytics
Identify KPIs
Although it's advisable to incorporate recruitment analytics at the beginning of a hiring journey, factors like the stage of the hiring process or the longevity of a recruitment strategy largely wouldn’t influence your plan to go on the floor. However, if you want to add SaaS-based recruitment analytics software into your process or plan on manually tracking data, the first thing you must figure out is the KPIs you must focus on. To do so, you must reflect on your hiring strategy and put an effort into finding the issues that are crippling it. It can be a negative candidate experience, offer acceptance rate, quality of hire, or simply the ratio of qualified candidates to the number of applications.
Promote a data-first approach
Employing the right tools is only the first step. Next is incorporating a data-first approach in your day-to-day recruitment activities. Not just you, but your entire team, handling various aspects of the recruitment process, must adhere to a culture that practices data gathering and analyzing. Everyone must also go through a formal practice to garner the skills required to understand, monitor, and analyze various types of recruitment data. While one doesn't have to be an analyst, it’s always a plus to learn the right skills.
Connect analytics to business outcomes
The overarching goal of tracking your recruitment efforts is to help businesses achieve their goals. So, you must use analytics to answer questions related to business processes. For instance, demonstrating the value of 'quality of hire' (QoH) can be tricky when it comes to measurement. However, by breaking down QoH into measurable components like new hire retention rate, new hire performance, and time to fill, you can clearly show its direct impact on the business.
3 Stages of Recruitment Analytics
On a holistic level, recruitment analytics can be bifurcated into three levels. Each level has its own significance in the recruiter journey.
Operational Reporting
The first stage in recruitment analytics is operational reporting. Here the focus is on the hiring metrics like cost of hiring, applicants per open position, time to fill, and time to hire. As we have understood earlier in the blog, using analytics, you can find answers to questions related to your hiring metrics or key performance indicators. Operational reporting gives you a clear picture of various metrics and assists you in adjusting your recruitment funnel as needed.
With operational reporting, one can also evaluate the effectiveness of the recruitment staff. Insights into employee performances and areas of inefficiencies and improvements can be identified by practicing operational reporting. If you want to gather operational-level data, your best source is an ATS that can collect all the data from various sources, help you track the dedicated KPIs, and provide detailed visualizations.
Predictive Analytics
Next is predictive analytics. With the advent of concepts like artificial intelligence, deep learning, and machine learning occupying a larger role in the recruitment industry, several tech vendors have already begun incorporating these innovations to enhance predictive capabilities within their recruitment analytics solutions. Predictive analytics is based on both recent and historical data. Using the data, one can anticipate behaviors, trends, and outcomes of specific processes. This stage focuses on statistical analysis, segmentation, and developing candidate personas. These elements help you build hiring models that predict future staffing needs and allow for strategic planning.
From projecting time-to-fill for open positions to estimating future candidate performance, predicting the likelihood of interview acceptance and more, predictive analytics infuses objectivity into your decision-making by relying less on subjective perspectives and more on actual data.
Advanced Reporting
While operational reporting gives you an overview of the most common metrics in recruitment, advanced reporting goes several steps ahead and allows you to examine your recruitment processes in greater detail. It gives insights into KPIs like cost per candidate, recruitment source analysis, employer branding, and recruitment funnel conversion rates.
To take complete advantage of advanced reporting you must be able to collect data from multiple sources. An example would be, sending questionnaires to candidates post-interviews to get their feedback and use the data to examine candidate experience. Additionally, tools that measure your employer's brand and reputation can help determine if your efforts to attract top talent are effective.
End Note
Recruitment analytics is a continuous process that’s necessary to incorporate into your hiring process. With streamlined recruitment analytics, you will be able to find answers to complicated recruitment questions, build better hiring funnels, and make more informed hiring decisions. Choose the right analytics tools and get started, today!
