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Filling vacancies is only part of the hiring journey. Recruitment analytics plays a pivotal role in helping talent acquisition leaders make strategic decisions that lead to a stronger, more successful and equitable workforce.
Leveraging these analytics offers companies the data insights they need to streamline their recruiting funnels, improve the caliber of candidates and hires, and manage and reduce costs wherever possible.
Want to achieve more with your hiring data? Keep reading to explore the core benefits, key metrics and industry tools for recruitment analytics that deliver invaluable benefits for talent acquisition leaders.
Recruitment analytics is the practice of using data-driven insights to optimize hiring practices and strategies. It involves gathering, analyzing and interpreting recruiting data to identify trends, flag gaps and improve the company’s overall hiring performance.
When recruitment analytics are used to their fullest benefit, talent acquisition leaders can make informed decisions to increase team efficiency, reduce hiring costs and secure top candidates.
For instance, talent acquisition teams can analyze recruitment data to make targeted improvements to bottlenecks—such as laborious, multistage interview processes.
By compiling data from different sources, talent acquisition teams get a 360-degree view of hiring processes. This empowers talent acquisition teams to identify inefficiencies in their workflows and make strategic changes.
Example: A global hotel chain used recruitment analytics to spot a worrisome delay in its candidate screening process. By automating CV screening with an AI-driven applicant tracking system (ATS), they reduced time-to-hire by one-third and freed up recruiters to focus on higher-value activities.
A data-driven approach makes it possible to select candidates with greater precision and improve hiring outcomes. It can even help talent acquisition teams pinpoint the traits and qualities that help candidates thrive in specific roles based on data on current star employees.
Example: Frustrated by a string of unsuccessful hires, a major bank used recruitment analytics to evaluate the attributes of its top sales representatives. Using this data, recruiters refined their job ads and sourcing tactics to look for candidates with similar professional backgrounds. These changes lead to a 25% surge in stellar, high-performing hires.
Recruitment analytics enables acquisition teams to understand the cost breakdown of recruitment processes from start to finish. This insight allows them to spot unnecessary expenses and optimize hiring budgets for the best possible return on investment.
Example: Upon evaluating its recruitment spend, a retail giant found its costly job board was yielding fewer quality hires than referrals from current staff. The company opted to redirect funds toward a new employee referral program. This move improved its hire quality—plus, slashed onboarding costs by 30%.
Recruitment analytics give talent acquisition teams the necessary insights for building a more inclusive workforce. It can reveal demographic trends at every stage of the hiring funnel and even show where unintentional bias may be affecting decisions by recruiters.
Example: Committed to its diversity, equity and inclusion mandate, a marketing agency analyzed its diversity metrics at each hiring stage. It discovered that the résumé-screening process was influenced by unconscious bias. To course-correct, the talent acquisition team adopted “blind” reviews, which resulted in a 20% boost in hires from underrepresented demographics.
Operational reporting is the first and foundational stage of recruitment analytics. It includes the initial metrics needed for establishing performance baselines and identifying areas for immediate improvement.
Recruiting data and insights collected during this stage include:
These metrics offer a quick snapshot of how well your hiring process is working. Most importantly, they help spotlight easy wins—areas where small tweaks can lead to noticeable improvements, fast.
Example: A company tracks time-to-hire across departments and finds that one division often trails behind others. With this information in mind, it restructures its interview processes to accelerate decision-making.
During the second stage, advanced reporting dives beyond surface-level metrics to find patterns and correlations in recruitment data.
By pulling from multiple data sources, recruiters are able to collect more in-depth insights and refine their hiring strategies with more precision.
Here are some metrics recruiters might measure for advanced reporting:
Advanced reporting helps recruiters diagnose the root cause of any issues, such as funnel bottlenecks, overspending or slow time-to-hire for specific vacancies. On the flipside, it can also identify wins for the company.
Example: A law firm notices that graduates from a specific university tend to stay longer with its company, perform better and advance quicker. Armed with this knowledge, it focuses its campus recruitment efforts at that school to source more high-potential talent.
In recruitment analytics, predictive reporting is its final and most sophisticated level. This stage uses historical data and AI algorithms to forecast future hiring needs, candidate success and trends in the talent market.
Recruiting shifts from reactive to proactive and makes it possible to track:
The powerful thing about predictive reporting is it empowers recruiters to anticipate and address challenges before they arise. That means it’s easier to align efforts with long-term business goals and develop a more strategic approach to hiring.
Example: By analyzing hiring patterns alongside growth metrics, a tech startup predicts a surge in demand for software engineers in Q2. Its recruiters act quickly to boost sourcing and build talent pipelines weeks in advance, so new hires are trained and ready to go when needed.
Hoping to transform your current hiring process into a stellar one? Start by monitoring and evaluating these core recruitment metrics:
Want a more detailed breakdown? Access the iCIMS guide on recruitment metrics for a deep-dive into their use and how to leverage them with success.
An ATS supports talent acquisition teams by automating and streamlining the full hiring process.
Throughout the candidate lifecycle, these platforms collect valuable data and act as a centralized hub for managing job postings, tracking applications, and communicating and engaging with candidates.
Use cases:
Recruitment marketing software helps companies target, engage and convert job seekers into successful candidates. These solutions are used to build brand awareness, create compelling content and deliver personalized experiences to attract top talent.
Use cases:
Data visualization tools turn complex data into easy-to-read visual reports, such as charts, graphs and maps. Users can explore data, spot trends and gain insights with more ease than when faced with the raw numbers alone.
Use cases:
Popular tools: Google Charts, Google Data Studio, Microsoft Power BI, Tableau.
Recruitment analytics can jumpstart your talent acquisition strategy in a myriad of ways—whether you’re hoping to upgrade your candidate pool, reduce costs or supercharge your hiring pipeline.
The secret is starting with the right technology. Leveraging purpose-built tools such as an AI-powered ATS, recruitment marketing software and data visualization solution helps to align decision-making with long-term business goals.
Ready to get started? Request a live demo of iCIMS’s enterprise applicant tracking system, and learn how harnessing recruitment analytics is easier than you think.