Data-driven decision making
Recruitment is a task which is crucial to an organisation’s success, as the process forms the crux of an organisation’s talent pool. Since poor hiring decisions can lead to long-term negative effects on the organisation’s growth, it is imperative to adopt modern, more evolved ways of hiring. This is why the most advanced companies are turning to data-driven decision making – recruitment analytics. The important recruitment analytics tools bestow upon the recruiters the power of data, which allows them to track the best sources of hiring, identify top hires and streamline the hiring process. When you have a vast pool of data pertaining to your candidates – such as how long job seekers stay in each interview stage – you don’t have to depend on arbitrary criteria or snap judgements for hiring. You can seamlessly move through the hiring process with a good ATS (Applicant Tracking System) that offers useful features such as the ability to post on various job boards and automated resume sourcing using AI.
Recruitment analytics in the hiring process
Recruitment analytics metrics are of great help during the hiring process, as they allow absolute objectivity in your decision making. By using data and algorithm-based predictions for hiring decisions, recruiters are able to remove their biases from the process, which results in improved outcomes.
Predictive recruitment analytics allows you to identify your most effective sourcing platforms from social media, job boards, referrals, among others. It can provide insights into candidate screening techniques, lead times, employee performance prediction and retention rates. In addition, recruitment analytics metrics also include future employment needs and hiring roadblocks, allowing you to navigate the process in a well-informed manner.
Recruitment analytics in the onboarding process
The onboarding process is more important than what some employers might think. In fact, successful onboarding can improve employee performance by 15%, as shown by a study. Thus, having a proper, structured onboarding program in place can be incredibly helpful in ensuring a given employee’s success in the organisation. One of the easiest ways of doing that is recruitment analytics, as it provides access to meaningful data that’s capable of making a change. Firstly, you can perform diagnostic analysis and establish cause and correlation for trends such as understanding how the onboarding process is affecting a candidate’s tenure at the organisation. Next, you can measure the time it takes for recruits to start generating value as effective onboarding reduces the time-to-productivity. Lastly, a good ATS will give you relevant information about the new recruits during the onboarding process.
Recruitment analytics in talent management
There have been immense leaps in talent management since the advent of recruitment sourcing analytics as the market for talent management tools is projected to grow 13% by 2027. The first step is to attract strong, high-quality candidates, which is made easy thanks to the insights that a recruitment analytics report gives recruiters. Good ATS such as Wisestep offer intelligent JD parsing, as they derive the relevant job parameters from the JDs and create jobs effortlessly. With actionable data, recruiters can now understand the right questions to add in job postings to attract the right talent. When it comes to retaining talent, predictive recruitment analytics offer the much-needed insights on the kind of talent that will stay in the given organisation for long-term.
Recruitment analytics in HR technology
HR technology is all the rage now, as new-age recruiters embrace technology to enhance their HR processes, with the shift being bolstered with the remote work trend. HR technology encompasses a plethora of tools and business functions including talent acquisition, attendance tracking, payroll and performance management, among others. These functions are being digitised or automated in order to make them more efficient. Although recruitment analytics is mostly used for the hiring process, it is increasingly employed to strengthen other HR functions such as to understand which management practices work best and why effective employees quit.
Conclusion
Data is driving the success of recruitment functions, from recruitment agency data analytics allowing you to choose the best hiring sources to ATS helping you match resumes with AI. This converts decision-making into a data-backed process, thus streamlining the hiring process. Additionally, recruitment analysis also helps in the onboarding process by providing the metrics for diagnostic analysis. It enhances talent management, allowing recruiters to attract and retain the top talent.
