The foundation of HR analytics
Hiring analytics is a part of talent analytics which includes monitoring, measuring, collecting, and analyzing data about candidates and employees to make better hiring decisions. Hiring analytics can help you make better, data-driven choices when it comes to finding, selecting, and hiring.
Recruitment analytics is a way to implement data-driven hiring in your organization, making your hiring process more efficient and effective. By using analytics to make strategic hiring decisions, you can identify the best candidates, analyze what your best employees have in common, and repeat the process as needed.
Recruitment analytics tools collect data from every aspect of your business and turn it into insight by uncovering patterns in procurement and recruiting processes. Part of using recruiting analytics to inform the recruiting process involves understanding what information to collect and how to apply it.
Recruitment analytics collection and analysis
Predictive analytics enable organizations and the recruiters who hire them to make informed, data-driven hiring decisions going forward. From there, both automated algorithms and recruiters can use predictive models powered by big data analytics to make more informed decisions about what to do next. By basing hiring decisions on data and algorithm-driven predictions, recruiters can remove their own biases, which produces more consistent results. Without a solid analytics solution for the recruiting function, most recruiters end up taking a shot in the dark when making hiring decisions.
Measuring the effectiveness of all these moving parts of the hiring process becomes difficult with conventional metrics and tools. Data analytics is one thing, but how you respond to issues that come up during hiring makes the process effective.
Analyzing recruitment data can provide valuable insights into which talent sources perform best, the performance of internal versus external recruiting, and any costs incurred. Recruiting with analytics is the best way to make sure you are hiring enough or the right candidates at the right time. Tracking and analyzing recruiting data can help you select recruiting activities that will bring the most value to your organization and improve candidate performance. For example, examining hiring data only allows users to track metrics such as hiring rates, fill times, and the number of applicants.
Recruiting data—about candidates, recruiting activities, and all related processes—can not only refine existing recruiting practices, but also lead to new ways to attract candidates and fill vacancies. Given the time, effort, and costs involved in recruiting, it makes sense to consider the many ways data can improve both the quantity and quality of recruitment. If you’re working on implementing hiring analytics for data-driven hiring decisions, you’re already on the right track, but not just any metric will do. By carefully choosing analytics tools, metrics, and trusted partners, you can improve your hiring practices and chart a clear path towards your organization’s hiring goals.
How you can build your recruitment analytics approach
Many modern recruiters are using analytics to gain actionable insights that enable them to make data-driven decisions regarding sourcing and selection. Most forward-thinking companies have started investing in the latest analytics solutions through business intelligence instead of relying on traditional recruiting methods to source highly talented candidates.
In today’s rapidly changing talent acquisition landscape, companies around the world are using hiring analytics to effectively implement data science and achieve remarkable hiring results. In fact, recruiters in today’s era can easily make analytics an integral aspect of their hiring strategy by simply choosing a feature rich recruiting software. Recent technological innovations in the recruiting industry have made it possible for HR professionals to use data to gain access to all the information they need.
By using a company’s recruitment analytics tool, you can create a centralized station of recruitment information, giving all stakeholders instant access to business dashboards. If you’re looking for more advanced features, there are dedicated data analytics tools available for recruiting that integrate with your HR systems. There is also a pretty useful hiring analytics module so you can generate reports on any stage of the hiring process.
Common data sources for recruitment analytics include applicant tracking systems (ATS), customer relationship management (CRM) systems, human resource information system (HRIS) data, satisfaction data, brand data, and data from advertising platforms used to promote jobs and brands.
Recruitment analytics solutions typically collect recruiting data from all digital touch points, which include your job page, recruiting CRM, your applicant tracking system (ATS), mobile apps, video interview software, social networks, and more. The data you can measure using predictive analytics in recruiting is as extensive as your company and can serve as a unique source of input and information.
However, the real advantage of predictive analytics lies in its ability to provide objectivity based on real data rather than subjective human judgments. Predictive analytics uses new and historical hiring data to predict the behavior, trends, and outcomes of specific processes. Prescriptive analysis helps companies find the best solution for known recruiting risks and overall business objectives.
DreamTeam is one of these recruiting analytics platforms that allows companies complete transparency and visibility into hiring processes, and creates a shared language between recruiters and company leadership – KPIs. It integrates with your ATS once, and continuously updates live dashboards with visualizations of insights in the recruitment process. You can register for a demo of DreamTeam here.
The bottom line
Other examples of analysis are ideal candidate profile prediction, hire time prediction, and recruiting funnel optimization. The hiring process itself is a “treasury of data” that can help predict whether a candidate will be a high-performing, culturally appropriate candidate, writes Ian Cook, HR Solutions Manager at Visier Analytics.
Matching ratios and other analytical tools used in recruitment should be based on educated guesses from the outset. The key to getting the most out of hiring analytics is to understand which metrics matter most and what your team needs to do to increase hiring performance.