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3 Benefits of Predictive Hiring Analytics for CHROs

3 Benefits of Predictive Hiring Analytics for CHROs

Can predictive hiring analytics benefit your hiring process?

What are predictive hiring analytics and how can they improve your hiring process?

Predictive hiring analytics learn from existing data and uses that data to forecast individual behavior making predictive HR analytics an essential technology for your HR practices. Predictive hiring analytics are very specific and are used to predict the success of your new hires. Predictive analytics are so accurate because they use data mining to predict outcomes that may seem uncertain, especially without proper data. Applying a predictive hiring model to your HR practices will allow you to enhance your workforce planning and can properly predict employee performance.

Benefits of Predictive Analytics Techniques

Predictive analytics can not only help you improve your hiring decisions but also your hiring process. With predictive hiring analytics, you can make accurate decisions based on large amounts of data. Implementing a predictive hiring model into your hiring process will allow you to verify that any new hire you decide to ask to join your company will be successful. Also, with a predictive hiring model, you will be able to make your hiring process more effective by understanding areas that attract the wrong candidates and changing those areas.

Quality Hires

One major way predictive HR analytics can improve your hiring process is by improving the quality of your hires. When you develop your predictive hiring model linking the hiring process to production performance, attrition data, engagement information, and all other data from the employee lifecycle, your model will be able to properly predict the potential future job performance of any candidate. It is important to remember, though, that your predictive hiring model needs to be constantly updated using all new data you acquire and must be continually adjusted. It is essential that your predictive hiring model has measurable processes and objective data that is reliable. To ensure that your predictive hiring model is effective, use pre-employment assessment results, interview results, engagement survey data, recruiting sources, turnover data, and performance results.

More Effective Job Sourcing

When you incorporate sources into your predictive analytics model, you can improve the way you find potential candidates. You can optimize your recruitment marketing and eliminate poor sources by tracing optimal hires back to their hiring source and using that source for future hires. With predictive hiring analytics, you can significantly improve the ROI of your recruitment marketing program. Hiring analytics even make it possible for you to negotiate better pricing terms with hiring sources as they give you significant leverage because you now know the quality of hires they produce and their cost of hire index. With predictive hiring analytics, you will be able to get job sources to lower their pricing or risk being cut from your budget altogether.

Hire Faster

Another way predictive hiring analytics can improve your hiring process is by allowing you to better understand which types of candidates are the best fit for your company. By knowing which types of candidates are best suited to work for your company, you will be able to deploy better tools that serve as leading indicators of potential job performance. Predictive hiring analytics can make your hiring process much faster by allowing you to move quickly once you notice a candidate that fits your job model. A predictive hiring model can make your hiring process much more effective because it will allow you to only focus on candidates that are right for your business.

Emily Pribanic
Emily Pribanic
Emily is a graduate of the University of North Texas. She has her B.A. in Advertising with a concentration in Copywriting. Emily has been writing since she was young and has a creative imagination. She lives in Dallas, Texas with her family and two cats.

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