The Role of Predictive Analytics in Staffing

Companies are handling larger quantities of information than ever, especially in their recruitment and staffing processes. To keep up, businesses are continuously searching for the best candidates to ensure their company works efficiently and effectively while navigating current staffing challenges like talent shortages. As companies look towards staffing firms for quality talent, predictive analytics has proven to be an invaluable tool. 

What data are companies looking at when it comes to staffing?

When it comes to staffing, there are several key performance indicators (KPIs) that can be useful to keep in mind. These include time-to-hire, offer acceptance rate, quality of hire, selection ratio, DEI initiatives, and cost-per-hire, all of which are helpful to analyze to improve your return on investment (ROI).  

Beyond factors that companies should monitor to optimize staffing and recruiting, improved human resources technologies, such as applicant tracking systems and HR information systems, are collecting more information about candidates than ever before. From former experience to demographic data, companies are given a considerable amount of detail about each potential candidate.  

Particularly in IT staffing, companies tend to sift through this data and look for specific skills and traits to pull the ideal candidate. For instance, an SAP specialist would be vetted with SAP experience, data proficiency, and analytical skills, among others, to best assist an organization’s ability to integrate SAP.  

With so much information to keep in mind when seeking the ideal candidate, parsing through this data is where technology like predictive analytics comes into play. 

How can companies use predictive analytics to understand this data?

Predictive analytics is the use of data to predict, analyze, and provide future scenarios that can drive strategic decisions in business. Leveraging predictive analytics, companies can use past successful recruitment data to predict what candidates will be the best fit for the job. By automatically sorting through data to ensure candidates meet pre-determined sets of criteria, companies will be able to have access to the top-quality candidates.  

For instance, data visualization tools that incorporate predictive analytics like SAP Analytics Cloud can match candidate backgrounds and job roles. With the power of AL and ML, this provides automated reports of high potential in real-time. In such a competitive candidate market, this can make a huge difference by shortening the time to hire and improving the quality of hires.  

Why do predictive analytics in staffing matter?  

Predictive analytics is the future of efficiently and effectively understanding staffing and recruiting data. 

By utilizing predictive analytics, companies can beat the statistic that only 7% of businesses are using HR data efficiently. By building the list of ideal traits and experience through a data-based approach available with predictive analytics, companies can save up to 23 hours of labor each week, making staffing more time and cost efficient.  

In a world of talent shortages and competitive labor markets, Bull City Talent Group is here for your staffing needs. Contact BCTG today to find out how you can optimize predictive analytics in staffing.  

Contributions from Natasha Shrestha