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4 Reasons Why Data-Driven Recruitment is Key in The Future of Hiring
4 Reasons Why Data-Driven Recruitment is Key in The Future of Hiring
We’ve come a long way since the days after World War II – where the modern-day recruitment industry was born. Over this time, we’ve seen the invention of the cover letter in 1956, the start of online background checks in 1985 and electronic resumes in 2002. In the ever-evolving industry of recruiting, it begs the question, “what’s next?”
With technology at our fingertips and impending evolutions such as the Metaverse, Web 3.0 and the Internet of Things (IoT), we have more data at our disposal than ever before. Data, in part, can be useful for organizations to gain real-time access to how their customers and stakeholders are interacting with their business. However, once companies have this data, the challenge becomes what to do with it.
“Generally speaking, better data leads to better decisions,” Georgianna Rhoda, Director of Recruiter at Hunter Recruiting describes. “This remains true for the recruitment industry and employers alike.” Rhoda explains, “Through compiled data, we can take a numbers-first look at all aspects of our application, hiring and onboarding processes to deliver the best results to our candidates and clients.” Data-driven recruitment goes beyond process improvement, and challenges employers to utilize new technologies to create a more inclusive and enhanced applicant experience.
Read on for the reasons data should be driving your recruitment process.
1. Streamline Application Process
Data can be overwhelming. A good place to start is at the top of the funnel – where your candidates begin the application process. Consider looking at your conversion rate, or the amount of people who complete applications divided by the total number of people viewing the page. You can then use this data to benchmark yourself against your industry competitors to see how your career pages perform. You can also look at time spent on your site and identify where people are falling off of the application process. This information can be valuable in determining how candidates are using your platform, and if there are any issues that may hinder them from applying to the role. Over time, this data can be utilized to create an overall better candidate experience starting at the very first interaction they have with your company.
2. Deter Unconscious Bias
According to a study by BrightTalk, 79% of HR professionals agree that unconscious bias exists in both recruitment and succession planning decisions. Data, when analyzed properly, can provide a new perspective on unconscious bias in your hiring process. Looking at demographic information of the candidates you are engaging, and how the numbers change at each step, can help you identify unknown errors in your recruitment practices. Additionally, new technology tools can use data to help deter unconscious bias. By leveraging candidate data with technologies such as artificial intelligence, human unconscious biases can be minimized, as candidates are ranked by a computer solely on their quantifiable skills and experiences. Historical data can also be used with tools that assess the wording of your interview questions and job descriptions to make sure they appeal to people of all genders, races and backgrounds.
3. Forecast Hiring Trends
Most hiring managers would love to predict the future. By utilizing historical data, companies can identify patterns and forecast trends within their organization. For example, a company could forecast how many people they’ll need to replace this year and account for any year-over-year season trends. This could help the organization set budgets, plan for necessary resources and build internal HR teams that are capable of handling turnover. Companies could also use historical data to predict total time to hire to give managers and departments a realistic timeline for getting a new employee up to speed.
4. Reduce Hiring Costs
Hiring can be very costly for organizations. According to a report by SHRM, it costs employers an average of $4,129 and 42 days to fill an open position. While this number varies based on the job role, experience required and salary range, you can imagine how hiring multiple employees a month could add up over the course of a year. A great way to cut costs is to utilize data to identify what is (and isn’t) working. An employer might look at what job boards lead to the greatest number of accepted employment offers and allocate their spending to those platforms. Additionally, a company may look at data and fall-off trends and identify that their interview process is too long, causing candidates to accept other offers during that time.
These data points can lead to conversations to better improve your organization’s recruitment strategies and ultimately provide you a new lens to examine your hiring processes through.
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