Embracing a Data-Driven Approach for Talent Acquisition
The way we hire employees has evolved drastically over the last decade. Instead of relying on resumes and personal preferences to assess a candidate's qualifications, more employers are embracing data-driven hiring for better, more informed decisions.
Data-driven hiring is about using standardized data points and analytics to identify, assess, and hire the best-fit candidates in a consistent, objective manner. Employers can use data at every stage of the talent acquisition life cycle to improve their understanding of candidates — and assess their own performance. For example, employers can look at metrics such as time to hire, attrition, and candidate conversation rates to judge whether their approach is succeeding.
Done well, this approach improves efficiency, assesses everyone with relevant and consistent data, and aligns hiring practices with the company’s business objectives. Here's what it takes to be a high-performing talent acquisition team.
“High-performing talent acquisition teams know not only how to maintain relationships with their candidates,” says Jessica Smith, Founder and Principal Recruiter at Savant Recruitment, “but they're resourceful and urgent enough to move them through the process by working carefully and alongside stakeholders in the organization so that nothing falls through the cracks.”
These teams rely on the latest technology, such as a modern applicant tracking system (ATS) and artificial intelligence-powered tools, to identify the best candidates and reduce the likelihood of bias. They also look to source a diverse slate of candidates from a variety of sources, including career fairs, job boards, social media, and promising internal candidates.
One benefit to a data-driven approach to hiring is the potential cost savings. According to a report by the Society for Human Resource Management, the average cost per hire is about $4,700. That cost balloons when a hire doesn’t work out, forcing the employer to go through the process again while leaving the business understaffed in key roles.
A data-driven approach to talent acquisition helps employers quickly identify job candidates who are the most qualified, letting recruiters and hiring managers focus their efforts rather than wasting time engaging with poor-fit candidates. Data also helps employers avoid inconsistent hiring practices by focusing on objective criteria, such as relevant experience, qualifications, and skills. The goal is to eliminate inconsistent, subjective, and irrelevant criteria, such as a manager’s personal biases or whether the candidate went to a certain college.
Achieving a data-driven talent acquisition process is about having the right processes, technology, and culture. This can include training and education on how employees should use data to inform decision-making and what to do with insights generated by an ATS or other system.
“Organizations should prioritize data quality and governance, ensuring that data is accurate, reliable, and consistent,” Smith says. “This requires establishing processes for data collection, cleaning, and validation, as well as implementing data governance policies to ensure data is secure and compliant.”
Finding the best talent in a tight labor market is challenging, and your talent acquisition team needs the right technology, data, and mindset to win in this competitive landscape. Apply data and analytics to your culture and hiring processes to ensure you’re spending your time with the best candidates, assessing them fairly, and making hiring decisions that result in long-lasting employee relationships.