How to Avoid These Pitfalls in Data-Driven Recruiting

Data, which took time to gather and analyze, was less critical in traditional recruiting than luck and intuition. Only an educated guess could be made about how well-received their hiring practices were. However, with the abundance of software and analytics tools today, anyone can develop a data-driven hiring process. Data-driven recruiting is one of the fastest-growing trends in the human resources industry. However, it needs to be more understood, and misunderstandings can lead to costly mistakes. This article explores some pitfalls of data-driven recruitment and explains how to overcome them.

Time to Hire

Data-driven recruitment can help companies achieve their hiring goals faster. This can be achieved by understanding where your hiring process is slowing down and then making improvements to speed up the process. A tech-based solution allows you to be confident and implement the program quickly, especially during an employment background check.

Recruiting data can include applicant volume, time-to-fill, quality-based metrics, and other measures. Using data-driven insights to streamline your application process can lead to more qualified applicants. It can also give you a more accurate view of your recruitment strategies and improve your communication with managers and executives.

Whether your goal is to reduce your time-to-fill or your cost-per-hire, it’s essential to identify the key performance indicators (KPIs) that can be used to gauge the quality of your recruitment efforts. You’ll need to clearly define your goal and then identify the best recruiting metrics for your situation.

Time-to-fill, or the average number of days from posting a job to accepting an offer, is a good starting point. However, it could be a better measure of your hiring process. For instance, a low applicant volume could affect your time-to-fill, and a high offer acceptance rate could result from inefficiencies in your recruitment strategy.

While time-to-fill measures how long it takes to hire a replacement employee, it doesn’t account for attrition. Attrition is the most costly HR factor. Rather than measure time-to-fill, consider identifying key metrics such as attrition rate, cost-per-hire, and diversity selection ratio.

Time to Engage

Data-driven hiring is a method that provides a comprehensive view of the entire recruitment process. It enables an employer to make objective decisions about candidate selection and placement. In addition, data-driven recruitment allows the identification of potential candidates that may have yet to be discovered by traditional methods.

Compared to other methods, data-driven recruiting can save time and money. It also helps companies to eliminate bad hires. This means that you can focus on acquiring quality talent.

The cost of a bad hire can be substantial. Studies show that a company loses USD 14,900 for every bad hire. That’s not including the salary paid to an unproductive employee.

The cost of attrition is also high. Studies indicate that 75% of the total need for new employees is related to those leaving. However, only 50% of companies measure the effectiveness of their recruiting efforts. A lack of metrics can lead to disaster.

Hiring the right people can improve your business in the short and long run. But it would help if you learned how to utilize the available data to achieve this goal.

While recruiters have traditionally relied on gut feelings and intuition, modern data-driven approaches concentrate on accumulating, centralizing, and taking action on analytics.

For example, recruitment metrics can help you determine which recruiting channels are the best for your business. They also provide you with the ability to track the performance of your hires.

Misperceptions About Data-Driven Recruiting

Data-driven recruiting can be an effective way to improve your hiring process. It also can help you find better-quality candidates and lower your costs. However, some everyday things could be improved about data-driven recruiting.

Before data-driven recruitment, recruiters relied on intuition and their own experience to identify suitable candidates. Moreover, collecting, analyzing, and using all the available data was time-consuming and expensive.

With a data-driven approach, the process is more objective. You can eliminate biases and make more accurate hiring decisions. In addition, data-driven models can improve your company’s value and hiring process.

When evaluating the effectiveness of your recruitment, consider tracking sources of hire, applicant conversion rates, and candidate engagement metrics. Reviewing these metrics can lead you to identify and fix weak spots. These metrics can also reveal issues with your application form, including incorrect information or a lack of diversity.

Another way to improve your hiring process is to forecast your hiring needs. This will allow you to set expectations for the time required to hire a new employee. Especially for critical positions, it is essential to have a reliable hiring timeline.

If you don’t track your applications, you may overlook applicants who don’t qualify. But if you follow emails, you can speed up the time it takes to hire.