Making Data-Driven Recruitment Decisions


What is data-driven recruitment?

Hiring the wrong person for the job is a costly and time-consuming decision. Data-driven recruitment allows us to measure the effectiveness of our hiring processes and make improvements, which ultimately helps us find the best candidate. In this dynamic job market, Human Resources should always be on the lookout for ways to enhance their recruitment strategies.

Data-driven recruitment involves analyzing data throughout the recruitment process to gain insights and discover patterns, trends, issues, and opportunities which help us make more informed recruitment decisions.

HR teams that make data-driven recruitment decisions hire higher-quality candidates faster, have lower hiring costs and reduced hiring bias, make more objective hiring decisions, and offer a higher-quality candidate experience. Ultimately, data-driven recruitment leads to higher-quality candidates who are better suited to the role.

Select relevant metrics

To select relevant metrics, consider the challenges involving your recruitment process that you’re already aware of. Common examples include a slow recruiting process, high new hire turnover, low candidate quantity or quality, etc. Select relevant metrics tailored to your audience’s needs.

For example, business leaders typically seek high-level insights into recruitment and hiring metrics that align with the organization’s goals (e.g., cost per hire, growth rate, etc.). However, recruiters may prefer to focus on the nitty-gritty data which evaluates the health of their recruitment process (e.g., interview-to-hire ratio, source of hire, etc.).

Some metrics report on data points from a specific point in date (e.g., the active headcount at the end of the month was 78), and others report on a defined period (e.g., the average active headcount for February was 79). Commonly reported recruitment metrics include turnover, retention, headcount, and cost statistics, which can be broken down further.

For example, we can calculate turnover by department, supervisor, or job title, new hire vs. existing employee turnover, and we can look at the data monthly, quarterly, or annually. We can gain insights by analyzing how the data has changed over time and researching factors that could have played into these changes.

Consider which metrics are relevant to track and identify where to pull the data from. Once you have selected your metrics, it’s time to collect and compile the data to create a recruitment dashboard.

Build a recruitment dashboard

A recruitment dashboard serves as a visual representation of recruitment data which allows us to quickly identify patterns, trends, issues, opportunities, and key recruitment metrics. A recruitment dashboard reports data on applicants, hires, campaigns, budgets, and other recruitment-related metrics.

The most efficient way to create a recruitment dashboard is by utilizing your Applicant Tracking System (ATS) or candidate relationship management system (CRM) software. Many of these types of software have a built-in Data Insights or Reporting section which allows you to create your own easy-to-build, customizable recruitment dashboard(s). This streamlines the dashboard creation process.

These software solutions allow you to select the metrics to report, specify the timeframe to report on, and apply customized filters based on specific criteria. See the example pulled from Paylocity below:

Alternatively, you may collaborate with a data analyst or someone proficient in Excel/Google Sheets to manually create a dashboard, but this is a costly and time-consuming task that requires an advanced skill set. If you have a data analytics team, you may work with them to create an automated dashboard. Otherwise, there are numerous resources online that walk you through how to create your own dashboard in Excel or Google Sheets, and if you have the time, it’s a valuable skill to learn.

Below is a list of some valuable metrics for making data-driven recruitment decisions:

  • Hires, terminations, transfers, and promotions
  • Turnover rate
  • Retention rate
  • Growth rate
  • Interview-to-hire ratio
  • Offer acceptance rate
  • Source of hire
  • Cost per hire
  • Time to fill
  • Job satisfaction metrics

Metrics such as turnover can be broken down in several ways. For example, we can observe the company’s overall annual turnover rate and compare it to previous years, and we can break it down by department, supervisor, job title, etc. We can also pull the annual turnover rate for new hires versus existing employees, exempt versus non-exempt employees, or the average monthly turnover rate over time.

We can export simple metrics to create a data point and turn other data sets into graphs or charts. However, some of the more complicated metrics need data from multiple places. A dashboard should represent the data visually so that the audience has little to no questions. Look at your draft from an audience’s perspective. What questions might they ask when they view this for the first time? What can be improved to provide more clarity?

While dashboards provide valuable insights, you need to dive deeper into the data to discover underlying issues and opportunities. These insights can be gained through data analysis.

Analyze the data

To start, research the factors that play into recruitment metrics to help you understand why certain trends occur and what, if anything, to do about them. For example, if a spike in turnover is observed during a particular month, data analysis can help uncover the cause.

How many departures were voluntary resignations vs. involuntary terminations and what were the external market conditions at the time? What happened internally that could have resulted in the spike in turnover? Think about changes within the company such as mergers, personnel changes, policy changes, and the job market. What does the data and research tell us?

Consider what the data looks like now compared to what it looked like in the past to identify patterns, trends, and changes. If your dashboard shows that your team had a spike in turnover every year in October, you should ask yourself questions about why that could have happened and what, if anything, should be done about it.

Can you predict what turnover will look like in October of next year by observing previous years’ data? What does this mean for the company, and what must be done differently moving forward? Focus on big-picture numbers for improvement and evaluate past data to plan for the future. You will find most of your answers to these questions through research on recruitment data and the factors that play into the metrics.

Let the data lead you

HR teams who make data-driven recruitment decisions hire higher-quality candidates faster, reduce hiring costs, minimize biases, and improve their overall candidate experience. Data-driven recruitment isn’t just about collecting numbers and compiling data. It’s about taking actionable steps based on the insights gained from the data and research. Successful HR teams don’t just collect and analyze data, they interpret it in a way that drives strategic decision-making.

Recruitment dashboards ultimately help us visualize data to identify patterns, trends, opportunities, and problems. Regularly updating and analyzing recruitment dashboards enables HR teams to identify challenges and opportunities proactively while fostering continuous improvement in the recruitment process.

I encourage you to use data not just as a retrospective tool but as a forward-looking guide for making strategic decisions to execute organizational goals. HR professionals who embrace data-driven recruitment set themselves up for ongoing success. Read my next CUSO Magzine article on Analyzing Recruitment Data to learn more!


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