Thanks to the proliferation of HR data across HRIS systems such as applicant tracking systems, companies have access to more recruiting data than ever before. This creates both challenges and opportunities for recruiting teams to use these newfound data sources to grow and nurture their talent pipeline. This is where recruitment analytics can help.
Recruitment analytics allows companies to connect data from disparate sources and link recruiting strategies to business objectives. Before, most recruiting teams were flying blind trying to put butts in seats as quickly and cheaply as possible, disregarding the impact of recruitment activities on business results. More advanced teams can incorporate some analytics into their decision-making process, but it often stops at tracking and benchmarking key recruiting metrics for recruiting efficiency, not talent effectiveness such as quality of hire.
We put together this guide to help companies adopt a more data-driven recruitment management process. It will explain in-depth what recruitment analytics is about, the potential impact, as well as the kind of recruiting questions it can help answer. We’ll also provide real-life examples as well as best practice tips to help you grab the concepts quicker.
Table of Contents
What Is Recruitment Analytics?
Recruitment analytics refers to the practice of data-driven decision-making by merging recruiting with other HR and non-HR data sources to identify drivers of workforce performance. Recruitment analytics is a subcategory of workforce analytics and standard modern practice in advanced recruiting and hiring management.
Recruitment analytics can benefit all the stakeholders in the organization. For executives, this practice gives them an unprecedented level of insight into hiring performance and the ability to align recruitment strategies with overall business goals. For recruiting teams, this practice gives them much-needed tools to monitor the health of their talent pipeline, identify potential recruitment risks, and proactively avoid or alleviate them. For line managers, they can get quick access to insights that they can easily act upon and dashboards to track their progress and measure success.
What Kinds of Recruiting Questions Can Analytics Help Answer?
These are the 5 burning recruiting questions that analytics can help answer.
1. How efficient and effective is our recruiting process?
A well-designed recruiting process can help bring in more qualified applicants and speed up the recruiting process while reducing the average cost per hire. This is why companies need to closely track the efficiency and effectiveness of their recruiting process. A good report or dashboard will give management a comprehensive snapshot of the current talent pipeline as well as its effectiveness.
Below is an example dashboard that captures everything one needs to know about recruiting efficiency and effectiveness.
2. What recruiting source yields the highest performers? What recruiting source yields the best cultural fits?
Several research and case studies have shown that employee referral and temp-to-hire are often the two best recruiting sources. However, is it true for your organization? What is better than having the data to prove this is also the case for your organization? That’s why recruiting teams need to have the ability to track and compare the performance of various hiring sources both at the company as well as the business line level.
Below is an example of how you can quickly compare the performance of various hiring sources.
3. What is our quality of new hires? What recruiting source yields the best quality of new hires?
Getting an empty position filled promptly is important. But it’s equally important to fill this position with a top talent that fits within the budget. Get this balance wrong and you could potentially see a sharp increase in the total cost of workforce and turnover rate in subsequent quarters.
Below is an example of our Quality of Hire index historical trend and forecast.
4. Are we losing the right people (low performers) or the wrong people (high performers or critical roles/skills)?
Recruiting and turnover are like two sides of the same coin. Hiring talent with the right cultural and skill fit will significantly increase the chance that a new hire will stay after the first 90 days. Another equally important aspect of turnover is to assess if the company is losing the right people or the wrong people. The right people in this case are unengaged employees with below-average performance scores. The wrong people are your superstars and high performers or highly engaged workers who are carrying their team.
Below are our recommended charts for tracking high performer and highly engaged turnover rates.
5. Is internal mobility a source of value or turnover and cost? What percentage of the workforce moves internally each year?
Compared to external hires, internal hires on average cost less, are more likely to stay, and also often stay longer. Being able to measure the cost-saving opportunities for internal hires can help recruiting teams cement necessary buy-in support for any future internal mobility promotion campaign.
Below is an example of how we help companies measure the impact of internal mobility on turnover.
Four Levels of Recruitment Analytics
The journey to recruiting analytics excellence has many stages. Each stage represents the companies’ ability to effectively translate data into insights and actions. Gartner broke down a typical analytics maturity journey into the four main stages: (1) Descriptive Analytics, (2) Diagnostic Analytics, (3) Predictive Analytics, and (4) Prescriptive Analytics.
Descriptive Analytics focuses on examining historical data to assess what has happened in the recruiting process and highlight any potential worrying trends. For example, the data shows that the number of applicants for cybersecurity roles has been falling. Example descriptive analyses:
Diagnostic Analytics concerns more about what caused these worrying recruiting trends to take place. Following up on the example in descriptive analytics, the question this company should try to answer is: “What are some potential causes for the falling number of applicants for cybersecurity roles?”. Example diagnostic analyses:
Root cause analysis
Predictive Analytics highlights the potential impacts and results that these worrying trends and risks are causing for the organization. The predictive question this company needs to answer is: “How will the falling number of applicants for cybersecurity roles impact the company’s continuity of operations?”. Example predictive analyses:
Multivariate statistical modeling
Forecast predictive indicators (identified via root cause analysis)
Prescriptive Analytics helps companies find the most optimal solution for known recruiting risks and overall business objectives. Using the same cybersecurity example, companies should use prescriptive analytics to prescribe interventions that can help increase the number of applicants for cybersecurity roles. Example prescriptive analyses:
What-if analytics to test different recruiting scenarios via changes in recruiting metrics and strategies
Workforce planning, scenario modeling
Integrating Recruiting Data with Other Data Sources for Maximum Impact
Being able to track advanced recruiting metrics like Time to Fill or Cost per Hire is good. But it’s even more valuable for management to see how improvements in these metrics can translate into tangible business results such as cost savings, ROI, or productivity improvements. This is cited as one of the top reasons why many companies fail at HR analytics.
The key to unlocking these types of analyses is to integrate recruiting data with other HR and non-HR data sources. For example, examining just recruiting data allows users to track metrics like hiring rate, time to fill, and the number of applicants. Only when you combine recruiting with turnover, performance, and engagement data, you can measure the turnover rate of new hires or identify recruiting sources that yield the most high performers and highly engaged employees. We also published a detailed article and a video on this topic.
The data recruitment analytics uses can come from both internal and external sources:
Human Resource Information System (HRIS)
Applicant Tracking System (ATS)
Performance Management System (PMS)
Enterprise Resource Planning (ERP)
Learning Management System (LMS)
Labor Supply Intelligence
Why Automating Recruitment Analytics?
For analytics teams who still manually process data, it is common to spend up to 2 weeks every month on data aggregation, cleansing, and integration. This team would comb through all the transactions to ensure that there are no anomalies in the data that can skew the results. After this was done, the team then starts working on generating reports and performing ad hoc analyses per stakeholder requests. The result is a process that is slow, expensive, and error-prone. Very little time was spent on explaining the insights or translating insights into best practices that are easy to act upon for management. This decreases the chance that a finding is implemented, and an ROI is realized.
Report and analytics automation brings huge gains for team efficiency and ROI by automating much of the manual process, allowing recruiting teams to quickly implement and ramp up their value-add analytics capability. What was previously done in years, can now be accomplished in just a few months. Advanced teams can also benefit from a solution like this. It gives them more time and buy-in-support to perform more complex analyses and understand the drivers of their workforce performance or turnover.
Top Recruitment Metrics
Chances are your recruiting managers are swarmed with monthly reports. This makes it hard for them to find these reports useful and easy to act upon. That’s why it’s important for them to have a set of KPIs or top metrics on the recruiting process and efficiency. These KPIs allow executives to get an overview of how their recruiting team and process are performing at any given time.
The top 7 recruitment metrics we recommend all companies to track are:
Quality of Hire
Internal vs External Hire Ratio
Make Recruitment Analytics Part of Your Talent Management Process
The performance of your workforce is heavily dependent on the quality of new hires. That’s why it’s critical for recruiting executives to create a robust data-driven practice to help companies hire qualified talent faster, cheaper, and more efficiently. The traditional approach to HR analytics requires significant investments in tools and people. An out-of-the-box solution like SOLVE™ can help companies significantly cut down the time spent monthly on reporting, allowing recruiting teams to focus more on implementing prescribed interventions.
Explore SOLVE™ Workforce Intelligence Solution today or see it in action.