Recruiting managers are constantly faced with difficult decisions when it comes to finding and hiring the right talent. The path to reaching these goals can be difficult. However, recruiting managers can benefit tremendously from data-driven recruiting that many of today’s top companies in various industries use.
But what exactly does data-driven recruiting mean? What does it entail? Why should you make an effort to use this strategy in your business? Most importantly, how can you effectively use data in making smarter, more informed recruiting decisions?
What Is Data-Driven Recruiting?
Data-driven recruiting is the use of facts and statistics to make hiring decisions, from creating recruitment plans to selecting candidates. Data is usually gathered and processed through IT systems, such as Applicant Tracking Systems (ATS), Customer Relationship Management (CRM) systems, social media platforms, surveys, analytics, and other tools.
Technology’s growth has provided recruiting professionals with access to a wealth of data and information that can be useful for identifying top talent, even with few resources. To stay competitive, companies turn to data-driven recruitment to find and hire talented candidates and build talent pools in an expedited manner.
How Data Helps Recruiting Managers Make Smart Hiring Decisions
Data science gives recruiting managers the ability to see patterns that the human eye can’t easily process. Identifying these patterns can help you:
- Get Better Quality of Hire
This is the first and foremost benefit of data-driven recruiting. Onboarding candidates who add value to your company gives you a distinct market advantage.
- Get More Diverse Hires
Diversity tracking can be challenging without analytics. However, tech tools can continuously monitor your hiring funnel for essential demographic ratios. These ratios include gender, ethnicity, and veteran status.
- Improve Your Efficiency
Data analytics can also help track specific touchpoints in the recruitment process. For instance, you can see the number of email exchanges between your company and candidates within a given timeframe. This gives you a better sense of where to cut the unnecessary steps in the process.
- Allocate Hiring Funds Effectively
Tracking the source of your best hires will help you determine where to invest your budget wisely. You can also effectively choose to allocate funding to the proper recruiting channels through data and statistics.
- Identify Pain Points
Analytics also help you know which parts of your processes work and which ones don’t. It can help point out questions in your application form that can be removed or tweaked and update your career page to get more conversions.
- Predict Hiring Outcomes
You can’t manage what you can’t measure. Data is all about measuring movements between each hiring stage. The data from those measurements will help you forecast and benchmark hiring outcomes realistically.
Setbacks of Using Data for Recruiting Decisions
Data can be a valuable tool in recruiting and hiring, but it’s not infallible. Here’s an overview of some of the drawbacks of having your hiring process be too data-driven. Understanding these can help you be more mindful come the time to make decisions.
- Data Can’t Determine Subjective Characteristics
You may think that subjectivity is outside your purview, but it’s not. While data science can determine how close a resume matches a job role, it may be unable to determine subjective characteristics, such as integrity, grit, and honesty.
- Data Can’t Determine Hits and Misses
Although data can help you determine who’s most likely to succeed in your organization, there will always be candidates who don’t make the cut but could have made great hires. So, if you’re relying solely on data, you may overlook potential employees and lose out on opportunities for diversity, innovation, and creativity in your workforce.
- Mining Online Information Can Raise Privacy Concerns
The rise in social media and the popularity of sites like LinkedIn have made it easier than ever for job seekers to showcase their skills and experiences to potential employers. Unfortunately, using such information for analytics can raise privacy concerns for most candidates.
- Data Can Reflect and Repeat Past Biases
Hiring managers and recruiters often rely on data to predict future job performance. However, when they fall back on these metrics, they often perpetuate existing biases within their company. For instance, if men employees had higher scores in the past than women, data might suggest hiring more men over women.
These are all possible setbacks. However, if you ensure your AI programs and data computing tools are audited and corrections are made if unintended biases are observed, they can be avoided.
Data-Driven Recruiting at Play
According to the LinkedIn Talent Solutions Survey, 77% of recruiting managers say that having a solid understanding of the market and talent pool they are recruiting from makes them more efficient in their hiring efforts. These recruiting managers also use data-driven insights to enhance the hiring process, improve the approach, adjust the tone of voice, and customize offers.
In today’s era of hybrid work, it’s essential to consider what your talent pool should look like in the context of the ideal workplace you intend to cultivate. Of course, this concept isn’t new, but applying it to your processes has been made easier with all the technological advancements available today.
6 Recruiting Metrics That Matter
There is an endless amount of information you can extract from data analytics for data-driven recruiting. To help you know where to look to make better hiring decisions, here are six metrics that best predict the quality of hire, individual recruiter productivity, and overall recruiting performance.
- Number of Candidate Interviews per Hire
This metric is the leading indicator of candidate quality and can pinpoint problems in your hiring process. If the number of candidates that go through interviews varies widely or is too high, you might want to take a moment and review your hiring process.
Ideally, hiring managers should have a good handle on the talent they’re looking for. If your preliminary process doesn’t eliminate mismatched candidates, then it’s one of two things. Either you have to get your hiring manager on the same page in terms of candidate expectations or tweak your current process.
- Conversion Rate of Passive Candidates Recruiting Efforts
You want to get the best person for a role, not the best person who applies. This means that getting a passive candidate interested in what you’re offering is essential to the success of your recruitment efforts. A good hiring manager should be able to convert passive leads into serious prospects.
- Conversion Rate of Email Campaigns
Take a look at how many people respond to your email campaigns. Recruitment channels might have automated features that enable you to reach out to the right candidates. If your email conversion rate is low, then it’s time to come up with better and more engaging email content.
- Number of Referrals per Call
If a promising candidate is unavailable for your open role, it’s a good idea to get high-quality referrals from that individual. These people are the ideal group to keep in your pipeline.
- Call-Back Rate of Passive Candidates
It’s essential to see how many passive candidates call you back once you’ve reached out to them. If the call-back rate is too low, you might want to review your company’s passive candidate recruiting efforts.
- Effectivity of Job Posts
Measure how effective your efforts are on recruitment channels by knowing how many people your posts reach. Out of that number, how many applied? If the ratio is low, you might want to improve your job postings or adjust your target audience.
Implement Data-Driven Recruiting into Your Process
Now, you’re ready to start using data science in your recruitment process! The last challenge will be defining the following to measure and achieve success:
- Tie Metrics Back to Your Recruiting Goals and Business Objectives
Whether it’s helping you fill open positions more quickly or reducing recruitment costs, it’s important to keep your goals in mind all throughout the data-driven recruiting journey. This can give a greater sense of urgency and priority to each measure.
- Set SMART Targets
SMART refers to specific, measurable, assignable, realistic, and time-bound targets. Defining these parameters properly will ensure that your objectives are attainable within a certain time frame.
- Create an Executive Dashboard
An executive dashboard will allow you to monitor and adjust your processes in real-time and make data-driven decisions. It’ll also let you focus more on building relationships with your candidates and less time on reporting.
GET DATA-DRIVEN RESULTS WITH ALLIED INSIGHT
If you’re thinking of implementing data-driven recruiting practices at your staffing agency and need additional help, contact us! We’ll be more than happy to jump on a call and see what we can do for you.
Allied Insight is a fractional CMO and growth marketing company specializing in leveraging the best practices of recruitment marketing, inbound marketing, SEO, lead generation, account-based marketing, and sales enablement.
We understand the importance of keeping up to speed with technological advances to improve your business process while scaling your business. If you want to know more, visit us at alliedinsight.com.
