We know it’s not easy to wade through hiring data for the first time. What KPIs should you focus on? How does A/B testing work? Are you even getting accurate data?
1. Narrow Your Focus (At First)
When delving into data-driven recruitment, it’s essential to start with a clear focus.
Determine the key performance indicators (KPIs) that matter most to your organization. Are you aiming to reduce time-to-hire, improve candidate quality, or increase diversity in your workforce? These KPIs will be your North Star, guiding your analytics efforts.
As you become more familiar with hiring analytics, you can add additional KPIs and track more variables at once.
Examples of Metrics to Track
- Time-to-fill. This metric measures the average time it takes to fill a healthcare job vacancy from the initial posting to the candidate’s acceptance of the offer. A shorter time-to-fill indicates efficiency in the recruitment process.
- Time-to-interview. This is a metric that measures the average duration between the initial posting of a job vacancy in healthcare and the scheduling of an interview with a candidate. This is essential for assessing the speed and efficiency of the early stages of the recruitment process.
- Cost-per-hire. Determine the cost associated with each hire, considering expenses like advertising, recruiter salaries, and other recruitment-related costs. Reducing cost per hire while maintaining quality is a common goal.
- Candidate sourcing metrics. Monitor the sources of candidate applications, such as job boards, social media, referrals, and direct applications. Identify which sources yield the best candidates in terms of qualifications and fit for the organization.
- Diversity and inclusion metrics. Track the diversity of candidates in the recruitment pipeline and monitor the organization’s success in hiring a diverse workforce, including gender, ethnicity, and background.
- Offer acceptance rate. Calculate the percentage of candidates who accept job offers after receiving them. A low acceptance rate may signal a need for adjustments in the offer or recruitment process.
Key Takeaway: Identify the key performance indicators (KPIs) that align with your hiring objectives. These KPIs will serve as benchmarks for measuring the success of your recruitment efforts.
2. Standardize Your Process
In data-driven recruitment, consistency is key. To make your data analysis meaningful, standardize how you track data, where data comes from, and the processes your team follows.
For example, make sure your team updates statuses for candidates in your hiring software. If a candidate goes from being a prospective to being offered an interview, that change should be tracked.
Also, standardize where notes are kept. Things can get confusing quickly if one employee keeps their notes on a personal device, instead of on a communal note-tracking system.
Key Takeaway: Ensure your data reporting is consistent and reliable at every stage. One common saying in data-driven hiring is “garbage in, garbage out,” meaning that the findings you get from your data is only as good as the data you put in. In other words, if you don’t update your applicant statuses or if you have an uneven, unstandardized process, you won’t get accurate results.
3. Make Use of A/B Testing
A/B testing, also known as split testing, is a method of comparing two versions of a webpage, email, app, or any digital asset to determine which one performs better.
For example, you might be curious about how salary transparency affects job posts. You could make two posts—one with the salary, and one without. By controlling all other variables, you can see if candidates are more drawn to the post with the salary listed. This kind of experimentation can help you make important decisions about how you want to present your jobs and your company.
Other examples of A/B testing include creating two versions of a job post to see what tone candidates respond to, testing whether it makes a difference to start with benefits or your company mission, and comparing responses to shorter and longer versions of the same job ad.
Key Takeaway: A/B testing is a strategy for comparing two versions of the same message. Implement A/B testing in your hiring process to understand how your messaging and company branding is received.
4. Focus on the Big Picture When Reporting to a Larger Team
When reporting to your team, prioritize sharing high-level metrics and actionable insights. Your entire team doesn’t need to dive into the nitty-gritty of your recruitment analytics.
Use clear visuals and concise explanations to ensure everyone grasps the essential takeaways. You don’t want to waste your team’s time, or risk them glazing over and filtering out what you’re saying.
It’s also much easier to support your data-driven hiring initiative when you have buy-in from your team. If your presentation ends up feeling confusing, your team is less likely to support your efforts. This lack of support can trickle down into laxness when it comes to updating statuses and maintaining clean data.
Key Takeaway: When presenting data to your team, focus on highlighting key findings rather than overwhelming them with every detail.
5. Reach Out to Your Software Partners
Even with an applicant tracking system (ATS) that gives you great reports, deciphering complex data can be daunting. Your software partners and customer success team can offer invaluable guidance to help you leverage your tools effectively.
Don’t hesitate to seek your customer success team’s expertise and ask for analytics-based training. There might even be recruitment metrics that you aren’t aware you have access to.
Key Takeaway: Collaborate with your software partners and customer success team to unlock hidden data and insights.
Data-Driven Hiring With Apploi
Embracing data-driven recruitment can revolutionize your hiring processes. By narrowing your focus, standardizing your process, and more, you’ll be on your way to more effective and efficient hiring.
Ready to take the next step? Schedule a demo today.