Common problems with recruiting metrics & how to avoid them
Spencer Bratman
Growth @ Dover
November 27, 2024
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3 min
When everything is labeled as important, nothing is. Talent leaders may rely on a laundry list of metrics to assess performance, believing that more metrics equals a clearer picture. However, this can create confusion instead of clarity.
Overloading on metrics can lead to several issues, such as:
Lack of prioritization: When tracking too many KPIs, it can be difficult for teams to determine which ones actually matter.
Diluted focus: Attention is spread thin across multiple KPIs instead of honing in.
Solution: Focus on one or two metrics that directly align with your hiring goals. For example, track time-to-hire and candidate drop-off rates to measure the speed of your pipeline and where you’re losing good candidates along the way. At the same time, remember not to be obsessed with these metrics. They might be semi-useful for improving hiring, but they’re not the end-all-be-all.
Data input is often inconsistent or incomplete. ATS platforms need clean, structured data if you want to gain meaningful insights. Most teams fall victim to the “garbage in, garbage out” trap of data entry, leading to metrics that don’t help much.
Some common data quality issues to watch for include:
Incomplete records: Candidate profiles don’t have critical information.
Inconsistent data entry: The team isn’t trained on what fields need to be filled out, and different formats affect analytics, making it harder to track trends.
Duplicate entries: Teams forget to clean up duplicates and merge candidate profiles.
Solution: Establish a process for entering clean, consistent data into your ATS. Train your team on best practices and do regular audits to ensure the processes are being followed.
This is a problem common to early-stage startups. Unlike large organizations hiring hundreds of people, startups only hire one or two roles at a time. At most, a startup might hire a handful of people annually. This makes it difficult to get meaningful trends and insights from your metrics.
Some common problems with sparse data include:
Limited sample size: Not enough data for trends.
Unique roles: Each hire can be so different that it feels irrelevant to compare them.
Focus on outcomes: Most startups simply want results, asking, “Did we make the hire?” All other metrics are secondary.
Solution: Shift focus from quantitative metrics to qualitative. For example, look at feedback from candidates and hiring managers about the recruitment process. See how well new hires perform and how long they stay with the company. Improving your recruitment pipeline and new hire retention are going to be much more important to startups in the early stages than any specific recruiting metric.
4. Data Is Hard To Compare Across Companies
Recruiting doesn’t happen in a vacuum. Each startup’s hiring process can be affected by its industry, size, funding stage, number of roles needed to fill and numerous other variables. This makes it almost impossible to compare recruitment metrics to other startups.
Trying to compare your metrics leads to challenges like:
Different benchmarks: What’s a good time to hire a software engineer? What about an executive assistant? Now, what’s the difference between time-to-hire for an engineer at a marketing company vs a consumer goods company? There are too many variables to count.
Different priorities: Some startups want speed, while others focus on culture fit. It doesn’t help to compare yourself when you don’t know what the priorities are for the other hiring team.
Solution: Stop comparing yourself to others. Instead, you can set goals and develop benchmarks over time as you grow. Compare yourself to your historical performance rather than nebulous external standards.
5. No One Wants To Be Held To Metrics
Metrics can be useful, but they can also create pressure and fear for hiring teams. Recruiters and hiring teams don’t want to be held to metrics that might be used against them.
Some reasons holding people to metrics fails:
Unrealistic expectations: Metrics that don’t account for the complexity of recruiting can feel extremely unfair, leading to resentment from the team members you already have.
Recruiting is hard: Hiring isn’t an exact science, and metrics rarely show the nuances of the process. They’re not necessarily representative of how someone is actually doing.
Solution: You can use metrics as tools for improvement rather than ways people can fail. You can look at metrics as opportunities. For instance, if time-to-hire is slow, you can look at ways to streamline processes and automate some tedious tasks for the hiring team.
How To Avoid These Recruitment Metric Pitfalls
If you want to make recruiting metrics work, you have to take a strategic approach. Here’s a summary of the steps we went over to avoid common pitfalls and use metrics in a way that’s actually helpful:
Prioritize key metrics: Identify one or two KPIs that align with your recruitment goals. But, also keep in mind that metrics don’t paint a full picture, so no need to be obsessed with them either.
Clean your data: Put processes in place for data entry and management.
Use qualitative insights: Don’t just rely on numbers. Get feedback from candidates and hiring stakeholders to get a more nuanced and comprehensive view of your hiring process.
Develop internal benchmarks: Don’t compare your startup metrics to those of other startups. Instead, start tracking your progress and using historical benchmarks.
Foster a growth mindset: Look at metrics as tools rather than rigid performance indicators. You can use some metrics without being beholden to them.
With these strategies in place, you can make recruiting metrics more useful for your team, and you’ll break away from the mindset that they’re the only indicator of success.
It’s also worth noting that there are plenty of other ways to improve hiring that are unrelated to tracking metrics. One way to boost your hiring efforts is by using a powerful ATS tool like Dover.
