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Introducing Candidate Drop-Off Insight

The pressure to hire faster leaves little time to reflect on the hiring pipeline and pinpoint recruitment processes that need improving. Enter Candidate Drop-Off Insights – your go-to tool to improve hiring as you go and always keep top talent in the pipeline.

When left unattended in the hiring process for too long, candidates tend to withdraw their application, reject your offer, or accept another offer altogether. This creates a lot of waste for the hiring team, putting additional pressure to start the recruiting process from scratch.

With Candidate Drop-Off Insight, you get a timely look into the bottlenecks in your hiring process, which you can then remedy and make sure the right candidate stays in the pipeline, and – hopefully – joins the team.

What is Candidate Drop-Off Insight?

Candidate Drop-Off Insight is a new feature within our Talent Acquisition chapter, that warns you about any significant trends in the number of candidates dropping out of your recruitment process.

Just like with all other Insights in Orgnostic, Candidate Drop-Off Insight is only activated when we identify a potential issue arising in your data.

This means that you won’t see Candidate Drop-Off Insight feature until we detect patterns that you should look into in order to improve the rate of candidates dropping off.

With Candidate Drop-Off Insight, you get information on:

  • which hiring stages require your attention
  • what might be causing the problem
  • suggestions on how to improve your pipeline.

Let’s now break this down into specific figures you will be able to access with this new feature.

Information you get with Candidate Drop-Off Insight

First, you get an insight into stages with an unusually high number of candidates withdrawing from the process.

Overview of Candidate Drop-Off Insights

Plus, you get info about what a healthy drop-off rate should look like for your organization. That way, you know what drop-off rate you should aspire to achieve.

A comparison of drop-off rates for your organization vs a healthy drop-off rate

Second, you get an insight into whether time spent in a stage co-occurred with high drop-off rates for a specific stage, which helps you diagnose the cause of the problem.

Third, you get a quick glance into roles or other units with the highest unusual drop-off rates. This way, you know which units require your immediate attention.

Candidate Drop-Off Insights help you pinpoint roles with the highest drop-off rates so you can act timely.

Finally, you get an overview of the number of candidates who have dropped off and who were kept significantly longer in the recruitment process.

An overview of the percentage of candidates who have dropped off

How Does the Candidate Drop-Off Insight Work?

As we’ve mentioned, Candidate Drop-Off Insight is activated only if there’s an issue with drop-off rates in your organization, so you won’t be bothered with unnecessary notifications.

When your hiring data meets a few predefined assumptions, we run a relevant statistical or Machine Learning algorithm to check whether we can identify an actionable insight.

The cleaner this data is, the more reliable conclusions can be extracted.

You can track and clean this data by properly managing your candidates in the ATS (Applicant Tracking System). For example, setting hiring stages in a clear manner and regularly updating the status of your candidates is a good step towards having clean data.

Under the hood

Our Insights rely on various statistical methods that try to identify the bottlenecks in your hiring pipeline based on your data, rather than on arbitrary rules. That way, we tailor our conclusions specifically for you and your organization.

For example, concluding which stage might need your attention relies on our estimation of how a healthy stage drop-off should look like, by using data on all stages and all candidates during a specific period of time.

After that, we test if there is a co-occurrence with other problems related to that stage.

For example, we’re using statistical tests to conclude if candidates who left the process spent significantly more time in your recruitment process when compared to candidates who did not leave the process on their own.

Using statistical tests ensures that only consistent differences surface to you.

How to Get Insights on Candidates Dropping Off

With the Orgnostic People Analytics platform, the Insights on top candidates dropping off from your recruitment are only a few steps away:

  1. Register on the Orgnostic Platform, if you haven’t already.
  2. Connect your ATS.
  3. After the data is pulled, go to Story.
  4. Click on the Talent Acquisition chapter.
  5. If there is room to optimize your TA pipeline,  you’ll see your Candidate Drop-Off Insight.

What’s next for Orgnostic Insights?

Talent Acquisition Insights offer you a new way to look at your hiring process and then make data-driven diagnosis and decisions to improve it.

We are constantly looking for new ways to extract valuable conclusions from your data, while simultaneously relying on statistical rigor and scientific articles.

There are more Insights coming up, so stay tuned to learn more about employees at high risk of leaving or the impact of burnout and environmental support on employees’ performance, to name a few.

Want to improve your recruitment and bring top talent onboard? 👉 Start your people analytics journey
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