Focus on Candidate Analytics - It's all about the stage

This week we cover 2 questions focused on Candidate Pipeline Analytics:  

1. Can you explain in more detail the types of analytics applied to the Candidate Pipeline and what they can tell us?

2. What data is needed to get going with Candidate Pipeline analytics?

Candidates Concept with Word on Folder Register of Card Index..jpeg

Let's dig in... 

1. Can you explain in more detail the types of analytics applied to the Candidate Pipeline and what they can tell us?

Sure thing.  For Candidate Analytics, it’s all about the stage…

Reruitment Analytics Candidate Pipeline Stage to Stage Analytics

At the core of candidate analytics are two key metrics: volume and conversion rates.  When analyzing your pipeline, a primary consideration is the conversion rate - how well are you doing at converting candidates from initial application to the various stages? How well are you doing at converting from one stage to another? Knowing your bottlenecks and where you have high drop off rates tells you where to focus to improve. 

At the same time, you have a certain number of roles to fill so you also have to consider quality. Is your candidate pool large enough to deliver the number of quality hires required?

Start-to-Stage Analytics:  What is the quality of the candidate pool? For all of those who are identified as potential candidates,  what volume and percentage are considered quality – and eventually become hires? This can help you determine if you have the right sourcing strategy overall and for specific roles, geographies or recruiting channels.

Stage-to-Stage Analytics:  How well are you progressing candidates through the pipeline? In this case, you are focusing on your ability to convert from one stage to another. This will help you quickly identify where you are having challenges in progressing candidates. For example, there is a high percentage of candidates converting from phone screen to 1st round interview. There is then a low percentage getting to 2nd round interview. This suggests there is an issue with the criteria to screen candidates for interviews.


2. What data is needed to get going with Candidate Pipeline Analytics?

Great question and we had a few variations of this, each with some undertone of uncertainty about the amount of work required to access the data and whether a lot of work would be required in terms of data cleansing/integrity.

So, here’s our suggestion: if you cringe when you think about the data required to do analytics on the pipeline, the first step is to understand what data is actually needed in order to do the analytics, i.e. the data required to analyze the stages and segments important to your business.  If clean-up is required, focus on the key segments first and gradually move to the next step.

There are three types of data required to be able to analyze the volume and conversion rates in your candidate pipeline: candidate pipeline process data, requisition data, and candidate data.

Here’s a quick-reference table with the data required to build the baseline set of analytics to drive insight into how well you attract, progress and hire quality candidates.

Candidate Pipeline types of data for analytics

Next week we’ll cover a very interesting topic – how to use analytics to manage and improve recruiting team performance.  Stay tuned.


See all our Talent Acquisition Analytics Infographics here


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