Recruitment AnalyticsI hear a lot about data, metrics and analytics. And I use the terms all the time as it’s a big selling point for our solution. But every time I hear it, the words seem interchangeable. We throw them out there with reckless abandon and fail to properly define the meaning and value of each.

This is not to say that data, metrics and analytics are not incredibly important (I believe they are) but that there is a certain danger in not truly understanding what it means to be data-driven and what you should be looking to achieve with this knowledge.

Every industry is facing this definition problem and nowhere is it more true than HR Tech.

We like data buzzwords in HR Tech

If you look at the recruitment technology space, every technology touts some sort of data solution to help you better understand your recruitment activities (and there’s many more that saying they capture all the data you’ll ever need). And the buzzwords around data are thrown about without mercy. Data, metrics and analytics are used without a real definition of what each of these terms mean and where they fall in terms of the type of knowledge and understanding you are able to get from your strategy.

But how do you truly get the heart of understanding? What needs to happen for the data you capture to be valuable to your decision making? Most importantly, how can we make sure it becomes a consistent part of our evaluation and improvement of our talent acquisition strategies?

In this post, I will look to define these terms and their relationship with one another.  I know it helps in my understanding of these terms and hope that it helps in yours.

What is Data?

When we talk about data we are talking about the 1’s and 0’s, the single inputs that enter your data warehouse for use in tracking success in your recruitment marketing campaigns. We are not at this point talking about the forward facing measures that we begin making decisions on but on how we capture and process data for further manipulation and analysis.

So when we think of data, we need to focus on a 3 main areas:

  • How is it captured?: This affects the consistent accuracy of the data analysis you can have downstream. You need to make sure that data is captured in the same manner in the same way based on the same criteria. If this isn’t occurring correctly, you’ll be hard pressed to get much value from the data you are capturing.
  • How is it stored?: Storage of data may be a little boring to talk about but in practice, how you set up and execute your data structure affects your ability to report on the data greatly. Ensuring that you store data in the most efficient way can affect your access and the speed at which you can access and utilize the data, which is integral to better decision making.
  • Is it comprehensive & agnostic? When you are capturing data you want to ensure that you are capturing data across your talent acquisition strategy and not just doing it piecemeal. You also want to make sure there are no biases in your data toward specific channels or sources and that the data set takes an agnostic view to what it’s reporting on.

Data is the first step to a fact driven strategy and it’s integral you understand how the technology you use captures, stores and reports on your data.

What are Metrics?

In recruiting, we have a lot of metrics from time to fill, cost per hire, source of hire, candidate drop-off and others. But what are metrics and what is their value to the recruiting strategy?

Once you have the data, it’s time to begin taking a look at the counts and simple ratios we can get from the data we capture.

The focus for metrics is in three main areas:

  • Counts in Real-Time: Metrics done right will provide you with updated counts of actions in real-time. From page views to contacts in the CRM to applicants to qualified candidates to hires, you should have a representative metrics view of your funnel that starts with simple counts across all actions from all sources in real-time.
  • Ratios the Matter: Metrics start as counts but the secondary value is in simple ratios between two data points. For instance, candidate drop-off is the relationship between the amount of candidates that complete one step to the ones that complete the next. These are simple measures but can give you an accurate and easy snapshot of what’s happening in your strategy. Not all metrics are valuable but focusing on the ones that you can consistently monitor the health of recruiting are important.
  • Granular and Comprehensive: Any good metrics will be provided in real-time and will be available to you on both on a per job level and an aggregate data level. For instance, you should have data that your recruiters can use to determine next actions on filling a job today as well as metrics on the full data set to understand more strategic plans down the road.

Metrics are the second step taking the data that is captured and stored and displaying it so you can begin making simple connections on what’s happening in your strategy.

What are Analytics?

Here’s the meat of this discussion and where we get the deepest in our quest for knowledge. As a caveat, Big Data is analytics on steroids but many that talk about Big Data don’t truly do it or use the term correctly (fodder for another post.)

Before I get started, I just want to point out the fact that if you don’t have data and metrics locked down, analytics are a moot point. You don’t just leap all the way to analytics. It’s a hop (data), skip (metrics) and a jump (analytics) to truly better understanding. Every step in the understanding process is as crucial as every other.

Analytics are the highest level of understanding. It’s taking the metrics that you are able to display and putting them through the ringer so to speak. It’s about relationships between the multiple metrics points enables us to find true insights in how we execute our strategies.

Whereas metrics are simple relationships, analytics are striving to provide simple insight from more complex relationships across multiple inputs. And doing so across the entire data set.

So when we look at Analytics, here are 3 main areas of focus:

  • Dashboard: To really excel at analytics, you need to first be able to have access to all of your metrics in a easy to use dashboard. If you can’t manipulate all your data across multiple factors, you won’t be able to get the benefit of analytics that you hope for. There will most likely be a lot of trial and error in figuring out what’s useful and not useful and you need a flexible solution that gives you full access.
  • Asking the right questions: The biggest question around analytics is where to start. Basically, what should be measure and test? If you don’t start with the right questions and create assumptions to test, you’ll be spinning your wheels with what could be truly valuable insight. Picking a direction (even if wrong) is integral to figuring out and learning more about your business and strategy.
  • Predictive Analytics: Buzzword Alert! But this is where we are moving as an industry. How do we take all the data and metrics at our disposal and use it to better predict the future? Questions like the following will help us better plan and execute:
    • Where are our best candidates going to come from in 2016?
    • How much of my Career Site traffic and applicants will be coming from mobile next year?
    • What skills are crucial to begin recruiting today based on future company talent needs? Will the candidate pool for those skills grow or shrink?

Analytics are the nirvana. It’s all around how we can take the data sets and metrics at our disposal to make educated bets on the future. It’s digging deeper into our understanding and consistently testing our assumptions to obtain true knowledge.

Where are you on the Knowledge Maturity Scale?

I’ve long thought about the difference between these terms and what I saw as the difference. And I hope this helps frame what’s important to think about when trying to pull insight and knowledge from the systems you use to measure your recruiting strategy.

So the real question is where are you today in terms of truly knowing and understanding your strategy? Do you currently capture data in the right way based on the same data across all of your sources and initiatives? Do you have easy access to the metrics that are integral to understanding the health of your recruitment strategy? Are you starting to think about the key questions you need to answer for both today and the future and beginning to delve into your recruiting analytics dashboards to try and figure out the answers?

It’s time for self-reflection. How knowledgeable is your organization today and what type of understanding do you want tomorrow?


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