Tracking recruitment success in the big fat data jungle

Recently I started training for the Spring Half Marathon. In my first attempts, I just left home, ran for a bit and returned. I had no idea whatsoever about the distance I’ve covered and the time it took me to do so. If my objective would be to ‘just run for a bit’, this lack of information would not be a problem at all. However, my objective is to run the aforementioned half marathon of March, preferably within two hours. In order to track my progress towards this objective, I’ve downloaded an amazing app. It provides me with incredible data about the route, distance, pace, calories burned and so on. I can even connect with my friends who are training too and get an insight into their performance as well. I find this truly helpful and it actually makes me want to run more, something I would have never expected beforehand.

There is a downside to this rich data flow though, as it is with all the available data in this (digital) age: it is very easy to get lost in it. I could spend ridiculous amounts of time looking at all the different metrics in this running app. To give you a specific example: I can see that my training buddy had an average heart rate of 174 beats per minute, at kilometer 11 out of 14, during his run yesterday. But how is this particular piece of information going to help me run 21 kilometers within 120 minutes next March? It is probably not. I could not help thinking about this example when I read a very interesting blog post about 51 HR performance metrics. Don’t get me wrong though, I love data. At Cammio we use and provide lots of data all the time. However, it is important to know where to focus on with regard to your objective (which can change over time). Whether you use data from your website analytics, your ATS, or whichever combination of sources, it is important to identify the metrics that are relevant to track your recruitment success.

In order to find out where to focus on, it helps knowing the difference between the most frequently used terms within the field of data analysis. Starting (again) with the objective, this term refers to ‘why we are doing something’. For instance, why do we have a career website, or why did we implement a video interviewing tool? An easy way to come up with good objectives is to use Kaushik’s criterium to make them DUMB: Doable, Understandable, Manageable and Beneficial. Objectives are, for example, to attract candidates, hire graduates or to have an efficient recruitment process. To accomplish the objectives, you deploy certain strategies which are the goals. Examples of goals are attracting more career site visitors or increasing candidate satisfaction. To analyze such a project, you need data. This raw data, in the form of numbers, are called metrics. Examples are the number of applicants per opening or the average time-to-hire. A Key Performance Indicator (KPI), moreover, is such a metric that indicates the progress towards an objective. This entails that the abovementioned metric of the number of applicants per opening would be a KPI, in case the objective is to attract candidates. The other one, average time-to-hire, would be a KPI for the objective of having an efficient recruitment process. For other objectives, this number could be ‘just’ a metric. Lastly, a KPI can be enriched by giving it a desired outcome, which transforms it into a target. Kaushik defines this as follows: targets are numerical values you have pre-determined as indicators for success or failure. This could, for instance, be to have 15 applicants per opening or an average time-to-hire of 18 days.

 

 

So, how can you track your recruitment success in this ocean of data? First, make sure your objective for the particular project is DUMB. Ask, for example, if your fellow recruiters understand the plan and be sure that your hiring manager provides you with sufficient resources. Then, it is time to set clear goals. At this stage you are getting more specific. Wonder what would be the right strategies to reach the objective. During your recruitment project the actual measurement starts. This is the point where the unlimited flows of data start coming in and where the focus starts. This means being picky and therefore to ignore metrics. Focus on KPI’s only, as they are connected to the objective. Or even better, critically look at specific industry benchmarks (like average time-to-hire in your home market), make them a bit more challenging and you have target. Now the numbers are actually telling you whether you are reaching what you aim for. Once you’re there, the last step is to look for causalities. Why are we, or why are we not reaching our targets? This reasoning automatically tells you what to do. That’s it! It’s a structured process in which you eventually only use a fraction of the available data. This does not mean that all the other metrics are useless. They could actually be great insights for other areas of your recruitment strategy.

At Cammio, we provide our clients with real-time reporting and analytics in their custom dashboards. But before we do so, we want to know the objectives. As part of the onboarding training, we look into the specific user cases and together come-up with ideas on how to use video. The approach can differ greatly per industry, company or even vacancy it is used for.

Happy Hiring!

Infographic | 10 recruiting trends to watch for in 2017 | Download

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