5 petabytes of data.

That is equivalent to 5 million GB.

This massive amount of data was the backbone to the creation of the black hole image. It took Katie Bouman years to piece and unify this all that data together to make history.

You need data to innovate.

There’s no way around it.

But it’s easier said than done, right? How exactly can you use data to innovate? In this article we’ll explain to you in detail about the role of data in driving recruitment innovation.

First, data helps you determine what to innovate

In order to determine what to innovate, you have to build the right dataset from the data you have.

In recruitment, there are numerous data sources from which you can build your dataset: your ATS, your career site, and social channels just to name a few. From this massive amount of data, how do you know if you’re building the right dataset? This can be done by combining all recruitment data sources and generating the right reports.



The image of the black hole wouldn’t have been possible if Katie Bouman hadn’t found a way to coordinate radio telescopes all over the world, to gather data at varying times, and to connect them to a network that allows these telescopes to work together. She then successfully turned this massive amount of data into one verifiable image.

What can we learn from Bouman’s success?

Having the ability to unify your data streams is key.

In recruitment, the data from your online channels can potentially help you understand your candidates. However, this is only possible if you have a single, unified view of their candidate journey. If you have a certain candidate that visits your website, it would be complicated to identify and track this same candidate in your ATS.

By having a holistic view of all streams of information and the candidate journey, you’ll find it easier to understand what’s going on across the line. Through only one port of entry you can identify what jobs candidates are looking for, which channels they come from, and predict their overall behavior and how they are interacting with your campaigns.


So you’ve unified your data and now you have the information you want. It’s time to assemble it into an easy-to-read report.

Building the right report means that you only extract information that makes sense for the business. To build the right report, you need to have the end in mind. Define what your desired outcome is.

Having the end in mind also means that you can identify the hurdles that is holding you back from reaching your desired state. Say, you are looking to improve a part of the recruitment process that doesn’t work optimally. Maybe you seem to fall into the same pattern of hiring the wrong people or wasting high budgets on the wrong channels.

It would make little sense to report on the number of clicks on your website if you want to solve those problems. That metric doesn’t impact the business much and it is irrelevant to the end goal you are trying to achieve.

Instead, you can look into reverse engineering your hiring success. Where did most of our successful hires come from? It would make more sense to report on the channels that bring you the best hires. Let’s say your data sources showed you that most candidates interact with your campaigns on Glassdoor. Maybe most of your candidates that apply came through LinkedIn.

Second, data helps to build and determine the success of innovation.

You’ve innovated. You’ve come up with a novel solution to your problems.

The end?

Not so fast. Now comes the time to validate the success of your innovation by reflecting if it has made the business better.

Define KPIs

Only when you know where you currently stand can you decide where to go next.

Defining KPIs that are critical to your core business can show you to what extent you are reaching your desired state. From there, you’ll have an idea on the next steps to take to reach it.

What is your current state? How far are you to reaching your goals? Are we making progress towards our goal? Are we getting to where we want to be? Why or why not?

In this process, you would also need to involve the right people in the business to see whether your KPIs and processes are making sense. Having frequent sanity checks allows you to know gives you a good idea if are going in the right direction.

Run experiments

Experimentation precedes innovation.

Running experiments require a lot of information and data, as well as time and patience. What you need to keep into account is to not stop or change the experiments too quickly. Learning will take time and resources, so being comfortable with waiting goes a long way.

When it comes to running experiments, it’s important to keep the KISS (Keep It Simple, Stupid) principle in mind. A lot of people make the mistake of overengineering experiments and making it too complicated. If you can’t explain your experiments to your co-workers in two sentences or less, that’s when you know you need to simplify.

Review outcomes

As mentioned before, keeping track of your KPI is an essential process along the way. It is vital to knowing where you stand in reaching your goals, even reevaluating whether your goals even make sense. If what you’re trying to achieve doesn’t make sense, then it’s time to come up with new experiments.

Creating an innovation is an iterative process. Once you’ve reached the end of the process you would need constant repetition, with each experiment becoming better…

Then test, rinse, and repeat!

An essential ingredient to a culture of innovation in the company. Building a culture of innovation is an iterative process more than anything else. This also means creating an environment that encourages new ideas and new ways of thinking, and then translate it into action by driving people to run experiments continuously.

Not to mention having the right people with the right mindset, who are data-driven and digital natives, and keen on doing fast experiments and tests, complete the recipe of success. How can you build a culture of innovation?

So was that a lot to take in? To summarize, these are the 10 steps to success

  1. Hire or assign the right people
  2. Identify all (relevant) data sources
  3. Build the right dataset by combining these data sources
  4. Generate the right reports & insights
  5. Sanity check these insights with the business
  6. Identify low hanging fruit
  7. Start innovation through experiments
  8. Define KPI’s
  9. Run experiments
  10. Learn, adapt & repeat

You might be staring into a black hole … but remember that it takes a whole lot of data, coupled with innovation to see it, just ask @Katie Bouman!

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Do you want to discover you can drive innovation with your own data?

Combining the data of the whole online candidate journey with your ATS or CRM data gives you the ability to see where your hires come from. Do you want to understand how all your online sources are attributing to open job views, clicks, clicks on the apply button, applications, interviews, offers and hires? Using your data from the past, you can reverse engineer your recruitment process. Identify which channels you want to invest, when to invest, and how much in order to reach your recruitment goals. If you’re interested to learn more, have a chat with one of our representatives at info@onrecruit.net and get yourself an obligation-free demo!