The Big Data Benefit for Direct Search

by Daniel Marwan in — March 2016
“The Geeks have arrived in HR” – that’s the actual phrase when it comes to Big Data in Recruitment. The executive search industry has witnessed a dramatic shift in how board and senior-level executives are recruited.

The idea of big data is simple: Collect and evaluate millions of pieces of data and put them into a context. It is not about large files but a large number of small pieces of information which, piece by piece, result in a big picture. “There is a treasure trove of data available which can be used for direct search”, explains Daniel Marwan, owner of Talentor International. “New technologies are changing the way we work in a fundamental way.”

Most firms are using LinkedIn for recruitment. In fact, LinkedIn is the fastest growing recruiting company in the world. Indeed, there is so much data available that recruiters are suffering from information overload. Furthermore, top executive talents remain hard to recruit as they are hard to find and remain in short supply.

More candidate information makes search harder

So how do you find the needle in the haystack when the haystack has grown infinitely large? In fact, it is growing so fast that 90 % of the data was created within the last two years alone. To improve results, research has to gather and analyse the right information and convert it into intelligent action.

This requires new skills that you typically do not find in the world of recruiting (e.g. in-depth knowledge of data visualisation or predictive analytics). That’s why the geeks have arrived in HR. They are taking a quantum leap in executive talent acquisition.

"With predictive analytics, we can identify persons from the shortlist who are willing to change their job. Through this, direct search becomes smarter and more effective”

Daniel Marwan

At Talentor we are now building big data capabilities across the whole organisation. Other business services such as preferred candidate monitoring or active fluctuation management will also be provided in the near future.

If you want to learn more about our data-driven search model, contact Daniel Marwan: