Rick Birkenstock, a BlueSky Search Executive, provides his take on how big data is changing the recruiting world, and how it’s not.
Recruiting tools are offering more and more search features through the use of ‘big data’.
Recently an interesting and thought provoking article was brought to my attention regarding the use of ‘big data’ in the support of recruiting efforts. The link to the full article is here and the focus is on leveraging technology to mine for programming talent outside of the normal sources (Monster, Dice, LinkedIn, etc.). Not only do these new market entrants promise you help to find talent in untapped pools, but they have also developed proprietary algorithms to determine how well they code.
I certainly do think that ‘big data’ has a place in finding resources in the recruiting world. Today, we typically find very advanced search capabilities on platforms such as LinkedIn where it is possible for instance, to filter results on a wide array of criteria such as years of experience, earned degrees, location, etc. These tools make it incredibly easy to zero-in on a small number of well qualified candidates in literally seconds – that’s a form of Big Data at work.
However the practice of using automated algorithms to scour the Internet and come up with objective scoring of their skills in relation to the peer group seems inherently flawed. Think about the Klout platform for a moment. Klout is an interesting model that tries to score you as an individual influencer based on a secret formula which assigns ‘Klout’ according to how “active” you are on a variety of social networking platforms, websites, etc. Someone who fiendishly participates is bound to score higher than a peer who avoids such activities. Does that make this person a better bet as an employee? Maybe, but maybe not.
Finding a qualified and enormously talented individual is only half the battle for most employers. Sure, the skills and experience are integral to making a good hire. However, for the clients that we serve at BlueSky, too much also depends on the intangibles which are too difficult to ‘score’ or quantify in search results. How well does the candidate work in a team environment? How do they perform under pressure? What kinds of leadership attributes do they exhibit? Will the candidate be a good fit with the company culture? These critical behaviors still require a human being with relevant experience to make the assessment and ultimately spot the talent.
This conundrum reminds me of the Clint Eastwood movie “Trouble with the Curve” about an aging talent scout (for major league baseball) who shuns the big data/stats in favor of relying on his experience to judge prospects. The ‘old guy’ still knows talent when he sees (or hears) it, but the ‘new guy’ wants to sign players based on ‘big data’ or raw stats. The story ends somewhat predictably showcasing the inherent failures in trusting the data only.
Big Data is changing the way we initially source candidates. At the end of the day, however, it is still all about finding people who fit the client’s needs holistically, not simply “finding skills”.