Deep Candidate Data Is the Answer
Deep candidate data would solve executive recruiting. A large-scale data collection brimming with high-quality candidate information that qualifies and calibrates executives would facilitate near-immediate hires. Companies need to start thinking “deep” when it comes to data.
Candiate data remains a challenge because it is in a state of constant flux. Executives get promoted. They leave employers. They move. They change their preferred email. They have kids. They go back to school. They go on sabbatical. And then, one way or another, they leave the workforce for good.
Consequently, candidate sourcing for executives is famously impossible to scale. The moment you’ve researched a fresh batch of spot-on senior leaders, the candidate information starts to age. These days, the information degrades very quickly.
So that database many search firms tout as their purported “crown jewel”? Its value depreciates. That forces executive search researchers and candidate sourcing teams to conduct fresh research for virtually every executive search that arises.
LinkedIn Lacks Deep Candidate Data
What about LinkedIn and its 850+ million member profiles? Its data is wide, no doubt. Yet LinkedIn’s data does not run deep. Members provide their career information, to varying degrees at various times in various fields on their profiles, making the information wildly uneven. And because LinkedIn Profiles are crowdsourced by the members themselves, the information lacks structure and consistency, making it impossible to search precisely. LinkedIn’s crude filters resemble weed whacking. You cannot yet reach into LinkedIn and pull up the ideal hire.
LinkedIn Profiles Can Be Misleading
Some members knowingly provide incorrect information about themselves. Some collapse multiple an employer at a company into a single title, usually the most recent and senior position. As a result, it often appears that an executive has worked at a company without being promoted for, say, 10 years when those previous jobs are simply not mentioned. Many LinkedIn members indicate that they’re employed when they have left their employer. It’s easier to get a job when you have a job. Many junior executives change their actual titles to make them seem more senior than they really are. So Directors of something become Heads of that thing. And then there are those pesky fake profiles.
LinkedIn Has a Dirty Data Problem
Though LinkedIn is mighty with more than 850 million members, LinkedIn information leaves a lot to be desired. LinkedIn suffers from a problem data scientists would describe as “dirty data”. All those zeroes and ones contain erroneous information. The LinkedIn Member database is inaccurate, incomplete, and inconsistent. For some in-house recruiting teams, LinkedIn has a way of making sourcing, and in turn, recruiting a living hell for companies increasingly desperate to make critical hires.
In other words, the candidate information provided on LinkedIn is so uneven, that it rarely tells us enough to determine whether a candidate is qualified. We can piece together information that we find elsewhere in press releases, articles, on corporate websites, as well as on social media: Twitter, Facebook, and TikTok.
Yet, what is missing are rich descriptions of a candidate’s experience, expertise, qualifiers, career preferences, and deal-making information. As a result, researchers and recruiters still have a lot of work to do to determine whether a potential candidate is viable. That’s why passive candidate recruitment is so laborious and virtually impossible to scale.
Deeper Candidate Data Does Exist
Deeper candidate data does exist in resume databases, job boards, and applicant tracking systems. But so far, those databases aren’t comprehensive and the platforms haven’t learned to play nicely together. So, even though the candidate information is much more detailed and structured, it remains isolated, if not abandoned altogether. And that’s a shame because all those binary zeroes and ones become much more powerful when databases are combined — a valuable lesson in computer-assisted research that I learned in my prior career as an investigative reporter. Deep candidate data done the right way would solve recruiting as we know it.
Deep Data Remains an Opportunity
Boolean Blackbelt blogger Glen Cathey makes an important point in a SourceCon presentation called The Five Levels of Talent Mining. He speaks of the need for “deeper, more structured, more searchable” data that would enable you to reach in and immediately pull out potential candidates that are spot-on. Mr. Cathey finds it remarkable, as do I, that no deep candidate data solution exists for public consumption. I’m told they do in other countries. Until then, deep data remains an incredible opportunity that we are pursuing. We invite you to join us in that quest.