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Distefano: Let’s say [a CEO] needs a new chief of staff. He’d ask people to take a quick assessment in KF4D. We’d ask the company to tell us, “What does this chief need to be competent in?” You could choose 15 skills out of 38, and we’d ask you to sort them into high, medium, or low [priority]. And then tell us about your [company] culture. Finally, what does the person need to do – e.g., are you hiring them to drive change? We take that input from the client, and combine with a deep catalogue of benchmarks. The algorithm takes that together, crunches it, and comes back to us with the profile of the person we are looking for. Our recruiters go out, find candidates, and then they take an assessment.
** Shoves rifle in orifice **
** Contemplates yanking trigger **
Wait … who thinks this would work?
Let’s start with the most basic idea possible: the above idea is actually great. It’s exactly how you should hire. You think about competencies, core skills, the overall culture, use some historical benchmarks (which Korn-Ferry, who is doing this, has access to), core responsibilities, and bang, there’s your picture of who you need to hire. At base, if this goes well/properly, it is actually “hiring with intention.”
Here are the various problems I can see with the model:
- Recruiting is by no means a perfect science: Even if you bring Big Data into it, which is essentially what’s happening here, the human element is still a concern.
- Things break down in every hiring process: People have been trying to map out a perfect hiring process for generations. You know what happens? Other priorities come up. Communication is poor. Etc.
- You can’t rely on “Big Data” when making C-Suite hires, because those types of people believe in “gut feel” more than anything: They don’t want “Big Data” to interfere with their ability to make a gut-sense hiring decision, honestly. Getting senior people to embrace the concept of Big Data is going to be such a challenge as is; forget about the “hiring of their peers” space.
- What does the C-Suite fear? More than anything else, it’s incompetence. They’re not going to let some 2-million-plus dataset influence their hiring if it feels like a person is coming in who might be a politically-unsavvy move, or expose them as a fraud in some way, etc. Big Data ideas cannot defeat human nature ones. Not yet.
- The whole thing is subjective anyway: I can tell you this first-hand. I’m sure it’s probably even worse at a much-higher level. (Bigger potential reward = more analysis paralysis.)
- Other C-Suiters will push their preferred political candidate through: And the logic will be, “OK, well, the data says this … but whatever, anyone can learn anything, right? This is my man!” Ironically, that’s the same attitude that most hiring managers use to keep the rank-and-file down in terms of hiring. That, and this.
This is one of those things that seems like a good idea on surface — maybe we should use a combo of skill sets, benchmarked data, and cultural fit/role responsibility to make a hiring decision — but when you factor in a little thing called human nature, it will never, ever work as planned.