Q&A: 5 Minutes with KeyInterval Research Principal William Tincup
1.What does “big data” mean to you (and should recruiters believe the hype)?
Big data is an aspiration…a goal to connect the dots between things we’re not already thinking about. We know what we know…but we can’t fathom what we don’t know. As Donald Rumsfeld calls it so eloquently…”the unknown unknowns.” An example of that might be Tuesdays are your best interviewing days. Or, Sally is indeed a terrible manager but she’s that way because she’s been screwed over by her boss on her commissions three years running and her team is the wrong culture match for her. So, she’s terrible but “big data” might unlock why and/or how to fix it. I don’t know. I don’t know if I believe the hype. Then again, I’m a professional skeptic.
As for recruiters, should they believe the hype? No. They should be very skeptical of snake oil salesmen selling snake oil. They should take a “show me” stance. Read that as bore me with details and examples of big data.
2. What are some of the most common myths or misconceptions about analytics recruiting and HR that pros need to know?
For me, the biggest misconception is that what works one place at one time would be the same for someone else at some other time. I mean, people are lazy…and I guess we’re all trying to make sense of an imperfect world, but if I’m a recruiter at Twitter, searching the land high and low for software engineers versus a recruiter that works for a Pizza Hut franchise owner in Midland, Texas, our realities are as different as Legos and trashcans. Meaning, would we ever look at the same analytics? Probably not. Analytics should be deeply personal and written in pencil.
3. What are some of the greatest opportunities or outcomes employers should focus on in terms of utilizing data or analytics? Any advice for getting started?
Map all recruiting analytics to the goals and/or initiatives of the firm. Direct connections to these things are not fuzzy logic. It’s not a question of whether or not you can measure it, it’s should you measure it. And the should you…well, that’s where mapping to the business is critical.
4. When you look at using analytics to improve recruiting, who’s getting it right? Any specific examples you can share (personal or otherwise) as an example of someone who personifies a “data driven recruiter?”
The people that are doing this best are hidden from us and rightfully so. The folks that are really doing this are contributing to the secret sauce of the firms they work for. Meaning, they are creating real competitive edge, and if they are out talking about it via conferences and in other ways, then it won’t serve as a competitive differentiation for very long. Talkers talk. Leaders lead. And really innovative practitioners rarely talk publicly. It is what it is.
5. In 140 characters or less, why are analytics important? Give us your best elevator pitch.
I don’t know what I don’t know. Do analytics fill in those blanks? If so, great. If not, search for the analytics that do fill in gaps.
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