Your Analysts Are Leaving — pt 1
Here is why and how to address it
Google turnover in data science and analytics and you will quickly be inundated with ads for predictive software. News flash —
The turnover rates in data science and analytics are so high that you don’t need predictive software to forecast them. Everyone is leaving!
Perhaps the turnover rates are as low as 1 in 4 each year as reported by LinkedIN and a few other sources. But I doubt it… Remove Google and Facebook and it is likely much, much higher. In my experience, which is decades in the making, analysts last 18 months tops at most companies. For the record, my team’s tenure was north of 5 years and rising… so I have a pretty good sense of what it takes to retain great talent (and not hire poor talent). Let me share.
First, let me say that I made some strong attempts to bring more data to bear for this article. Good data on this topic is hard to come by. There are a plethora of articles — but those only go so far, so deep, and often cherry pick statistics with a bias agenda. Many don’t distinguish between:
Voluntary & Involuntary Turnover
Your first inclination may be to think quite differently about these two types of employee attrition. Given the number of times executives and hiring managers have used the term opioid addiction in recent conversations — there is merit. But we will skip past that subset as an outlier to our purpose.
In Data & Analytics, it is NOT just a matter of poor hiring. It is a matter of poor understanding at a level bordering on utter incompetence.
Sorry, some of you are flinching. You know it. Some of you are getting worked up and puffing your chest. You fear it. And some of you are totally naive to this — seek help!
Often I hear defensive managers claiming recently fired employees lacked the proper skills or sometimes the right mindset for the role. Here is a tip — this is most likely your companies fault.
Unfortunately, it is not as simple as hiring more carefully. Well it is… it is other than that simple part. Analytics is a broad discipline. Worse still it is poorly taught — typically only on the job. So hiring an analyst is not so much about acquiring a person with a great pedigree, personality, or portfolio (you can, of course, if you can pay for it). It is about aligning the specific data needs of your company to the right set of data skills.
I once asked the same question regarding the data of every individual that interviewed me. I got the answer you see here from each one. This role was with a Fortune 500 company (in Healthcare) and was for a role as Head of Business Intelligence (letters + a VP at the end). At the end of my interview, I asked the hiring executive (C-level) to let me speak to someone who could answer the question…
Analysts don’t take roles they know they are not qualified for. Aside from the double negative — the issue with this statement is know. New hires are an optimistic lot. Analysts are no exception — we just get jaded much quicker. So maybe you can blame your high involuntary turnover on blissful optimism — but I submit it is your company’s, not your new employee’s.
So how do you fix this?
Invest in understanding you data environment, your analytic needs, the nature of your data-driven (or data-averse) culture, and the size of the gaps that your analysts will need to bridge. Get an outside eye. Remember, most analytic teams are starved for resources. They honestly believe this is their biggest problem (it isn’t), but they are not inclined to be forthcoming if they think it may jeopardize getting more help.
I have assessed the data environments of hundreds of companies. Trust me — it is valuable information for hiring (as well as planning). I have screened thousands of candidates (and these days I require a data assessment below executive level). I have edited and revised plenty of job listings. But more importantly, I conduct a lot of training for top decision-makers — especially in hiring.
My point here — know your situation. Create job listings that address it. Screen your candidates appropriately. Educate them. If they know what you really need, they aren’t likely to take a role they can’t handle. But finally — educate yourself. I would add more education here — but we will leave that for part two. Read it here!
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