To be in the modern business environment is to sail against a current of change. In today's context, technical skills and analytical acumen are paramount to success in a previously unforeseeable breadth of fields. Unfortunately, upon buzzword-ification, analytics has had much of its useful definition eroded.
This was driven home for me last week when I read an inquiry from a well-meaning recruiter who was operating a little bit outside his comfort zone.
Or maybe he was comfortable: A side-effect of contentment riding the tide, unaware that it threatens to whisk us toward irrelevance... One way or the other, only a few sentences into a job advert with a title that sort of made sense for my LinkedIn profile, he lost me with the scope of this position:
"This individual will play a key role in the creation of business unit reporting functionality
to empower key business decisions."
The Issue With The Offer
Okay, they're after a dashboard jockey. That's not the right flavor for me, but it could be for someone else. The problem is that the role is called "Analytics Manager". It entails no direct reports (nix "Manager"), and employs a troubling concept of "Analytics".
Analytics, like a physical textbook, is entirely incidental. The value of analytics is information. The value of analytics professionals is generating the information and implementing a plan of action that works in his organization's context.
If you leave this page with one idea, make it this one:
Analytics Is Not Arithmetic
Basic data blending and aggregate functions are tasks, not a career.
That said, if a company wants to hire someone to create graphs from query results, far be it from me to stop them. However, armed only with this clip of the job description, the reader can easily tell this role is about giving information to the decision makers...not making decisions. What's worse, these decision makers likely (definitely) have some strong ideas about what they want reported. They need a mechanic to put the parts together.
Something a bit alarming: Until this role is filled, the decision makers in need of empowerment will, just have to sit around and keep making decisions without information.
Okay, that's facetious, but it lets you know exactly how important this role really is to the company: They want someone to give new figures to the people who are already making the decisions anyway. At the end of the day, this position is the very definition of a nice-to-have.
The ISsue With The Organization
These folks have the budget and opportunity to bring someone into their organization to analyze their data - probably the first time this "transitioning" company has had anyone do so - and the only value proposition they could come up with was reporting?
It's like putting someone in a gold mine and having them count the rocks.
This lack of vision jumps off the page to anyone who has been in the data science game and knows the strategic role analytics groups should be playing. Seeing a company hamstring their employees and themselves like this is disheartening, but not rare.
The Issue With The Title...And My Solution
Am I taking this a little personally because I've held titles similar to the one advertised?
The larger issue is that people will remain at least as confused as they are today by these titles unless we really iron out some details. Bottom line: "Analytics Manager" says basically nothing about a position, and it's up to hiring managers to understand the fine print. The title could apply equally well to a PhD mathematician and a sort-of-sober guy who can write queries with GROUP BY clauses.
As a step in the right direction, I recommend the following, still-not-perfect-but-better titles and provide some definitions:
Title: (Data) Analyst
Ah, Analyst. I can see those sharp, wire-frame glasses now. This is where I and many others started the journey. There are likely as many suitable analyst backgrounds as there are analysts. Economics, statistics, mathematics, and other quantitative studies prepare analysts for their first full-time gigs. Analysts should be voracious learners: competitive and restless. While the young wiz-kids may come to conclusions a little too quickly, some guidance will help them do exactly what you need: Fail quickly, cheaply, and forward.
Analysts work on statistical modeling and categorization problems under/with the guidance of a senior methodology developer who has more experience with the organization's data and preferred approaches.
Expect analysts to come equipped with theory but light on applied experience with a need to develop effective business communication. When you need an analyst whose work directly drives business strategy, throw a "Senior" in front of this one.
Title: Data Scientist
Specific? No, but it tells the market you're looking for someone a few cuts above entry-level researcher. This title enables you to reasonably ask for an advanced degree, a programming background, and experience applying a wide array of classification and regression techniques to real-world data.
He has worked directly with C-level executives and pivots quickly from theory to application to strategy. Importantly, your data scientist is self-directed: He wants to answer the questions you haven't asked.
Someone with this title should be able to simply and effectively communicate the importance of his findings or lack thereof.
Title: BI Analyst
Plain and simple, this is your dashboarder. He's a spreadsheet wiz, and he knows some SQL principles. While not afraid of data, he's going to be a little bit naive when it comes to drawing conclusions. That's okay though, he's a couple years out of college or fresh from an MBA program, and he'll catch on quickly.
While he's no statistician, expect a BI Analyst to understand the business needs above all else, and trust him to slice and dice the data to give you what you're after. But you have to know what you're after.
Title: BI Developer
A different beast from the BI Analyst, he likely has a computer science background and a Microsoft certification in tote. These folks have deep database knowledge that includes using tools like SSRS (SQL Server Reporting Services) to create custom reports from data warehouses. Being able (and expected) to bring disparate sources of data together programmatically naturally requires a more technical background.
While this role may sound like an outsourced IT resource at first glance, there really isn't anything enjoyable about needing to send 3 emails and make two phone calls before minor tweaks can be implemented in a dashboard. This is doubly true for departments just setting up this capability.
I don't fault companies for not knowing exactly what they're looking for. However, the way industry throws around "Analytics" titles today doesn't help employers or employees. Like "Big Data" and "A.I.", these titles get abused until they are entirely hollow.
It's time to make a change.
Am I personally convinced of a conspiracy involving BI companies conditioning innocents to believe graphs and charts are analytics? Possibly.
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