Thinking Beyond the Toolbox: The 3 Stages of Exceptional Analytics

Let's make a bet.

Ask your local data scientist or analytics professional to summarize their skills, and I'll bet you a crisp $5 bill that they come back with a long list of software, tools and programming languages.

I expect it to play out kind of like this:

Phil: "Hey Gary the Data Scientist, tell me about your skills!"

Gary the Data Scientist: "Python. R. Hadoop. Excel. SQL. D3. SAS. SPSS. VBA. SVM. ETL. OLAP. JSON."

Phil: *quietly walks away, confused*

Listen, it's not that I blame Gary for answering the question that way, but what bothers me is that the conversations around analytics these days seem to be focused more on the tools themselves, rather than the actual analyses that they're designed to facilitate. The ability to manipulate data and execute code is certainly important, but you might be the world's best Python programmer and a downright terrible analyst. 

The point is, strong analytics requires a synthesis of strategy, execution, and communication.

Without strategy, it's aimless. Without execution, it's theoretical. Without communication, it's ambiguous. To become an exceptional analyst means mastering all of the above, not just the down-and-dirty data part.

Let's take a closer look.

Stage 1: Strategy

Strategy is about recognizing a challenge or opportunity, assessing your options, and identifying an effective and efficient plan of attack. Strategic analysis means doing what's right, not necessarily what you're good at.

Stage 2: Execution

Once a strategy is in place, execution means rolling up your sleeves, stepping into the ring, and going into battle with the data. This is where people with the technical chops (like our friend Gary) really shine.

Stage 3: Communication

You've set your course. You've built a brilliant strategy. You've navigated the data with unrivaled wizardry and wit.

And here's what you have to show for it:

Oh, no.

Oh god, no.

Like so many before you, you've neglected the final -- and arguably most important -- stage of them all: communication. Communication is about providing clarity. It's about translation, narration, and visualization. Simply put, it's about explaining your work in terms that someone who doesn't eat, sleep, and breathe data will comprehend.

Let's face it, your audience probably won't be a room full of classically-trained statisticians. More likely, it's a client or exec trying to quickly understand what your findings mean and how they impact the business, while simultaneously deciding whether or not you're full of s**t. A great analyst summarizes insights clearly and concisely, while providing just enough meat to establish credibility. If the CMO is eager to hear more about how much time you spent training that spatial autoregressive model, he'll ask. Trust me.

The bottom line is that each stage in the process  -- strategy, execution, and communication -- requires a completely unique mentality and skill set, which is what makes analytics so damn hard (and at the same time so damn rewarding). Most people over-index on one and a few excel equally at two, but only the true analytics unicorns have mastered all three.

Don't be a Gary. Be a unicorn.