An Ode to Analysts
Founder & CEO
Most people who work in research and analytics will tell you, data is rough. It’s hard to access, impossible to aggregate cleanly, it’s error prone, it’s time consuming and most of what you work through is not really looked at, understood, or cared about. And, most of your best hunches lead to a dead end, or some heinous insight where you figure out that rain is likely in Seattle, or that more people in New York are likely to be fans of the Yankees. Next.
When a small part of a report is wrong, people yell at you – and when everything is right, people still yell at you, because they don’t like what the data tells them and that’s somehow your fault. At best, it can lead to action, to creativity, to new stuff that makes the world (or at least, a piece of brand content) better – and at worst, it simply leads to nothing.
The nothing part bothers me the most.
Probably, because I’m a maximizer and lost opportunity kills me. And because, living in data and looking at it every day, I believe so fully in the capacity for insights to shift business strategy, confirm or question what you think you know, and to help decision-makers (that’s everyone, by the way) see around corners. Or maybe, it’s just because I know how hard it is to surface anything in data that is worth sharing, that when you do it’s a crime not to do something about it.
Let’s start with what anyone who wants to work in data needs to know first:
When working with data, most investigations lead to a dead end. Period. Your best hypothesis, for the most part, will not pan out. Ever.
Any analyst or data scientist who doesn’t start with this basic truth is either a liar, far far better than me or anyone I’ve ever met, or trying to sell something that they hope the buyer doesn’t understand because if they did, they wouldn’t bite down on it.
Far from being neat and prescriptive, data is the messiest work of all – at least if we’re talking about the kind of data that inspires magical thinking. Working with data is iterative, discouraging, and frequently fruitless despite your smart instincts and reasonable theories.
So how do we get there? With persistent, dogged drudgery and a passion for unraveling why this set of people love what they love. How they’re connected together in values or vision, if not simply by age, gender or by how much money they make each year at a job that they hate. And what all of this actually means for how we, as publishers, creators, brand marketers, must therefore reimagine our stories and how we communicate for our audience.
Things to consider:
– What’s actionable rather than merely interesting – will this insight make people more likely rather than less likely to take risks?
– Does this confirm what I already believe, or does it in some way challenge what I believe to be true/correct?
– Have I tried to make meaning out of all of this, or am I merely stating what is evidently true, that anyone picking up what I’m working on could see for themselves? (This is the – what am I bringing to this? – question)
– Have I taken this far enough, or could I/should I/should someone else push further?
– Is anything in here politically difficult to share (yes folks, that’s a real question that every researcher needs to ask him/herself when sharing insights, if you want to increase the likelihood that this will ever see the light of day), and if so – what’s my plan for that?
I hope this wasn’t too discouraging. But if a simple article can discourage you from analytics, then you probably shouldn’t’ be doing it anyway. Good luck!