Now might be the time to admit it: You have a data problem. You’re surrounded by it. It’s flooded your desk, overwhelmed your hard drive and is piling up like floor-to-ceiling garbage in your consciousness. And you’re afraid to throw any of it away. “What if I need it one day? I invested in it, so it has to be worth keeping, right?” You’ve ended up in this cluttered mess, surrounded by information when all you really wanted is to be surrounded by answers.
You’re a data hoarder. But you are not alone and help is out there.
For the last couple of years, Big Data has been the fixation of every marketer struggling to understand its audience better, and for understandable reasons. We know the world of content is fractured. People consume wide, varied streams, from traditional TV to search engines, social networks and mobile apps.
And as their consumption footprints expand, marketers have responded by diversifying how they reach people and the way they measure those interactions. Marketers today spend so much time collecting every single real-time data metric (shopper data, digital data, social data, mobile data, etc.), but they easily lose sight of the true purpose for collecting all this information in the first place: to find insights that will help them be smarter and more efficient. The Big Data idea has been: “With this much info at our fingertips, marketers can’t lose.” But the reality is that Big Data is often a damn mess.
The truth is that more stuff does not make your house and life better, and more data does not make you smarter or provide more meaningful insights. Most marketers waste a lot energy collecting data that is not usable and would greatly benefit from a new Small Data strategy. It’s about efficient effort for maximum effect. Unless you have an army of Google statisticians at your disposal, why collect metrics that provide no real insight?
As a hoarder, you have the same problem every hoarder has—whether you are hoarding trash you collected from a dumpster or stockpiling metrics. You don’t know how to say, “Enough already.” What is the first thing professional organizers do in dealing with hoarders? They take assessment of the situation, create a plan of attack and begin throwing stuff out. You need to do the same.
Start backwards. Decide where you want to go before you even begin. A learning agenda is a great way to start—meaning, align your objectives with learning questions. Accept that there are always priorities when it comes to objectives, and if that list of “what’s important” includes everything and the kitchen sink, you are setting yourself up for failure.
Next, get your KPIs (key performance indicators) organized. Every objective you have can be measured through a wee list of KPIs. (Smoke, for example, is a pretty dependable KPI for fire.) If you feel the list is too small, that’s actually a sign you’re doing it right.
You may have a few metrics working together to create a KPI (engagement scores typically combine Facebook likes, Twitter impressions and social media engagement metrics divided by the number of unique visitors), and that’s OK as long as it is laddering up to one of your few objectives. You will be tempted to hoard data simply for the sake of collecting data, but if a metric exists that does not have a home, it is probably not worth measuring. Or worse, you may have forgotten an important objective which includes this metric. Keep the KPIs aligned with specific objectives, neatly and cleanly.
Big Data might be OK if you have resources, expertise and time lines to properly mine multiple sources of data, process those data points, and integrate and refine them into insights. But try to give yourself a little intervention here to look for hoarding tendencies.
Look at yourself in the mirror and ask if you really have this luxury of maintaining a Big Data approach under compressed deadlines. A Small Data strategy is powerful in its simplicity and effectiveness.
Small works. Time to clean up your act.