This past Wednesday I took part in an Adobe chat on Twitter focused on attribution modeling. As usual, members brought a lot of value to the discussion and some great ideas were shared – but one thing in particular stood out to me.
Our need to quantify everything threatens to overwhelm us.
Amidst all the discussion it became clear that even those companies who are data-driven are still struggling to make sense of all the data. This shouldn’t come as a surprise though, as data collection and analysis can easily become a very deep rabbit hole for companies to jump into.
The thing about data is, there’s always more of it. More data points to collect, and more granularity to filter down to. So what we see happening is this: no one ever seems to have enough data. And with that, there’s never enough analysis done. Or at least, that’s the thinking.
But is it maybe possible that we focus too much on the minutiae at the expense of the bigger picture? Even more important, are we really seeing the kinds of returns on data capture and analysis that justify the expense?
Do we need data scientists to measure the ROI of our data scientists?
Now I’m not arguing that analytics are unimportant. Making good use of data to inform decisions and strategy is a key benefit to our modern technological age. But it’s important to remember that you can get lost in the data as well. Rather than being a fount of knowledge, it can turn into quicksand.
And this is the struggle I see companies dealing with today. Some are just trying to get a grasp on what being data-driven means. Others are so data-driven they can’t change a lightbulb without running an ROI analysis. But with most of them, the data just keeps getting more and more overwhelming.
It’s becoming even more of a problem as we get multiple channels working together and we attempt to reconcile the data for cross-channel attribution and intersection.
In my opinion, while there’s an important place for data and analytics in running business today, there still is some art as well. There’s the vision and there’s the soul. And when we try to become a data-driven company, we risk losing that part that I consider a key contributor to success.
Yes, we want to know that what we’re doing is working – but we also don’t want to spend all of our time just looking for information and correlations and anomalies.
Cautiously Embrace Data
Embrace data – but be wary as well. Show restraint and go into any data-driven decision with a goal or hypothesis in place. Without any caution, you risk getting lost.
This goes for the big companies as well as the small. An understanding of data is important. Knowing how to act on data is more important.
But what’s most important of all is that you show restraint in your data analysis. Or you risk sinking into that quicksand. The more you struggle, the deeper you go – until you’ve lost sight of the sky above.
If you’re not careful, your world will start to look like this:
Instead of this: