We live in a golden era of big data, but more often than not, we only ever look at a small portion of it. In every industry, businesses sit on a gold mine of data that they don’t use.
It used to be that analysts’ time was cheap and data was expensive. Now, that equation has flipped. With the rise of cloud data warehouses, data is cheaper than ever to collect, and people’s time is far more valuable. In other words, we’re faced with too much data and not enough time to leverage it.
In response, we’ve dumbed down our data. We aggregate and sample to make it easier for our current BI tools to process. We use visual dashboards to help executive committees see when metrics change, but struggle to explain why. But these fail to take advantage of the wealth of factors in our data that actually have a measurable impact on business.
As a result, we tend only to see the obvious. We explain away variance in the data as “seasonality.” We find outliers. Or worse, we see nothing at all because we only consider a biased subset of variables. That’s why we have to move past the idea of “insights.” An insight alone may be interesting, surprising, or hard to find, but if it’s not actionable, it doesn’t inform good decision making.
That’s what separates the facts from the insights. Facts are well-supported, support clear decisions, and tie back to the KPIs that drive the business.
Stop focusing on outliers and extremes
The data we collect every day is both wide and deep - giving us access to hundreds of factors to understand what’s driving core metrics at a granular level. The problem is if you’re only leaning on the outliers and extremes, you’ll only see the most obvious risks and opportunities. Analysts still need to dig into the massive amount of factors in your data to understand why something is changing and what to do about it.
I’m increasingly hearing from leaders who expect more context about their data to help them drive decisions. Outliers and extremes might pique their curiosity when times are good, but when they’re navigating rougher waters, they need specific, actionable facts that can drive decisions. Well-defined customer segments are targets for new campaigns; information about which promotions in the market are and aren’t performing inform future discounting; and device-specific engagement data enables engineering improvement.
By looking deeper into their data and rigorously testing more hypotheses, companies can arm themselves with meaningful facts and can look past their trailing business metrics and tribal knowledge to get a fast, comprehensive picture of what’s changing in order to set strategy in real time. They can make better decisions.
Build a data-driven culture by caring about the facts
Every business says they want to be data-driven, but most don’t actually know what that looks like in practice.
As the Harvard Business Review pointed out recently: “The biggest obstacles to creating data-based businesses aren’t technical; they’re cultural. It is simple enough to describe how to inject data into a decision-making process. It is far harder to make this normal, even automatic, for employees — a shift in mindset that presents a daunting challenge.”
If you want your team to take data seriously, you need to demonstrate that you care about the facts, not spurious or debatable insights. This means asking pointed questions and following through with actions based on that data, not on your gut. It’s often the action step where teams seeking to be data-driven fall short because an insight in and of itself doesn’t direct the next steps.
Find facts that drive real impact
More often than not, the so-called insights we derive from data are just that - information without action.
For example, a global consumer products brand seeking to optimize their channel performance found themselves stuck at the insights level. Their existing analytics tools and highly simplified data consistently reminded them that Walmart was their biggest customer. Well, of course. But what are they going to do with that superficial, obvious insight?
This team needed help diving deeper into their rich transactional data to find the actionable facts. They wanted answers like “What products do different customer segments buy at Walmart compared to other channels?” and “Why are sales of a certain product fluctuating at Walmart?” and “What products are performing differently?”
The insight that Walmart is a dominant channel didn’t give this team the ability to change their product strategy or improve performance. But, with faster, accurate visibility into the impact of more factors, they were able to develop effective marketing and sales strategies to create new opportunities with customers and cohorts they’d never considered.
Now, more than ever, you need to be looking at your data differently. You need to leverage a more diverse set of factors in the moment to be proactive, allowing you to identify opportunities for growth, stability, and customer health. Investigating insights is a peacetime investment for companies looking for incremental gains. Acting on facts in real time will allow you to proactively leverage your data to make critical decisions and identify opportunities for growth, stability, and customer health, particularly as new opportunities arise.