3 components to get the most out of your data
Data is a tricky tool – sometimes dangerous. It can have incredibly positive or negative effects on decision making if it’s not handled correctly. Clive Humby made the point back in 2006 that data is the new oil. Raw data has to be processed just like crude oil has to be refined before it has any value and oil that’s mishandled doesn’t just fail to help you, it causes a spill. Without the right tools and know-how, data can hurt your company just as easily as it can help it.
The small businesses I work with have the most to gain, and yet the most to lose, from trying to implement data on their own. Done right, data leads to understanding, understanding to action, and action to growth. But two mistakes we see constantly, no matter the size of the company, are 1. not understanding the numbers, or 2. taking the context of the business/industry and running with it – disregarding the numbers that back it up.
None of this is a new idea, and I won’t pretend I came up with it. Aswath Damodaran makes the case in Narrative and Numbers that a good valuation needs both a story and the numbers to back it up. Brent Dykes builds his entire framework in Effective Data Storytelling around three pieces – data, narrative, and visuals. Cole Nussbaumer Knaflic’s Storytelling with Data comes at it from the visual side: understand the context, choose the right chart, then tell the story. I’m sure there are plenty more. The framework isn’t mine, but it’s valuable, and what I want to share is how it applies to the businesses I work with every day.
There are three components necessary to get the most out of your data: Context, Numbers, and Visuals. As we walk through each one, you’ll see how each point of the triangle needs the other two to actually function effectively.
- Context
You may have heard of context called story, narrative, or external and internal factors. All the same thing here. Context is what’s going on in and around your business and your industry that provides insight. It generally comes from three periods:
- Historical: what has happened before – what solutions worked, what failed, and the circumstances surrounding it.
- Current: immediate awareness of the environment and conditions you’re operating in right now.
- Future: with current and historical context together, we can anticipate what’s coming.
Let’s take this a step further. The context that matters most is context specific to your business and your industry – and the story you believe about it shapes every decision that follows. Take Uber. Back in 2010, Uber raised $1.25 million in its seed round. To get there, it had to convince investors to buy into a narrative. Investors either saw Uber as trying to break into the red ocean of the transportation industry – an already crowded market full of taxis, buses, and limos – or as one of the first movers into a brand-new ride-sharing category. Same company, different story. The ones who passed missed out on millions, even billions (just ask Mark Cuban, who turned down a $250,000 stake). Damodaran uses Uber as a centerpiece in his book for the same reason: in 2014 he valued it at around $6 billion, venture capitalist Bill Gurley argued the market was far bigger than Damodaran’s story allowed, and the gap between their valuations came down to the narrative, not the math.
Bring that back to trade businesses. A landscaping company in Ohio has different context than one in Texas – the seasons differ, the fertilization schedule differs, and so on. I think most would agree that knowing how terminating a service line, or letting a manager go, could impact total revenue is valuable context. Without it, a dip in revenue from one month to the next can psych you into taking action you don’t actually need to take. Context explains the numbers, and vice versa.
2. Numbers
I hear a myth that carries a lot of weight in business: “the numbers don’t lie.” I’d argue they certainly can and will if you don’t confirm they’re reliable. Correlation and regression can tell you how strongly one set of numbers moves with another, but neither can tell you why. You’ve probably heard this as “correlation does not equal causation.”
Back in college, I ran a small experiment on exactly this. I set out to see if household income could explain birth defect rates – something that, on the surface, should have almost nothing to do with the other. What I found: the lower the household income, the higher the rate of birth defects. I wrote it up like a genuinely interesting discovery, and I intentionally saved the regression results for the very end of the report.
Here’s why: correlation tells you whether two things move together. R2 tells you how much of the change in one your model explains. Beta tells you how much y moves when x moves. None of them can tell you why. Income and birth defects were correlated, and on its own the regression backed that up. The statement “lower income causes birth defects” could technically look “true” if you only trusted the numbers on the surface. But once I added smoking rates to the model, income’s effect nearly disappeared. Income wasn’t the direct driver – it was standing in for something else.
The missing explanation? Lower income correlates with high stress, high stress correlates with higher smoking rates, and higher smoking rates during pregnancy correlate with birth defects. I left that fact out on purpose, because it explains the numbers far better than income alone does. Yet without proper context, you could convince someone that lower income directly causes birth defects. The same trap shows up in trade businesses: revenue jumps in April, the same month you start running ads, and it’s tempting to credit the ads – until you remember April kicks off your busy season every single year.
Now I don’t run a linear regression on every number that crosses my desk at Levo Insight, but we do double- and triple-check our numbers, because we know they can lie. One tell that your numbers might be lying to you: check whether they can be explained by context outside the numbers themselves. If they can’t, that’s usually when a deeper statistical check is the right next move. Numbers, paired with context, explain what’s actually happening.
3. Visuals
Most people think visuals tell the whole story on their own. That couldn’t be further from the truth. Visuals are interpretations of the numbers – nothing more, nothing less. As humans, we understand pictures fast. Our brains process shapes, faces, colors, and patterns almost instantly, which means there’s a lot less mental translation happening when you’re looking at a visual, and a good one can carry a surprising amount of context on its own.
Reading a spreadsheet and trying to spot where numbers moved over time, and how much, is tedious work. Seeing a line gradually climb to the top right of the screen tells the same story but understood in seconds instead of minutes or hours. In fact I’d bet you imagined that graph in your mind while you read it. If numbers make you think, then visuals let you see.
Visuals lead to insight, and the wrong insight leads to the wrong action. That’s why it’s important to choose the right visual for the job, even if that means a visually repetitive dashboard. An effective dashboard is worth more than a pretty one with new and crazy graphs. When you’re looking at something that adds up to 100%, pie charts, stacked bar charts, and area charts work best because the shape itself visually represents one whole, with each piece as a share of it. On the other hand, using a pie chart to show revenue over time would be a poor match – a line graph handles that far better. I’ll admit I reach for a fancier-looking chart now and then, but more often than not, the simpler the graph, the better it communicates, and the faster we can act on it.
How This Connects
Have you ever spent hours, or even days, studying a topic or trend, and then had to explain it to someone in seconds? You’ve built up detail after detail – layering context on top of numbers on top of visuals – and trying to hand all of that to someone starting from zero, in seconds, is impossible. MIT researchers found the brain can identify an image it sees for as little as 13 milliseconds – far faster than I could say the first word of my explanation.
If I tried to walk you through how revenue increased over time, except for an odd dip in month seven, which is strange because we actually added a new crew that month, but on the other hand we cut a service line with profit margins below 10% but there always was a lot of crazy weather that month, and blah blah blah – I mean I’m snoring already. But if I handed you a dashboard on revenue alongside a plain English report explaining why we cut that barely profitable service line, and how a marketing adjustment drove a jump in revenue the following months, you’d take it in, understand why, and potentially act on it far more easily. Especially when presented through a story.
We covered three main elements: context, numbers, and visuals. When they’re intertwined, the relationships between them look like this: context and numbers explain each other, numbers and visuals help you understand each other, and context and visuals allow you to interact with each other.
As a business owner, it’s important to know your numbers, and even more important to understand them. Context, numbers, and visuals together give you that opportunity – and with it, the ability to make confident, informed decisions that move your goals forward. Decisions that improve efficiency and drive growth. The same decisions that turn a small business into an enterprise.
If you’re sitting on data you’re not sure how to read – or you’re not sure your numbers are telling the truth – that’s exactly what we do at Levo Insight. We build dashboards for home-service businesses and pair them with plain-English explanations of what’s driving the numbers, so you can act with confidence. Reach out at levoinsight.com, and let’s take a look at yours.