3 components to get the most out of your data
Data is a tricky tool. It can have an incredibly positive impact on decision making, or a completely negative one, if 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 the most to lose, from trying to implement data on their own. Done right, data leads to understanding, understanding leads to action, and action leads to growth. But two mistakes I see most, no matter the size of the company, are: not understanding the numbers properly, or taking the context of the business and running with it — disregarding the numbers that back it up.
There are three components necessary to get the most out of your data: Context, Numbers, and Visuals. Each point of this triangle needs the other two to function effectively. Let’s walk through each one.
- Context
Context is what’s going on in or around your business and 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.
Bring that into the trade world. A landscaping company in Ohio has different context than one in Texas. The seasons differ, the fertilization schedule changes, and so on. Knowing how terminating a service line could impact total revenue and gross profit 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 allows you to effectively interact with the visuals.
Here’s what that looks like without it. Say a power-washing company sees revenue drop 15% in February compared to January. Without context, that number looks like a warning sign, right? Maybe the crew is slipping, maybe a competitor is undercutting on price. An owner reacting to the number alone might cut marketing spend or eliminate a service line to protect margin. But if February revenue drops 15% every single year because of weather, the “problem” isn’t a problem at all – it’s a pattern. Worse, if that owner cuts the wrong line in a panic, they might be cutting their highest-margin offering based on a number that never needed fixing in the first place. We could use that to alter our operations and marketing every February.
2. Numbers
There’s a myth that carries a lot of weight in our world: “the numbers don’t lie.” I’d argue they certainly can, if you don’t confirm they’re reliable. You’ve probably heard the phrase “correlation does not equal causation” – two things moving together doesn’t mean one is causing the other.
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 deeper statistical check for the very end of the report.
Here’s why that mattered: a statistical model can tell you not just whether two things move together, but how much one actually explains the other, and whether it’s plausible that one is causing the other at all. In my case, the two numbers moved together, but the model showed the income figure barely explained the birth defect rate – nowhere near enough to support the claim. On the surface, “lower income causes birth defects” could look true if you only trusted the numbers moving together. Add that deeper layer, and it falls apart.
The real explanation? Lower income correlates with higher stress, higher stress correlates with higher smoking rates, and smoking during pregnancy correlates with birth defects. That chain explains the pattern far better than income alone – but without context, you could easily convince someone that lower income was the cause.
I don’t run a full statistical check on every number that crosses my desk, but I do double- and triple-check my numbers, because I know how they can lie. No one likes statistics – I don’t think you want to hear about how R2 was low, correlation coefficient was high, and β was weak. But there are easier ways to trust the numbers. The easiest way being can your data be explained by context outside the numbers themselves. If they can’t, that’s usually when a deeper check is the right next move. Numbers help explain the context, and they set expectations for what the visuals should show.
3. Visuals
Some people think visuals tell the whole story on their own. On the contrary, visuals are interpretations of the numbers – nothing more, nothing less. As humans, we understand pictures fast. Our brains process shapes, 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 visual can carry a surprising amount of context on its own. Reading a spreadsheet and trying to spot where and how numbers moved over time is tedious work. A line gradually climbing toward the top right of the screen tells the same story in seconds instead of hours.
Visuals lead to insight, and insight leads to action – which makes choosing the right visual for the numbers significantly important, even if that means a visually repetitive dashboard. A simple, effective dashboard is worth more than a flashy one. When you’re looking at something that adds up to 100%, pie charts, stacked bars, and area charts work best, because the shape itself represents a whole, with each piece as a share of it. A line graph, on the other hand, is what you reach for when you’re showing revenue over time. I’ll admit, I reach for a fancier chart now and then – but more often than not, the simpler the graph, the faster we can act on it.
How This Connects
Have you ever spent hours, or days, studying a topic or trend, and then had to explain it to someone in seconds? The human brain can process a visual graph in roughly 80-500 milliseconds – much faster than I could get through the first sentence of an 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 we also cut a service line with margins below 10%, and there was a lot of bad weather – you might, politely, ask me to stop talking. But if I handed you a dashboard on revenue alongside a plain-English explanation, you’d understand why the numbers look the way they do, and you’d have the confidence to act on it.
That’s what happens when the three pieces work together. But it’s worth naming what happens when one is missing: visuals without context create false confidence – a clean-looking chart can lead you to the wrong conclusion just as easily as a messy spreadsheet. Numbers without visuals rarely get looked at closely enough to matter. And context without numbers is just a story – one that might feel true without actually being true.
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 business forward.
If you’re not sure which leg of the triangle your business is missing, take a look at some of our free resources for guidance.