It’s not what a chart says, it’s what you hear. The best visualizations in the world mean nothing when the person looking at them has no idea what they’re seeing. As analytics evolves and moves off of the desk of the analyst and into factories, warehouses, or assembly lines, things will need to change. Indeed, there’s a ton of potential here to democratize the power of data and analytics, but only if you’re sensitive to what people need and how they understand information. Here’s how you can develop analytics tools for folks that don’t click a mouse for a living.

Talk to people and ask what they need

It seems obvious, but your first step should be to talk to the intended audience for your charts. When making charts for someone else, many make the mistake of assuming what other people want or need. “We stopped telling people what they needed,” says Gary Cifatte, CTO at Assuming you know what people want better than they do is a recipe for wasted time and a subpar result, but it’s an easy trap to fall for. “Everyone signs off on it. Then you deliver the product, and they go, ‘this is great, but it doesn’t do anything that helps us’,” says Cifatte. While it’s natural to assume that a non-technical audience may not know how to best construct an analytics visualization, the opposite is also true. The average data analyst or IT worker can’t know how everyone else in the company does their job.

Watch how people work

Talking to people is a great step towards understanding their needs, but you can learn almost as much just by watching people work. We often end up blind to inefficiency in our everyday lives. A worker can tell you if something drives them crazy, but they may not be aware of smaller issues, or ways to improve efficiency. Take some time to watch people work, and look out for things you would change. As an outsider, you’ll be naive to this new world, but sometimes it takes a beginner to recognize something that old-timers never thought to think about.

Try it yourself

In addition to asking people about their needs, try to spend some time in their shoes. Experience what their day-to-day is like. If you’re building a reporting dashboard for an assembly line, try shadowing a few workers. You can even try doing the work yourself. Whatever your approach, you need to start with a solid understanding of the needs of your audience. “Audience should be front and foremost in your mind throughout the analytical process. This means understanding how your audience sees,” says Cole Nussbaumer Knaflic, author of Storytelling with Data. So whether you talk to people or work alongside them, make sure you can picture the user and what they go through.

Show people a better way

Sometimes even great tools never take off because despite being great, no one uses them. To workers used to a certain way of doing things, it’s naturally to be suspicious of new processes. “It been difficult for people who’ve been there for forty years to change their processes, but if you truly show people the light I think they’re happy to come around eventually,” says Jonathan Holley, Marketing Analyst at Bailey International. Talking to your audience not only helps you research the problem, it shows workers that you’re at least attempting to see things from their perspective.

Do your homework

Every business has unique needs, but they may not be as unique as you think. You can save a bunch of time by learning about industry best practices. While visualizing certain aspects of your business will require a custom touch, you’ll likely find that most of your analytics needs have been covered in one form or another. Read some case studies and study how other companies approach analytics and reporting.

Keep it simple

At iCharts, we like to tell people to start small, especially if your charts are for a less technical audience. While it’s tempting to come right out of the gate with a big, complex, and nuanced data visualization, these sorts of charts are typically hard to read, especially for the uninitiated. Start with something basic. If you insist on nitpicking over the chart, focus on how you can make it easier to read, not how you can cram more data in. “Think about how you’re using things like color and size,” says Knaflic. Little changes can make a big difference, but once again, less is more. While a splash of color can add emphasis, too much of it can drown out the message. “Don’t ever assume someone looking at the same data visualizations will walk away with the same conclusions,” says Knaflic. By starting simple, you’re more likely to create something that’s straightforward and easy to read. Furthermore, simple charts form a baseline for future experimentation.


While simple is usually best, there’s nothing wrong with a little experimentation. Once workers start to get the hang of your charts, it may be time to make some tweaks. Once again, you should listen to feedback from the audience, see how it works for yourself, and trust your judgement. By adding complexity in stages, you can be sure things don’t get too complicated too fast. Make sure that if you do end up going overboard there’s a simple way to take a step back. Remember that the simplest approach usually works best, even for a tech-savvy audience.

Trust your experience

The more you get to know your audience, the better you’ll be at making something they’ll use, but before you spend hours building every last chart someone asked for, stop and think. Unfortunately, what people want is often different from what they need or what they’ll actually use. As the person constructing these analytics dashboards and charts, it’s your job to know when to say no. Ask yourself if this is something that can make someone’s job easier.

The best analytics are the ones people actually use, but that starts with knowing what people need. Until recently, analytics has mostly focused on offering high-level views of an organization. However, as analytics tools become more common and work their way down into lower levels of an organization, it’s easy to find yourself out of touch with the problem at hand. So talk to people, get your hands dirty, and give people a tool they’ll actually want to use.

For analytics best practices, check out our resources page.

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