5 Ways to Supercharge Your Data Communications 5 Ways to Supercharge Your Data Communications
You only get the true value from your data insights if you can communicate them effectively to other people. Visualizing data... 5 Ways to Supercharge Your Data Communications

You only get the true value from your data insights if you can communicate them effectively to other people.

Visualizing data for communication is not the same as visualizing as part of exploratory data analysis. When you first encounter a dataset, you will probably create a whole bunch of heatmaps, scatter charts, time series charts, and histograms so that you can get a feel for the numbers.

But when you’re presenting your insights to people outside your team, those same visualizations are likely to be confusing or impenetrable.

As a high-level data scientist or analyst, you won’t always be speaking to other experts. Some of your most crucial conversations will be with C-suite executives, heads of other teams, compliance departments, or clients and customers. These people are time-poor, and can easily be overwhelmed by complex visualizations – meaning that you’re not driving the actions and decisions that you want to.

I’ve worked with hundreds of organizations on their data communications – ranging from startups to multinational corporations. Based on that experience, here are five ways that you can upgrade your own presentations and data communications.


  1. Start with the audience

When creating a visualization, there is an understandable tendency to start with the data and work from there. Instead, we need to jump ahead and think about the people we’re communicating with. What do they need to know? What decisions are they trying to make? How data-literate are they? Do they have any preconceptions? What are their concerns? Are they likely to be outright hostile to your conclusions? These human insights will help you make decisions about what data to include (see below), what to focus on, and how to present it.

  1. Boil down the story

If you can’t articulate what the key message is, your audience has zero chance of understanding it. It can be time-consuming to tease out the story, but it’s well-worth doing this work before you slap all the data onto the page, slide, or screen. You should be able to sum up the story in a single sentence – and a version of that sentence should be the title that appears above your visualization. If you have multiple stories to tell, create multiple visualizations. If you don’t have a story to tell, why take up peoples’ time by presenting the data to them in the first place?

  1. Choose charts with care

Chart selection is often made using a gut feeling, previous experience (“This is how we always present this data”), or based on the suggestions from a piece of software. It’s not very scientific – which is a shame, as there’s a huge amount of research that’s been done on graphic perception, or how humans interpret different types of visualizations. Back in the 1980s, William Cleveland and Robert McGill were studying graphical perception, and their insights have been refined since then. Cole Nussbaumer Knaflic’s book “Storytelling with Data” is an excellent source of information – you can see her chart guide here.

And the (free) Data Visualisation Catalogue from Severino Ribecca allows you to browse chart options by function.

  1. Don’t include everything

Less is more in data visualization – whether you’re preparing a printed report, putting together a slide deck, or creating an interactive online dashboard. Based on the needs of your audience and the story you’ve identified, you should be able to be selective about what you include. Is a model better explained if you just demonstrate the most influential features in the dataset? If you’re talking about trends in a subset of a population or a specific period of time, can you cut out everything else? You’re not hiding information – you can always give people access to the data set if they need it. But by filtering out the noise, you’re giving a clearer signal. If you want to see just how stripped-down a data visualization can get, check out the climate stripes created by Professor Ed Hawkins, and the thinking behind them.

  1. Give them something to do

When you’re presenting data to a group of people, you normally have an objective in mind. Maybe you’re trying to get a new initiative signed off, or you need them to carry out a specific action, or you’re hoping to drive behavior change. It helps to make this action clear and specific – ensuring that it’s achievable for your audience, and measurable by you. You want to avoid vague actions like, “Let’s all try harder at this,” or “Let’s change the world.” Are you pushing them in a specific direction, or presenting a range of options? Do you want them to accept and act on your insights, or come back with feedback and questions? If you can’t come up with anything actionable, then do they need to see this data?

None of these is an instant fix for data visualizations, but it should give you a set of things to consider next time you’re heading into that crucial meeting.

Learn more about Data Communications ODSC Europe 2022

I’ll be talking about these and other common challenges with presenting data in my talk at ODSC Europe 2022, titled “Communicating Data Insights with Impact.” In this session, I’ll break down common challenges that data teams face in presenting their work to others, and suggest practical solutions – which are often rooted in people and culture, rather than data and code. It is aimed at any data practitioner who is frequently presenting insights to other stakeholders.

About the author on Data Communications/ODSC Europe 2022 speaker:

Alan Rutter is the founder of Fire Plus Algebra and a specialist in data visualization. He has worked as a journalist, digital consultant, product owner, and trainer. He runs workshops for startup-focused learning organizations General Assembly and Jolt, and delivers in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, the Arts Council, and numerous universities and academic organizations. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualization courses. You can visit his website or follow him on Twitter.

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