Have you ever experienced this? You are listening to a presentation, and a chart pops up on the screen. The first thought that comes to your mind? Confusion. You look around the room wondering if anyone else has a clue what this colorful enigma is supposed to represent. Instead of trying to decipher the cryptic code, you slowly lift your phone and begin to check email.

This is an all to common trend we see in conference rooms every day. We now have a sea of data pouring in from everywhere in our digital and non-digital worlds, but there is one critical element we continue to overlook. Making sense of that data to drive actionable insights. Lucky for you there is a repeatable process to building great data visualizations that do just that (Spoiler Alert: You don’t need any specialized tools to make it happen!).

With St. Patty’s Day right around the corner, we are going to have some fun with a public dataset about Irish Whiskey Sales to demonstrate how to bring your data viz to life through the following process:

  1. Choose the right visualization
  2. Declutter
  3. Get focused
  4. Bring your visualization to life

For the purpose of the exercise, let’s pretend we are an analyst at an Irish Whiskey distillery. We are tasked with providing a recommendation to the president of the company as to whether we should expand our business to the United States or Ireland. Let’s start with the “before” data visualization picture. Don’t worry, we can only go up from here…


1. Choose the Right Visualization

There are many types of visualizations out there: bar, stacked bar, line, scatterplot, slope graph, heatmap, waterfall, square area, pie and even simple text. For the purpose of this post, we will focus on bar and line charts. (I will save my disdain of pie charts for another time…)

Our visual is leveraging a stacked bar chart to display the historical trend of Irish Whiskey sales by volume across 10 countries. Stack bar charts work wonders when comparing across categories while also being able to see a portion of that category. However, what we truly need to understand here is the relative nature of the sales by country across a given time period. For that purpose, the line chart is a great fit. It allows the audience’s eye to easily understand the relative volume of whiskey sales across the countries in the visualization.

2. Declutter

With Spring cleaning right around the corner, the next step is fitting. There are three major changes we can make to our visualization to prevent our audience from getting a headache.

  • The first is removing the grid lines and deemphasizing the X and Y axis by making it a lighter grey. Heavy grid lines take focus away and compete with your visual. White space is your friend. Learn to love it!
  • Next, let’s clean up our X and Y axis. The Y axis has unnecessary trailing zeros that provide no value. We can change those to millions to help reduce clutter. As for our X axis, I am pretty sure we read left to right and not bottom to top. So why display your labels that way? Let’s flip those around so everyone in the meeting doesn’t get a crick in their neck.
  • Last, always makes sure you accurately label your X and Y axis. Otherwise, we wouldn’t know if the measure of volume for this chart is in cases of Irish whiskey or pints of Guinness.

3. Get Focused

Where and how you focus the audience’s attention is your chance to either flip the light bulb on in their head or leave them in the dark. You want to guide your audience so their “ah-ha” moment comes before you even tell them.

There are several tactics you can leverage to do this, but we will focus on color, intensity, and spatial position for now. For some odd reason, people turn into Picasso when creating a data visualization adding as many colors as PowerPoint will allow. DO NOT DO THIS. Unnecessary color only distracts your audience from the story you are trying to tell.

In our example, our decision point is whether to expand to the United States or Ireland. For that reason, let’s focus our attention there by making the United States blue and Ireland green. Note, we are using colors that are associated with the countries to make it easier to understand.. For the purpose of this exercise we don’t care how the other countries are performing. However, they do provide a good reference point. For that reason, lets group them all together with a light grey color. The low intensity of this color does not distract our audience from what they should be focusing on.

Last, we can move our labels next to the actual line. This change in spatial positioning makes it easier for our audience to reference the country they are looking at.

4. Bringing Data Visualization to Life

Now let’s bring it all together and make our data visualization come to Life. The most critical step is knowing your audience and their objective. In our case, we are presenting to the president of the company who wants a recommendation on where we should expand next. The headline of the chart is the perfect place to communicate our actionable insight we have uncovered. In our final visualization, you will note we effectively leverage color in our title to associate the United States and Ireland to their respective lines. Next, we directly annotate an inflection point in the visualization where the United States surpassed Ireland in volume of Irish Whiskey sales. This helps reinforce our point.


In today’s world, everyone is a data person whether you like it or not. Embrace it. By using this process, you will be able to make sense of your data and drive actionable insights.

At HatchWorks we firmly believe in this mantra and apply these techniques whether we are performing an analysis or building a full-scale analytics product for our clients. If you are interested in learning more about how we help companies to turn data into actionable insights, contact us for more information. Good luck and happy vizing!

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