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Create Visuals that Are Worth a Thousand Words

Between 1853 and 1855 a young physician named John Snow generated dot graphs to track the spread of cholera in London. By visually comparing the prevalence of cholera in two districts that drew water from different sources, he was able to link the disease to microbes in water that came from the Broad Street Pump. Snow's breakthrough occurred before Louis Pasteur's proved in 1864 that germs cause disease.

Now, we use visuals of all types to analyze and summarize big and little data. Here are some tips on creating meaningful visuals:

  • Carefully analyze your data and decide, "What does this mean?" For instance, do increases in local home prices suggest that the economy is improving or that the stock of homes is very low or both?
  • Tell your audience how you want them to interpret your visual. Embed the message in the title, caption, or legend. The title of a recent Wall Street Journal figure is Consumer Confidence Index. Fortunately, the title tells you how to interpret the data: "Confidence Up, but Still Below Prerecession Level."
  • Use the right type of visual. John Snow's cholera graph was a scatter plot overlaid on a London street map to emphasize geographic location. To represent the incidence of cholera cases over time, he could have used a line graph. For year-to-year comparisons, he could have used bar graphs. Pie charts or area graphs would have been a good way to display the incidence of all types of infectious disease during the cholera epidemic.
  • Keep it simple. Provide enough, but not too much, data and text. Omit extraneous words and images. Keep the focus on the data. Twenty years worth of data may not be necessary.
  • Provide the source for your data and the year(s) when the data was collected. It is important to know when the data was collected rather than reported. Government data is often a few years old.
  • Label all data items using the right units for your readers. In some graphs the 'x' or 'y' axis lacks labels, and the units are not intuitive. When referring to foreign currency, consider providing dollar equivalents.
  • Provide captions for all images. Translate captions that are in foreign languages. An online museum exhibit contained images that either had no captions, captions with small print, or captions that were in foreign languages. Viewers had no idea what the individual images signified or what the exhibit as a whole meant.
  • Divide and conquer. Instead of squeezing data about tax rates in each of the fifty states into one visual, divide the data into four or five regional graphs. Alternatively, use a table with states grouped by tax rate or regions or alphabetically, depending on emphasis.
  • Let the medium dictate the design. Avoid backgrounds or colors that make type and images unreadable. Items represented in different shades of gray in newspaper graphs are indistinguishable. Visuals displayed online need a typeface and font that are readable on any computer. Visuals for mobile devices should be smaller and simpler. Test whether your images display clearly on the intended devices.
  • What's next? What should the reader conclude or do after becoming familiar with the data? A chart with interest rates for different types of bank accounts could have the following caption: "Select an investment arrangement that suits your time horizon, average balance, and cash needs."

Graphs and other visuals are convenient ways of organizing and presenting data in a meaningful way. Know what your data says, and know what you want your data to say to your audience.Then create visuals and text that complement each other and that are easy to grasp. Achieve a simple, uncluttered look. Don't get carried away with fancy fonts or free clip art.

Sources:

John Snow by Ralph R. Frerichs

Graph Types, www.google.com/search?q=types+of+graphs. [Includes three dimensional graphs. Use these if they increase reader comprehension.].

Harbart, Tam ,"Tech hotshots: The rise of the dataviz expert", 5/23/13, [The article summarizes Stephen Few's groundbreaking work in data visualization].

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Market Intelligence for Growing Companies © June, 2013

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