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Data-Driven Charts: The Good, Bad, and the Ugly

It is generally believed that well-presented material – clear, concise, orderly, consistent, MECE (mutually exclusive, collectively exhaustive) – is perceived to be more credible, which makes developing a high-quality presentation a goal worth pursuing. In order to achieve that goal, it must be understood that there are basically three aspects of a presentation that must be well developed; and each has its own best-practice criteria.

  1. Style – frameworks and images that help tell the story must be formatted to blend with the style of the template.
  2. Verbal/written message – correct flow, grammar, punctuation, consistent use of terms, first-referenced acronyms, etc., all need to be present in order for a solid message to be conveyed properly.
  3. Data – clearly drawn, uncluttered data-driven charts with all pertinent information laid out in a consistent manner without redundancies are necessary to provide the proof that your verbal/written claims are valid.

We're going to explore the best-practice criteria of a well-drawn chart. In the process, we'll applaud the good charts, identify the bad charts so they can be avoided, and cringe at the technically correct but visually ugly charts. Chart formatting best-practice criteria are categorized in three ways:

  • Components of data-driven charts – fields that all data-driven charts need to have present, i.e., a basic template layout.
  • Chart elements – preferred formatting for the parts of the data-driven chart so that the correct parts of the charts are visually dominant and the real estate is properly used.
  • Color in charts – guidelines for applying/using color in charts.

Components of Data-driven charts

The chart components need to be laid out thoughtfully and consistently, which helps brand the material you're presenting. This standardized layout also helps your audience find information quickly, e.g., when a legend is in the same place all the time, your audience will automatically look there first for the information they need. Another benefit of the thoughtful placement of the chart components is that they will actually define the boundaries of the content field. The example below is a vanilla chart layout, which can be adjusted to accommodate the design elements of your template. No chart layout template can ever be vanilla enough to work seamlessly with all proprietary templates, but this one is pretty good.

  1. This is the overall content field for data-driven charts (and all types of content). It contains all of the components that need to be present for data-driven charts.
  2. The chart title, of course. In this layout the chart title defines the top left-hand side of the content field. The chart title should have the largest size font on the whole chart. Don't format the other text in the chart to be larger than the title. Also, don't make the chart title font size too much larger than the rest of the text on the slide, e.g., a 40-point font for a chart title and an 18-point font for the body of the chart is probably too much of a disparity. The page looks too unbalanced when there is too large a range of font sizes. The chart title should build up as lines are added. This keeps the size of the area that contains the actual data-driven chart constant.
  3. The subtitle should build down as more lines are added. This will prevent the title and subtitle from colliding. The subtitle should be distinctive: different color, slightly smaller font size, italicized, etc.
  4. Units of Measurement
    1. The first level for the unit of measure is right below the subtitle. Use this position if the data on the chart is represented in i) only one unit or ii) there is only one chart on the page and, therefore, only need for one unit of measure field. Remember that you want to avoid redundancies, so identify the unit of measure at the highest possible level.
    2. Secondary levels for the unit of measure are under the x and y axis headings and
    3. Under the heading text for each of the multiple data-driven charts on the page, e.g., there are four line charts on the slide and each has its own heading (title) describing the contents of the chart so each has its own unit of measure.
  1. Identifiers are used to qualify the data being presented. Typical identifiers are "preliminary," "example," or "illustrative." Many times the use of an identifier will eliminate the need for sourcing information. The identifier can define the upper right-hand border for the content field.
  2. The legends can usually occupy the area under the identifier. If no identifier is needed, move the legend up into the identifier position. This side of the chart is often without content, so it's a good position for legend information. If the chart title/subtitle is long, drop the legend down under the title.
  3. This is the field where the actual data-driven chart is placed. This is the also prime real estate on the slide.
  4. Axis headings (8a and/or 8b) text headings above each data-driven chart (if multiple charts are used) are descriptors that need to be formatted consistently from chart to chart and page to page.
  5. The footnote/note/source field is placed at the bottom left-hand corner of the content field. This field builds up as lines are added.
  6. Text fields should be set up at the master level. We advocate for the first level being left-aligned, nonbulleted text. The top level of all text is a heading, which does not usually have a bullet. Therefore, this is how the text hierarchy should be set at the master level.

Chart Elements

Establishing preferences for chart elements is as important as including and consistently laying the components of a chart. Where the components of the chart establish the fields, the chart elements preferences determine whether the information you're presenting is clear and understandable.

How many times have you seen the default chart formats in presentations? Too often? The default chart formats in PowerPoint do not do your hard-won data justice. The graphic below is an example of a default chart, and the text in red describes issues that prevent the chart from presenting well.

It usually takes a tremendous amount of effort to identify correct and usable data for charts. Be sure you spend time formatting the chart so that it presents your data in the most compelling way.

The example below is a comparison between a default chart and a chart formatted to a best-practice standard. Notice that the overall use of space is much better in the reformatted best-practice chart. The text in blue describes the formatting changes that were made and the reasons for doing so.

The most dominant aspect of the best-practice chart is the columns

Bolding taken off text labels; if everything is bold, then nothing stands out

The columns have numeric values, eliminating the need for a y axis

There are no lines, only fills, which reduces the visual clutter

The 3D is eliminated, eliminating the ambiguity of the column heights

No gridlines or horizontal tick marks are necessary

Space between the groups is reduced, making the columns thicker

Autolegend is eliminated and replaced with one that does not take up prime real estate

The best practice chart is a much better vehicle for presenting your supporting data-driven material. There are no superfluous elements on the chart. The message is vividly clear.

You may, however, wish to format the labels under the horizontal baseline differently. This text was entered into and plotted by Microsoft Graph. Notice how far the labels drop down from the baseline? Also, if they contained much more text, they would begin to wrap; and it's difficult to control the line breaks in the graphing program. You may want to disable the automatic labeling and add the text labels to the chart as individual fields. Then it would be easier to manage layout and space utilization. It takes time to reclaim/control space on a chart, but the effort is worthwhile.

The 3D was eliminated from the best-practice chart. In general, 3D formatting in data-driven charts is strongly discouraged. Never sacrifice clarity for a style choice.

Here is another comparison between a default chart and a best-practice chart. The blue text below and to the right explains the formatting changes that were made and why.

The slices are labeled, eliminating the need for a legend; the audience does not have to work so hard to understand the information being presented.

The best-practice chart's slices are all the same color, making it possible to highlight individual segments to add additional information.

The slices now have numeric values, making it easier for your audience to value the slices. Segments should always have numeric values when it is not strategically important to keep the exact data off the chart.

The border around the pie is unnecessary.

The legend is unnecessary. It is better to label the slices than use a legend.

All in all, a cleaner chart and a better use of real estate

Don't make your audience work harder than necessary to understand your message. They shouldn't have to wade through unnecessary elements or redundancies on the page to get to the heart of your message. Best practices are to:

  • Eliminate the unnecessary elements of a chart
  • Remove redundancies
  • Place the information necessary for understanding the data as close to the plotted segments as possible.

Be kind to your audience by imposing these best practices. If they're not working so hard to extract the information from the slide, they're paying more attention to you!

Here is another comparison between a default chart and a best-practice chart. The comments in blue explain the formatting changes that were made to the default chart and why they were made.

The size of the sprites increased to 10 points, now the most dominant features of the chart are the sprites

Bold taken off text; if everything is bold, then nothing stands out

Gridlines have been lightened to gray. By fading them the sprites (as with all other plotted columns, bars, lines, bubbles) tend to be more prominent and "pop"

Autolegend is eliminated and replaced with one that does not take up prime real estate

The tick marks on the axes are on the outside. If you choose this position, make sure that you use it consistently from chart to chart. Other options are tick marks that cross the baseline or are on the inside. The chart tends to look cleaner when they are on the inside, but you can decide for yourself which works best

The yellow sprites were changed to blue so they would show up better against the background

Color in Charts

Color not only brands the charts to your company's template and color scheme, it is also a powerful tool that should not be traded away unnecessarily. For example, in the pie chart above, the default chart assigned a different color to each of the slices. This is not a great practice for very good reason: you're not able to use color to highlight a segment or two so you can add another level of information to the chart. It's best just to handle that issue by adhering to the best practice of using color deliberately and strategically, not for the sake of variety and pizzazz. Variety is counterproductive to maintaining consistency; and pizzazz should be added by way of content, not sparkly accessories like random color applications, animation that does not support the messages, or inappropriate graphics.

There are also other aspects of color in data-driven charts that you need to understand.

  • You should identify an alternative set of colors in case you need more colors than your palette can supply. Color can often be a differentiating tool: some charts need many different segments and, therefore, many different colors. Don't let the graphing program select the colors for you. They won't blend with your palette. Identify additional colors that you can bring into play when necessary.
  • You should also look carefully at how the graphing program is pulling from your palette. For example, there is a company that uses blue, gold, and maroon in their template. The primary color is blue. Different hues of the primary blue are also used but are not on the template because it contains the accent colors they need. The accent colors are yellow and maroon. Not bad. But the way the graphing program pulls the colors from the template makes the chart look like it's comprised of columns of mustard and ketchup. It is pulling in the accent colors and using them as primary colors. First of all the palette needs to be adjusted and, second, the broad use of gold and maroon needs to be limited and reserved only for accents. Pay attention to how your palette is being used. Don't let a bad situation persist just because it is a little time consuming to reformat the color in charts.

The Good, Bad, and The Ugly

The good charts are the best practice charts. When best-practice formatting is applied to your data-driven charts, you're increasing your audience's ability to understand your message and elevating their perception of your material, company, and you.

Best-practice formatting needs to be carried out in two ways: 1) on each individual chart to be sure that the variables are consistent with best practices; and 2) on the different chart types so that there is a consistency of look and application from page to page, from document to document, and from engagement to engagement. The chart formatting becomes part of your branding.

The bad charts are the default charts (or minimally formatted charts) that show up in otherwise great presentations. There is no excuse for this type of thoughtless display when the rest of the presentation evidences meticulous preparation. Also never sacrifice clarity for style choices. 3D effects are not a style choice if they confuse the audience with ambiguously plotted data.

The ugly charts are those that are technically correct, but fail to do the job correctly. Many of the best practices have been employed in the 4th Qtr Performance Update chart, but several things could have been done to make it more aesthetically pleasing: clip art is used to establish the design of the template (always a bad decision), the palette does not match the color scheme of the template nor do the colors complement each other, the use of the charting space is not optimal.

All three aspects of a presentation – style, message, and data – need to be in synch and adhere to established best practices before a presentation can be classified as great.

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