Upcoming webinar on 'Inforiver Charts : The fastest way to deliver stories in Power BI', Aug 29th , Monday, 10.30 AM CST. Register Now
Upcoming webinar on 'Inforiver Charts : The fastest way to deliver stories in Power BI', Aug 29th , Monday, 10.30 AM CST. Register Now
Bullet charts are a powerful tool that pack large amounts of information into a small area. They are primarily used to provide context to a numerical measure by comparing it to an expected value, and against a qualitative scale. However, this density of information can sometimes make bullet charts difficult to understand. Follow these guidelines to make clear charts that avoid common mistakes and help your reader make the correct interpretation. For an overview on the basics of bullet charts and the types that you can use in your report, click here.
Consider the two charts below. Both charts present the same information, with the only difference being the starting point of the vertical axis. Notice how the relative proportions look completely different in the chart on the right, where the y-axis starts at 50. For example, Metric B is not approximately twice the value of Metric C, as we see in the chart on the right. In fact, their values are much closer to each other, as shown in the full picture on the left. This occurs because we estimate the value of bars based on their heights, and truncating the bars leads to a misrepresentation of information.
It may not always make sense to start the y-axis at zero, and in these cases, it is best not to use bars to denote the performance measure. Instead, we may use a marker like the “X” marker below, where the reader relies solely on the position of the marker to read values. This allows us to zoom in on large values that are still relatively close to each other, as seen in the image below. The achievement of a target does not form the prominent “T” shape as in the classic bullet chart, and we lose the obvious visual cue provided by this, but the values of both the comparative and performance measures are clearly visible.
Color can be a useful tool to draw attention to a specific chart, or a specific aspect of the chart. We can only draw the eye to a section if it stands out against the rest of the chart using a pop of color. Using too much color draws the eye in all directions, defeating the purpose.
Instead, use different intensities of the same hue, along with a legend showing what each intensity represents, as seen below.
As discussed earlier, bullet charts that use markers for the performance measure lack the visually prominent intersection with the target marker to indicate overachievement. To make the overachievement or underachievement clear, we may use markers colored in green and red as shown below.
Use hues that provide sufficient contrast between the comparison bands and performance bar to demarcate them clearly. At the same time, it is also important to have sufficient contrast between the qualitative bands themselves to be able to estimate their lengths correctly.
Limit the number of comparison bands to a maximum of five. When using intensities of the same hue, this allows sufficient contrast between bands to distinguish them from each other, and to clearly see the performance bar against the darker bands, as seen below. This also prevents us from having a visually overwhelming chart, especially when using different colors for each qualitative range.
For example, consider the chart below which has seven qualitative bands. Notice how difficult it is to see the value of the performance measure or the target marker and to see where the comparison bands begin and end, especially towards the darker end of the spectrum.
Traffic-light colors (red, yellow and green) are often used to denote bad, satisfactory, and good in the qualitative bands, as shown in the image below. These colors form a familiar scheme for value judgements, but can be a barrier for colorblind readers who cannot distinguish between red and green. This is a significant problem as 1 in 12 men and 1 in 200 women are colorblind.
Limit the use of too much color as noted above, but in cases where it is necessary to use color, consider using a colorblind-friendly scheme, like the orange and blue palette used below.
Not all targets must be met. Sometimes, we have targets such as costs or number of defects that represent a maximum limit that should not be exceeded. For example, the first chart below shows us the number of defects per 1000 items manufactured and sets target numbers that should not be exceeded for each factory. In these cases, we may reverse the qualitative scale as shown, since fewer defects are a better outcome. This chart adopts the convention where lighter values represent better outcomes. In the case of expenses, as in the vertical bullet chart on the right, we may use a bar extending from zero towards the negative values as expenses represent funds that are lost to the company. This is another case where we may reverse the order of the comparison bands, as lower expenses are more desirable.
A bullet chart can help us compare several measures such as actuals, forecasts, targets, or previous year values simultaneously. We may add a second comparative measure using a marker like an ellipse or a triangle as shown below. This chart compares current year values with the target, shown as a line marker, as well as the values from the previous year, shown as a triangular marker.
We may normalize the target marker to support presentation of KPIs with varying magnitudes or multiple units of measure. Normalizing the target markers sets them at the same level regardless of the exact value of the target. The rest of the bar is then scaled according to the value of the target marker. This enables quick understanding and comparisons between metrics that fall short of or exceed the target.
Consider using highlight colors in red and green as shown below (or in a colorblind-friendly palette) to allow readers to quickly distinguish between negative and positive variance values. Dashboards with many bullet charts can be visually busy and slow to scan, and adding strategic color in this way allows the reader to quickly process this information across measures on the board. The chart below also uses a thinner bar to encode the variance, allowing for more visual space.
- By Hamsini Sukumar
