How to go about visualizing a single KPI – Part 3

Links for Part 1 and Part 2 entries.

In previous representation styles, the single value KPI was represented as-is and against itself. Continuing with the discussion on different presentation techniques, this post outlines few more styles to be looked at.

Style #4: Trends and Time Series

Trend based representations are associated with time series data, as a matter of fact both are in separable and go in tandem. The only dimension against the KPI is time. Since time always progresses in linear fashion, the best method of visualization is through line cBlog_SingleKPI_5harts. As an additional feature the maximum, minimum, beginning and ending values can be shown along the different points for effectively communicating to the user. The second chart on right can be adopted when  a trend of actual and benchmark values have to be plotted. Gaps between the lines will explicitly indicate the differences and intersection points will indicate deviations.

Another common method for showing trends is through column charts. In terms of evaluating a single KPI value, the column chart and line chart are at par in terms of the amount of information communicated to the user using visualBlog_SingleKPI_6 cues. When the KPI is evaluated against a benchmark, the column representation scores slightly higher against line chart.

Style #5: Spreads

This style is visualization is applicable whenever a single non time based dimension is used for evaluating the KPI. Options are a plenty for this style of visualization and the most common are Bar charts, Pie charts, Heat Maps, Box Plots etc.

Box plots are an ideal way to show the spread within the KPI itself with information such are central point, outliers, IQR etc. This is typically used by analysts and power users rather than average users on day to day basis.

Pie chart and its variants such as doughnut chart, heat map, radial chart show the spread amongst the dimension set. The Blog_SingleKPI_7total size is 100% and individual sectors will add up to the total. Although the data is presented in absolute numbers, users tend to interpret the percentage values first when these style of charts are used. It is good to remember that an implicit unwritten interpretation happens for these chart types.

Bar charts on the other hand eliminates the implicit percentage conversion and shows the data as-is. Sorted bar charts are better at showing ranking among the dimension set rather than a pie chart from visual interpretation point of view.

There might be scenarios where other visualization methods such as a line chart or column chart might provide a better visual effect in terms of user interpretation or overall look and feel. One has to look at the underlying data and experiment with few options before finalizing the best fit.