From Analytics to Action
An analytics interface may be visually appealing, but if it doesn't stimulate action, it's not going to be very effective. Good interfaces provide the context to let the user know when action might be required. Consider the treemap displayed in Figure 2, drawn from a health care organization that operates a number of hospitals. Each rectangle represents emergency room visits to one hospital; the larger the rectangle, the higher the number of ER visits. The color represents the number of visits relative to the forecasted number of ER visits. Red means the actual number of visits was higher than forecast, while green means the actual number of visits was lower than forecast. In both red and green cases, there is a problem with the forecasts.
Dont Automate Everything
Automatic clustering saves weeks of work, but it is not be important for the marketing manager to know the details. What he or she needs to know in order to figure out what to do next is the size of the outlier investments and returns. Surely, the manager could have inferred this with a spreadsheet and enough time, but this display communicates the findings at a glance. It is easy to see the number of outliers in each cluster, how the clusters relate to each other and the magnitude of the problem or opportunity.
Apply principles for good visual design. Displays of related information are horizontally and vertically aligned so the eye can see patterns across related variables (they do not have unintended alignments that suggest misleading or irrelevant comparisons). Color serves to highlight exceptions, not to enliven a dull dashboard. Analytic results are not presented to 10 decimal places when the user does not need such precision to make a decision. The displays have a high "data-ink" ratio, following Yale professor Edward Tufte's principles for designing statistical graphics. Good interfaces avoid 3-D effects or ornate gauge designs when simple numbers, charts and graphs will do.