Sophisticated data models won’t do us much good unless decision-makers are able to interpret, understand and act on the results appropriately. Here are seven principles for designing analytic apps that lead to high user acceptance and results, from our team of consultants.
Understand What Users Will Do With The Results
Analytic interfaces should be driven by an understanding of what users will do with the results. Frame the discussion on uses around role-based design, with sensory cues directing action on only the most critical pieces of information. Role-based design of interfaces is important to match analytic needs to support the different type of decisions people may need to make throughout the organisaton. While scores of workers from management to the contact centre might benefit from access to analytics, different interfaces may be required to serve different job roles.
Remember less is always more. Good analytics interfaces show the information most critical to the user – not every piece of information that might be available for analysis. Sensory cues direct attention. Good interfaces exploit people’s abilities to perceive patterns based on position, size, shape, color and movement. These properties highlight important features that might otherwise be lost in a table of numbers.
Let Users Lead
Start from user needs and work backward to design the interface that supports those needs, ultimately to the analytics that will drive that interface. Even when users can’t specify in advance what they really want, it’s critical to involve them early and often as analytic interfaces are designed. Sometimes users may not be able to define it, but they’ll know it when they see it. Users are even better gauges for bad interfaces – if enough users believe an interface is unsatisfactory, you’re well-advised to accept their judgment.
If you are contemplating giving users the ability to set analytics modeling parameters, determine if they want to set those parameters and that they know how to do so or at least give them default values. Users can help identify early wins the designer may not have thought of and might provide useful introductions to other potential users and their communities. A user who feels a sense of ownership in interface design can become an advocate for the technology respected by other users. Users of different abilities may point out accessibility considerations, such as how and when color is used so colour-blind users get the same information from the intensity of the display.
A Picture is Worth a Thousand Numbers
Because of our human ability to understand relationships quickly based on size, position and other spatial attributes, the eye can summarise what might otherwise require thousands of numbers to convey.
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. Analytic dashboards alert users to potential performance issues and provide actionable information. Good interfaces provide context to interpret results that suggest what the user might do next and provide mechanisms such as clickthrough to facilitate an explanation and further analysis.
Apply Design Principles
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). Colour serves to highlight exceptions, not to brighten up a dull dashboard. Analytic results are not presented to 10 decimal places when the user does not need such precision to make a decision. Good interfaces avoid 3-D effects or ornate gauge designs when simple numbers, charts and graphs will do.
