7 Ways to Maximize the Value Data Visualization in Dashboards

Allison Allison 2013_11_26

Allison R. Allison is a consultant with Leidos Health and is associated with the HIMSS Clinical & Business Intelligence Data and Analytics Task Force. Allison is currently assisting hospitals in gathering requirements for analytical dashboards and ICD-10 remediation efforts. Her interest in visual design of dashboards was sparked through these dashboard developments. Allison received a Master’s Degree in Epidemiology from Michigan State University.                

Dashboards are a popular way to get information out to members of an organization.  According to Stephen Few, a leading user interface dashboard expert, “(a) dashboard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance" (Few, Stephen. “Information Dashboard Design.” 2nd Ed. Analytics Press (Burlingame, CA), 2013. At 26).  So, what does this mean?

A dashboard brings together the information that an end user needs to understand and monitor what is going on in the business.  For example, a quality dashboard might include a scorecard that describes how the quality metrics are performing against goals, a chart that trends metrics over time, and a list dimensions (e.g., physician, location, service) by which the metrics can be stratified. 

Dashboards are popular because they provide useful information quickly and efficiently.  Unfortunately, sometimes a dashboard’s design thwarts the end user from acting on the information provided.  Sticking to the rules below will help ensure that the dashboard provides the clearest message possible. 

Color is a great way to communication information to an end user.  However, if used improperly it can distract the user from the important information on a dashboard.  A good idea is to start a dashboard with muted background colors like white or grey.  Then add color and color intensity to draw the users’ attention to what is important, such as metrics that are not meeting goals or whose trends going in the wrong direction.  Color can also be used to relate information within a dashboard. For example, every time you see a blue bar on a graphic it represents a specific metric and a red bar represents another metric.   

The amount of space utilized by a metric should be proportional to the importance of that metric.  Important metrics might have detailed drills or break outs since the end users may require more detailed information to get the answers needed. 

According to Few, a dashboard should be limited to a single screen.  If a dashboard user has to scroll there is a possibility of missing information because the metrics at the bottom of the page will not be assessed as often. Additionally, scrolling a dashboard may mean that users have to remember numbers from the top part of the dashboard to compare them to the bottom part of the dashboard.  This can be problematic given that most people cannot easily remember more than 5 numbers.


Not all the screen’s real estate is equally valuable.  As shown in Figure 1, people tend to scan a screen from top left (most valuable – bright green) to bottom right (least valuable - grey), with center of the screen also being a focal point.  When laying out a dashboard take advantage of this by placing important metrics and charts in areas that naturally get more attention from a user’s eyes. 

Dashboard Visualization Figure 1_2013_11_26.png                    

 Figure 1: The associated value assigned to a single screen space

Make sure that the graphics you use convey the intended message.  The bars on the two charts illustrated in Figure 2 each represent the same values (30, 25 and 35).  However, the graphical display for the chart on the right has been configured incorrectly because a visual interpretation makes it appear that the outer bars are double and triple the middle bar.

  Dashboard Visualization Figure 2.jpg                     

  Figure 2: The differences between displaying the Y-axis at zero versus a midpoint.


Providing metrics without context can leave the dashboard user asking “so what?”  For example, in Figure 3 the graphic on the left shows that a 30-day hospital readmission rate in December of 18% for patients with chronic obstructive pulmonary disease (COPD). It is an interesting metric but it does not do much to inform the dashboard user.  Context informs the dashboard user with information such as:

  • Is the trend improving over time?
  • How does the rate compare to the goal, target or threshold?
  • How does the rate compare to industry averages or benchmarks?
  • What is the rate of improvement or degradation? 


A much better version of the graph that includes context is shown on the right side of Figure 3.

Dashboard Visualization Figure 3.jpg

   Figure 3: Provide context so that user have the information to draw useful conclusions.                    



The last major point is to keep the design as simple as possible.  There is a tendency to create overly complicated dashboards that contain odometers, gauges, stoplights and complex graphs that chart too many variables.  Do not decorate your dashboards with these unless there is a clear purpose and avoid using detailed precision unless it is truly necessary.  Including extraneous and meaningless items on a dashboard makes it harder for the user to find, understand and compare the metrics of interest. 

Following the steps outlined above will help to display those messages in a clear and easy to understand format.  

dashboard, visualization, value data