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or Region. Again, if you don’t account for a particular filter while building your dashboarding process, you’ll likely be forced into an unpleasant redesign of both your data collection processes and your dashboard.

      If you’re confused by the difference between dimensions and filters, think about a simple Excel table. A dimension is like a column of data (such as a column containing employee names) in an Excel table. A filter, then, is the mechanism that allows you to narrow your table to show only the data for a particular employee. For example, if you apply Excel’s AutoFilter to the Employee column, you are building a filter mechanism into your table.

      Determine the need for drill-down features

      Many dashboards provide drill-down features that allow users to “drill” into the details of a specific measure. You want to get a clear understanding of the types of drill-downs your users have in mind.

      To most users, drill-down feature means the ability to get a raw data table supporting the measures shown on the dashboard. Although getting raw data isn’t always practical or possible, discussing these requests will, at minimum, allow you to talk to your users about additional reporting, links to other data sources, and other solutions that may help them get the data they need.

      Establish the refresh schedule

      A refresh schedule refers to the schedule by which a dashboard is updated to show the latest information available. Because you’re the one responsible for building and maintaining the dashboard, you should have a say in the refresh schedules — your manager may not know what it takes to refresh the dashboard in question.

      While you’re determining the refresh schedule, keep in mind the refresh rates of the different data sources whose measures you need to get. You can’t refresh your dashboard any faster than your data sources. Also, negotiate enough development time to build macros that aid in automation of redundant and time-consuming refresh tasks.

A Quick Look at Dashboard Design Principles

      When collecting user requirements for your dashboarding project, there’s a heavy focus on the data aspects of the dashboard: the types of data needed, the dimensions of data required, the data sources to be used, and so on. This is a good thing — without solid data processes, your dashboards won’t be effective or maintainable. That being said, here’s another aspect to your dashboarding project that calls for the same fervor in preparation: the design aspect.

      Excel users live in a world of numbers and tables, not visualization and design. Your typical Excel analysts have no background in visual design and are often left to rely on their own visual instincts to design their dashboards. As a result, most Excel-based dashboards have little thought given to effective visual design, often resulting in overly cluttered and ineffective user interfaces.

The good news is that dashboarding has been around for such a long time that there’s a vast knowledge base of prescribed visualization and dashboard design principles. Many of these principles seem like common sense; even so, these are concepts that Excel users don’t often find themselves thinking about. Because this chapter is about getting into the dashboard state of mind, I break that trend and review a few dashboard design principles that improve the look and feel of your Excel dashboards.

      

Many of the concepts in this section come from the work of Stephen Few, a visualization expert and the author of several books and articles on dashboard design principles. This book is primarily focused on the technical aspects of building reporting components in Excel, but this section offers a high-level look at dashboard design. If you find that you’re captivated by the subject, feel free to visit Stephen Few’s website at www.perceptualedge.com.

      Rule number 1: Keep it simple

      Dashboard design expert Stephen Few has the mantra, “Simplify, simplify, simplify.” The basic idea is that dashboards cluttered with too many measures or too much eye candy can dilute the significant information you’re trying to present. How many times has someone told you that your reports look “busy”? In essence, this complaint means that too much is going on in the page or screen, making it hard to see the actual data.

      Here are a few actions you can take to ensure simpler and more effective dashboard designs.

      Don’t turn your dashboard into a data repository

      Admit it. You include as much information in a report as possible, primarily to avoid being asked for additional information. We all do it. But in the dashboard state of mind, you have to fight the urge to force every piece of data available onto your dashboards.

      Overwhelming users with too much data can cause them to lose sight of the primary goal of the dashboard and focus on inconsequential data. The measures used on a dashboard should support the initial purpose of that dashboard. Avoid the urge to fill white space for the sake of symmetry and appearances. Don’t include nice-to-know data just because the data is available. If the data doesn’t support the core purpose of the dashboard, leave it out.

      Avoid the fancy formatting

      The key to communicating effectively with your dashboards is to present your data as simply as possible. There’s no need to wrap it in eye candy to make it more interesting. It’s okay to have a dashboard with little to no color or formatting. You’ll find that the lack of fancy formatting only serves to call attention to the actual data. Focus on the data and not the shiny happy graphics. Here are a few guidelines:

       Avoid using colors or background fills to partition your dashboards. Colors, in general, should be used sparingly, reserved for providing information about key data points. For example, assigning the colors red, yellow, and green to measures traditionally indicates performance level. Adding these colors to other sections of your dashboard only serves to distract your audience.

       De-emphasize borders, backgrounds, and other elements that define dashboard areas. Try to use the natural white space between components to partition the dashboard. If borders are necessary, format them to hues lighter than the ones you’ve used for your data. Light grays are typically ideal for borders. The idea is to indicate sections without distracting from the information displayed.

       Avoid applying fancy effects such as gradients, pattern fills, shadows, glows, soft edges, and other formatting. Excel makes it easy to apply effects that make everything look shiny, glittery, and generally happy. Although these formatting features make for great marketing tools, they don’t do your reporting mechanisms any favors.

       Don’t try to enhance your dashboards with clip art or pictures. They not only do nothing to further data presentation, but they also often just look tacky.

      Limit each dashboard to one printable page

      Dashboards, in general, should provide at-a-glance views into key measures relevant to particular objectives or business processes. This implies that all the data is immediately viewable on the one page. Although including all your data on one page isn’t always the easiest thing to do, there’s much benefit to being able to see everything on one page or screen. You can compare sections more easily, you can process cause-and-effect relationships more effectively, and you rely less on short-term memory. When a user has to scroll left, right, or down, these benefits are diminished. Furthermore, users tend to believe that when information is placed out of normal view (in areas that require scrolling), it’s somehow less important.

But what if you can’t fit all the data on one sheet? First, review the measures on

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