Microsoft Office Tutorials and References
In Depth Information
Key Questions to Ask Before Distributing Your Dashboard
Use colors to identify the ranges in your data model. Using colors in your data model
enables you to quickly look at a range of cells and get a basic indication of what that range
does. Each color can represent a range type. For example, yellow could represent staging
tables, gray could represent formulas, and purple could represent reference tables.
In Chapter 2, we introduce you to data models and building a data model map.
Cross-Ref
Is my dashboard user-friendly?
Before you distribute your dashboard, you want to ensure that it’s user-friendly. It’s not difficult to
guess what user-friendly means.
Intuitive: Your dashboard should be intuitive to someone who has never seen it. Test it out
on someone and ask her if it makes sense. If you have to start explaining what the dashboard
says, something is wrong. Does the dashboard need more labels, less-complicated charts, a
better layout, more data, less data? It’s a good idea to get feedback from several users.
Easy to navigate: If your dashboard is dynamic, allowing for interactivity with macros or
pivot tables, then you want to make sure that the navigation works well. Do users have to
click several places to get to their data? Is the number of drill-downs appropriate? Does it
take too long to switch from one view to another? Again, you’ll want to test your dashboard
on several users. And be sure to test any interactive dashboard features on several
computers other than yours.
Prints properly: Nothing is more annoying than printing a dashboard only to find that the
person who created the dashboard didn’t take the time to ensure that it prints correctly. Be
sure you set the print options on your Excel files so that your dashboards print properly.
Is my dashboard accurate?
Nothing kills a dashboard or report faster than the perception that the data in it is inaccurate. It’s not
within my capabilities to tell you how to determine whether your data is accurate. I can, however,
highlight three factors that establish the perception that a dashboard is accurate.
Consistency with authoritative sources: It’s obvious that if your data doesn’t match other
reporting sources, you’ll have a data credibility issue — especially if those other sources
are deemed to be the authoritative sources. Be sure you are aware of the data sources
that are considered to be gospel in your organization. If your dashboard contains data
associated with an authoritative source, compare your data with that source to ensure
consistency.
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