Can my Excel Demographic Dashboard be recreated in Crystal XCelsius? This is the main theme for this series of posts. In the first post I set the stage, define the rules and show how the basic “demographic KPI’s” can be displayed using gauges. The second post discusses one of the major drawbacks I find in XCelsius and similar applications: the use of textures and the consequences of it.
Back to the dashboard, I am trying to recreate the population pyramid that you can find in the Excel version. Please take a look at the Excel pyramid (above) and the one I designed in XCelsius (below):
I don’t want to discuss features and options, only the end result, but let me summarize the process:
- There seems to be no easy way in XCelsius to connect data points in a scatter plot and I didn’t like the chart without them, so I had to rule out the scatter plot;
- There is no option to align series in a bar chart, so it can’t be used to create a pyramid; the option is available for the stacked bar chart, but in this case you can’t display four series without stacking them (obviously);
- This is a minor issue: the x-axis labels can’t be formatted to remove the minus sign but, as long as the scale doesn’t change, you can hide it with a small white rectangle.
My final solution uses a stacked bar chart to encode the current year and a subtle overlapping scatter plot to encode the reference year (1996). I could also minimize spacing between data points by using a smaller chart or by interpolating data points. I chose this one because it retains the nature of the tool (namely the texture in the bars). Feel free to send me other alternatives!
The XCelsius pyramid looks a little better than the bare bones Excel version, but spotting the differences between the reference and the current year is harder.
So, what are the learnings? Judging from this task, in XCelsius you are confined to a very small set of charts that you are unable to format the way you’d like. This is not necessarily bad. It depends on your audience, your data, what and how you want to show.
So, my advice would be: if there are no trade-offs (are you sure?), if what/how you want to say can be said in Xcelsius without significant perceptual impact, and your audience likes it, by all means, use it. But try to be very conservative in your formatting options (minimizing the impact of textures, for example), otherwise those eye-catching charts can wear out very fast.
That said, I believe that you can’t avoid trade-offs and that, by using Xcelsius, you can lose some relevant details in your data. But this is not over. Let’s see if Xcelsius proves me wrong. The next post discusses scatter plots.