One problem with overlapping plots here is that it doesn't convey that we are dealing with parts of a whole. Both the stacked area chart and stacked column chart naturally relate the growth of one component to the shrinking of another.
Relative comparison between slices of the stacked area or column chart is a difficult cognitive function, however, and is imprecise. I'd have to disagree with the article's author on the value of the stacked bar chart, as, while the step changes are more discrete, point-to-point comparison is still encumbered. The even more un-sexy clustered bar chart is yet more appropriate.
A solution, when the designer needs or wants to reflect total volume of that whole, is to underlay the lines (in this case) with an area plot representing the total volume over the same time interval. In this way, the two pieces of information (individual performance and total size) are encoded in distinct and easily understandable ways.
This pattern is good only when you effectively compare 2 variables; you easily see that when one shrinks, other grows, and when does it happen. When you have more variables, it automatically becomes too complex.
Comments
One problem with overlapping plots here is that it doesn't convey that we are dealing with parts of a whole. Both the stacked area chart and stacked column chart naturally relate the growth of one component to the shrinking of another.
Relative comparison between slices of the stacked area or column chart is a difficult cognitive function, however, and is imprecise. I'd have to disagree with the article's author on the value of the stacked bar chart, as, while the step changes are more discrete, point-to-point comparison is still encumbered. The even more un-sexy clustered bar chart is yet more appropriate.
A solution, when the designer needs or wants to reflect total volume of that whole, is to underlay the lines (in this case) with an area plot representing the total volume over the same time interval. In this way, the two pieces of information (individual performance and total size) are encoded in distinct and easily understandable ways.
This pattern is good only when you effectively compare 2 variables; you easily see that when one shrinks, other grows, and when does it happen. When you have more variables, it automatically becomes too complex.