"The vertical silos of demography/finance/infra are good as a first cut, but a lot of the value and insights will come from metrics that cut across these verticals. I'm very curious about the spread of unit costs on education, infrastructure and other items.
A map embed in the reports would not go amiss.
Please ban all pie charts. You can easily replace all with bar graphs and have happier readers.
In general, I would say that reports of this nature provide two kinds of information: descriptive and analytical. Both are necessary. Right now, the reports are heavy on the descriptive and quite light on the analytical. It might not be a bad idea to separate the two, and list down the former in an easy table or something. Visualisation may not necessarily add value to the descriptive stats, but simply make them more "pretty".
This way, with the analytical information, you may have the luxury of going after the precise metric that favours analysis or comparison, and in the form that is most accessible. For example: if I want to look at the differences in gender enrollment, you can simply display the number of girls there are in school for every 1000 boys. The resulting number there of 9xx is something that is easily comparable to other 9xx figures in everyone's minds."
"The vertical silos of demography/finance/infra are good as a first cut, but a lot of the value and insights will come from metrics that cut across these verticals. I'm very curious about the spread of unit costs on education, infrastructure and other items. A map embed in the reports would not go amiss. Please ban all pie charts. You can easily replace all with bar graphs and have happier readers. In general, I would say that reports of this nature provide two kinds of information: descriptive and analytical. Both are necessary. Right now, the reports are heavy on the descriptive and quite light on the analytical. It might not be a bad idea to separate the two, and list down the former in an easy table or something. Visualisation may not necessarily add value to the descriptive stats, but simply make them more "pretty". This way, with the analytical information, you may have the luxury of going after the precise metric that favours analysis or comparison, and in the form that is most accessible. For example: if I want to look at the differences in gender enrollment, you can simply display the number of girls there are in school for every 1000 boys. The resulting number there of 9xx is something that is easily comparable to other 9xx figures in everyone's minds."