Data Viz Done Right

March 5, 2018

Makeover Monday: How good are policymakers at estimating indicators related to girls and women?

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God I hate survey data, especially survey data where the responses are so poor compared to the actual that they make it look like the data is wrong. I really, really struggled this week coming up with anything I found interesting.

I ended up skimming through parts of the main report to get a better idea as to what the survey is about and any interesting findings they might describe.

In the end, there were major themes:

  1. Policymakers are really out of touch with the issues facing girls and women in the five countries in the study. 
  2. Policymakers "think" they know what's going on.

Really, it's quite a sad situation. When policymakers are so far disconnected from the truth yet think they are close, I suspect not enough action is taken. I guess that's politics.

It took me a good 15 minutes to comprehend what the original chart was even about. Apparently it shows how far policymakers' estimates are from the actual indicators.

What works well?

  • The bands for +/- 20% from the actuals helps give context to the estimates from policymakers.
  • The country titles and subtitles for the topic make is easy to know what each chart is about.

What could be improved?

  • What do the green diamonds mean? Apparently they are policymaker estimates, but there's no indication of that in the dashboard.
  • Why are these topics picked for these countries?
  • Why is Senegal excluded?
  • A more impactful and descriptive title would help.
  • It's unnecessary to include the source and legend with each chart.

My Goals

  • Try to understand the data; easier said than done
  • Understand the spread of each topic within each country
  • Show ALL responses
  • Allow the user to filter and drill in to the topic they are interested in.
  • Stick to the overall style guidelines from Equal Measures 2030
  • Include BANs for the number of policymakers that estimated within +/- 20% of the actual values

I don't love my final dashboard, but after working on it for far too long, I figured it was "good enough". It could probably use an explanation somewhere for how to read the charts.

Click on the image for the interactive version.

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