Week 3 - Dr. Rosling

 

Dr. Rosling’s lecture provided many valuable insights into the health and wealth of developing nations.  He was not trying to solve the problems of the developing world, but he illustrated how you could harness data to debunk myths and make informed decisions.  The dataset that I found the most interesting was the one regarding child survival and GDP per capita.  Rosling showed that there was a strong linearity between child survival and wealth.  This was not a surprise, but once he broke out the continents and regions of the world into individual plots on the graph it become more interesting.  Sub Saharan Africa was plotted very low on the graph (low GDP and child survival), but once you exploded the data you could see that there was more variability among the countries.  From this you could identify what countries have had more success than others.  Rosling then went down even deeper into the data to show how there was variability within the country depending on the GDP per capita of citizens.  I believe the point Rosling was making about this dataset was the need to drill deeper into the data.  Once you drill into the data you can ask better questions and possibly prescribe better solutions for what you are trying to solve.  The same thing can be applied in Marketing.  We can segment our markets into consumers with homogenous buying habits and target specific products to deliver value to them.  If we don’t segment and instead prescribe a one size fits all solution we will likely fall short of our ultimate goal.

I also enjoyed the visual presentation of Dr. Rosling’s data.  I think if you muted his dialogue, or couldn’t understand his accent, you would understand most of what was being presented.  The visuals clearly showed trends over time, especially the first dataset on family size and life expectancy.  Rosling was debunking a myth held by his students that said there are two distinct groups in the world: one with large families and short life expectancies, and the other with smaller families and longer life expectancies.  This was true in 1960, but as Rosling set the data in motion it became clear that third world countries are now also having smaller families and enjoying longer life expectancies.  Basically, the visual demonstrated the point much better than Rosling could have ever said it.  The dataset covering daily wages also benefitted from the visual illustration of the point Rosling was making.  The visuals also showed the clear relationship between variables, especially the child survival rates and GDP per capita. Rosling’s powerful visuals were able to take larges sets of data and wield them into a strong concise message.