This blog is a documentation of a ted talk I watched by Hans Rosling. He is a Swedish physician. About some years ago he took on the task of teaching undergraduate students the subject of global development. He had spent 20 years in Africa studying hunger, so he knew quite a lot about the world.
He chose medical students for his classes and decided to teach them the subject of global health. He had a fear that the students might know the things he was going to teach, so he decided to conduct a test to know how much the students knew about global health.
He conducted a simple test based on child mortality where he grouped 2 countries with extreme differences between them in the child mortality rate, for example, Sri Lanka and Turkey were grouped together where turkey had twice the child mortality rate as Sri Lanka, and the students where are asked to choose between them.
To his surprise, only 1.8 out of 5 questions were answered correctly which was less than what a chimpanzee(2.5/5) would have scored if it was given to choose. He then tested the professors and they gave competition to chimpanzees with a score of 2.4.
What we can learn from here is that people do not have the data and they make decisions based on preconceived ideas. When the students were asked about what world they leave in, they answered the western world and the other being third world. The western world were the industrialists with longer life and smaller families and the third world were having shorter life and larger family. He then showed the graphical representation of this with the data from 1962. From the data, the claim made above makes sense but then he showed the data year by year. The so-called third world improves healthcare and decreased family size. He showed the movement of each country in the graph and almost all the country were same as the developed countries.
He takes the data of the USA and Vietnam and then points to the improvement of healthcare in spite of the war. In 2003 Vietnam was almost as same as the USA. He also shows the graph of the distribution of income between rich and poor, in the old data there was a significant difference between the rich and poor, and many countries were under the poverty line. As time passed the difference decreased and many countries came out of the poverty line.
He also talks about averages being dangerous. He showed the GDP vs child survival rate of South Africa as an average and then compared it with Nigeria and Uganda, the region of Nigeria with the best result was similar to the region of Uganda with the worst result, and the same for Uganda and South Africa as an average, where South Africa had better results compared to Uganda and Nigeria. The reason this is dangerous is that if we make reforms with the data of South Africa as an average, the reforms would be useless in Uganda and Nigeria. Therefore data should be analyzed deeply rather than relying on averages.
The learnings from the session are that we have to rely on data on making any marketing decision, we cannot do things on our preconceived ideas. We shouldn’t be focused on averages. We need to represent it graphically so that hypothesis can be made. Data changes over time so it should be checked regularly.