We can learn a lot across domains. A close look at how medicine has evolved tells us a
story. When we are ill these days, it is an automatic response to call a doctor or go to a
pharmacy to fetch medicines. Just about 200-300 years back, this did not exist. We have
reached far ahead in medicine now, thanks to getting to the bottom of the causation, with
the discovery of ‘Cell Theory’ by Robert Hooke. It is the advances in microscope
technology in the 19th century helped scientists observe live cells and we reached a
tipping point of modern medicine.
We are at a similar tipping point of discovering and finding ways to cure and prevent
challenges which have been there in the fashion industry for decades.
Dwelling further in the area of forecasting, itself, reveals another story. It is Philip Tetlock
who did decades of research on forecasting ability of experts and came with the theory
that many experts forecasts were as close to chance as throwing a dart by the common.
That is not to say there are no expert forecasters. They are a very few and he studied in
detail what made those Super Forecasters perform superior to many others.
Since Tetlock’s enlightening interview in 2015, technology in deep learning has advanced
significantly and also the ability of machines to predict. We still believe best outcomes in
forecasting will happen through:
1. Improving the ability of the human to forecast better; and
2. Humans using inputs through technology, collaborating to update the forecasts constantly and validating the forecasts with machinegeerated ones.