If you are over a certain age, you probably remember using cameras containing film. Because of cost you would take a limited number of photos and send the film off to be developed. When the packet of photos came back, you carefully selected the best and placed them in the family album.
Fast forward to the modern day and we now take hundreds of pictures, keeping most of them stored on our phones and in the cloud. For example google photos enables unlimited photo storage.
We have changed our approach from filtering on the way in (selecting a few photos for the album) to storing everything and filtering on the way out (store thousands in google photos and search with a simple query). There are many other examples of storing large volumes of data and filtering on the way out, such as our searching of emails or journey planning on our mobiles.
This new approach helps us drive innovation, particularly in our use of data. However, we need to avoid constraining our thinking by applying assumptions and rules on the data we use, rather than looking with an open mind at what the data is telling us.
A recent example for me may help make this real. Working with a data science team, we were exploring how to transform the detection of fraudulent insurance claims. Although things were improving it wasn’t significant until we changed our approach to the problem and the data.
Analysing all the data again provided great metrics on certain customers we could be 99%+ confident were making a genuine claim. This allowed us to transform their experience by fast tracking these customers through the claims process and allowing our claims teams to focus on the more borderline claims. It was only by removing the narrow focus on detecting fraud that yielded the benefit!
I’d love to hear your thoughts on how you avoid constrained thinking and please share any real world examples you have come across!