With the growth in data and analytics, it is not uncommon to hear organizations talk about how focused they are on data-driven decision making. The premise behind this focus is that the quality of organizational decisions is improved if they are driven by data.
Those of us who are in the analytics profession, and for others who are in other business functions and believe in the power of data, here is a question to think about – is it possible to pursue data-driven decision making in our personal lives?
My interest in this subject was triggered by a blog by Stephen Wolfram and the book Better by Atul Gawande. Wolfram, who is the brain behind Mathematica and Wolfram Alpha, in his blog back in 2012 wrote about the insights he was able to draw from the data crunching he did on personal data that he had accumulated over 20+ years. Wolfram’s analysis of his emails, keystrokes, phone calls, meetings, events, and walking habits helped him draw very meaningful insights. He called out that storing personal data at the minimum provides the benefit of “memory augmentation” – the ability to recollect events, incidents, and actions from data archives as an extension of one’s own memory.
For the more analytically inclined, he was able to show that more meaningful insights could be drawn from personal data. For example, analyzing his email archive helped him realize that most issues at his workplace resolved themselves by the end of the day without his intervention. His intervention would only have resulted in wastage of his time.
Gawande, a surgeon in the US, recommends in his book that people could count something that is of interest to them. He counted (and recorded the data) on how often things were left inside patients after surgery. Things left inside patients included surgical instruments, sponges, etc. Analyzing the data showed Gawande that these incidents were more likely to occur during emergency situations (unexpected complications) in a surgery. This insight allowed him to be better prepared in such situations to avoid these mishaps.
The blog and the book only amplified my interest in the area of Personal Analytics that I had unwittingly gotten interested in many years ago. I had been collecting as much data as I could about my personal finance (bank statements, daily spends, etc.), my daily habits (eating/walking), and my work activities (emails and meetings) for many years. I have 15-20 years of hourly/daily data in some of these areas. The question is – how well have I used this data to draw meaningful insights? Trends in my financial data have helped me make better personal investment decisions.