JULY 20189him realize that most issues at his workplace resolved themselves by the end of day without his interven-tion. His intervention would only have resulted in wastage of his time.Gawande, a surgeon in the US, recommends in his book that peo-ple could count something that is of interest to them. He counted (and recorded the data) on how of-ten things were left inside patients after surgery. Things left inside patients included surgical instru-ments, sponges, etc. Analyzing the data showed Gawande that these incidents were more likely to occur during emergency situations (unex-pected 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 am-plified my interest in the area of Per-sonal 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), my daily habits (eating, walking) and my work activities (emails, meetings) for many years. I have between 15 to 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; my work related data has helped me become more productive at work by allowing me to plan meet-ings, events and other commitments suitably; I only wish I had applied insights that I have learnt from my eating and walking behaviours over the years.Reviewing this data archive re-cently led me back to Wolfram's blog which then led me to realize that Personal Analytics is an emerging technology trend as recognized by Gartner in 2016. Personal Analytics is a field of analytics which focuses on allowing people to collect, mea-sure, analyze and improve using data about themselves. With the perva-sive presence of technology in our lives, it is increasingly becoming easy for people to collect and analyze data about themselves. The movement behind this emerging phenomenon is called Quantified Self with the belief that collecting and analyzing one's personal data could help one improve one's health, wealth, so-cial life, family relationships, work productivity, personal productivity and more.Just as Gartner's Analytics Matu-rity Model (Descriptive, Diagnostic, Predictive, Prescriptive) applies to business analytics, it is quite possi-ble in the near future that we will be able apply the same model to Per-sonal Analytics. Imagine a personal dashboard (Descriptive) refreshed every day, week, year that helps you understand the impact of your be-haviour and your actions on your health, wealth, social life and other aspects of your life. Imagine then a visual application that allows you to deep dive (Diagnostic) into the dash-board to help you understand why your savings dipped over the past year or why your weight went up over the last month and so on. What if you could have automated person-al agents (bots) that review your data and provide you alerts (Predictive) to manage your social relationships("you will miss your daughter's school performance if you don't get off work now") and better still, pro-vide meaningful insights (Prescrip-tive) to meet your health, wealth or other personal goals.If your interest has been piqued with the possibilities of Personal Analytics, here are starter solutions that can help you get started:1. Wolfram Alpha (the brain child of Stephen Wolfram) provides a Face-book App to draw insights from your social network ­ some of the insights you can get are about where your friends are clustered geographical-ly, what do you talk about often on Facebook, when do you use Facebook and more 2. If you know R, then you can use data from your chat tool (Whatsapp, Snapchat, WeChat) or your bank statements or your work archives to analyze and draw insights about your personal, professional and financial behavior; here is where you can get started - https://www.wired.com/insights/2013/11/love-life-and-r-personal-analytics-gets-real/ With technology getting increas-ingly embedded in our lives through wearable's and the availability of analytical tools, apps and models to mine data from these wearable's, it is quite likely that Personal Analyt-ics will be a technology phenome-non in the next 5-10 years. If you are interested in getting a head start, you can begin by collecting data and using simple analytical tools to ana-lyze and draw insights from the data. Here is to a better you because of Personal Analytics! With the pervasive presence of technology in our lives, it is increasingly becoming easy for people to collect and analyze data about themselves
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