Analytics – Verb: a thought process to discover, interpret and communicate information hidden within a situation or event.
Knowingly or unknowingly, Analytics function as a basis of all the things that work around us, and all of us are the recipients of the benefits of analytics at every moment and everywhere.
“War is ninety percent information.” – Napoleon Bonaparte
Analytics is not a new craft that was born out of the evolution of computers. It was born out of the basic human instinct of survival and urge to win. Analytics was used to hunt, to fight, to win wars and to trade. The techniques and tools used were primitive, however; even today the thought process remains relevant and universal.
Analytics, as it stands today, helps us in deciding which movie to watch at what time, what accessories suit our lifestyle, which books we should be reading, which candidate we should choose as the next Prime Minister or President of our country and even who could possibly be our soulmate!
In this blog, I would try to walk you through the mystic world of analytics – and you do not need to be a scientist to understand it. All you need is a bucket full of common sense.
Five SENSES of Analytics
- Question: This is the ‘Why’ behind the ‘Buy’. It is very similar to looking down at a crystal ball and asking the question for which you seek the answer.
- Data: Collecting, assimilating and structuring the available data.
- Constraints and Assumptions: Equally important in identifying the nuances of the situation and its data. “Facts do not cease to exist because they are ignored” – Aldous Huxley
- Model: A technical term involving selection of appropriate techniques to format the data. When applied to new data or records, it predicts the outcome based on the available information.
- Application: Actual validation to respond to the questions asked in the first place.
Now that you know the basics, let us consider a real-life example of the use of analytics.
A very popular dating site was founded by a group of mathematicians who believed that match-making is possible by crunching data and less by emotional connect.
It works primarily at two levels:
- First, by asking the users to answer predefined questions. (Question)
- Second, the users decide the relevance of each question. (Constraints & Assumptions)
Thus, creating a data set (Data) based on which people are matched (Model), by measuring if the question was important to both people, as well as how they answer it (Application). However, this is just the tip of the iceberg in the field of analytics.
The addition of socio-economic and behavioral data to the above multiplies the chances of a perfect match and new results emerge. Accumulation of such results over a period of time improves the quality of future match results.
Advancement in computing capabilities and thanks to our great mathematicians, today we have very sophisticated tools & techniques to analyze and make better fact-based decisions, fueling our basic instinct of survival and winning. In years to come, the term ‘intuition’ may not refer to a human feeling anymore.
Related Topics & Credits:
‘2017: Advanced analytics enter the real world’ – by Zubin Dowlas, https://thestack.com/big-data/2017/01/19/2017-advanced-analytics-enter-the-real-world/
‘The Dark Side of Customer Analytics’ – by Thomas H. Davenport and Jeanne Harris, https://hbr.org/2007/05/the-dark-side-of-customer-analytics