Rather, their breakthrough ideas came from seemingly insignificant behavioral observations they’d made while interacting with friends, family members, colleagues, or strangers.
The most successful ideas and innovations originate from data observation, not from well-planned brainstorming sessions, despite mainstream notion.
Some years ago, I noticed something interesting. When I asked innovators, company founders, and entrepreneurs about the breakthrough ideas that led to their killer brands, they didn’t tell me, as I might have expected, that their great ideas had emerged from a well-planned brainstorming session or as the result of years of hard work in the lab. Rather, their breakthrough ideas came from seemingly insignificant behavioral observations they’d made while interacting with friends, family members, colleagues, or strangers. These key observations often occurred when least expected, revealing an unmet and previously unrecognized consumer need. These were the observations that became the foundation for entirely new, breakthrough brands.
It was a surprising, thought-provoking insight. After all, who would have thought that SnapChat, the social media app that allows the user to create photos with an ultra-short lifespan, was invented when the founder’s friend tried desperately to find a message containing a photo of himself smoking pot? Or who would have imagined that a priest dropping a Bible on the ground and spilling all his bookmarks would lead to the invention of Post-it Notes? Or that a failed insurance claim on a broken surfboard would lead to the invention of GoPro?
In our data-obsessed world, we’ve been convinced that billions of data observations drive innovation. However, if you peel the historic onion, you’ll discover that the key to innovation is often a coincidental observation.
Only a couple of years ago, you wouldn’t be able to attend a conference without hearing “Big Data” mentioned over and over again, nor could you have attended a board meeting at which Big Data didn’t dominate the agenda. Everyone was intrigued by the notion that a black box of data could magically produce deep insight into humans’ deepest needs, thereby revealing billion-dollar innovation opportunities. Like a kid in a candy store, every CEO proclaimed, “I want one of those!”
The term “Big Data” was supposedly coined by John Mashey in the mid-1990s over a lunch-table conversation at Silicon Graphics. Since then, experts have proclaimed Big Data to be some sort of ultimate crystal ball, a window into the consumer’s mind; but in recent years, many perceptive industry experts have began to conclude that the picture is incomplete. Big Data has its value, but something is missing. What’s needed, so to speak, is a counterbalance to Big Data.
The missing piece in the puzzle, I’ve discovered, is tiny — and though it may be tiny, the potential impact of “Small Data” is huge. I’m talking about first-hand observations made in consumers’ homes, in restaurants, in night clubs, in sports clubs, when driving or on the phone. These seemingly insignificant, seemingly irrelvant observations, once connected, have the potential to identify the vital causation that Big Data has, so far, seemed to be lacking.
You could say where Big Data is all about seeking a correlation, while Small Data is all about seeking the causation. Small Data is the key to turning Big Data into the success story everyone has been wanting.
Srikanth Velamakanni, co-founder of Fractal Analytics, one of the world’s leading data-mining companies once said: “I cannot count the number of businesses that have asked us for a Big Data solution without really knowing what they are looking for – they’re seeking the correlation without knowing the causation – the Small Data”.
I tend to say that true creativity happens when one combines two ordinary things in a new way. In many ways, this is the essence of both Small Data and Big Data. There’s probably nothing as powerful as combining creativity with structured thinking. The most exciting thing is that we’ve just begun this amazing journey.
So next time you hear the term “Big Data,” think “Small Data,” too.
DISCLAIMER: This article expresses my own ideas and opinions. Any information I have shared are from sources that I believe to be reliable and accurate. I did not receive any financial compensation in writing this post, nor do I own any shares in any company I’ve mentioned. I encourage any reader to do their own diligent research first before making any investment decisions.