Five Reasons Why Big Data Isn’t Enough
March 26, 2016, 3:30 PM UTC
AT&T’s Global Network Operations Center provides 24/7 monitoring of 9 million network elements in real time
The GNOC processes approximately 1 billion calls, 2.5 billion text messages and 107 petabytes of data daily
Photographed by Peter Nguyen — AT&T
Here are 5 reasons why Big Data no longer can stand alone, and why the future is likely to always include Small Data:
- Big Data analyzes the past – and thus is rarely able to predict the future. Small Data explores untouched terrain – and thus is better able to discern and predict new trends.
Cover image courtesy of St. Martin’s Press LLC
- Big Data is rarely able to factor in the fact that 75% of everything humans do is irrational – and thus tends to produce an overly rational picture of the consumer. Small Data accounts for and explores our irrational (and human) mind.
- Big Data requires enormous investments that rarely pay off immediately. Twenty or 30 of what I call “subtext interviews” are enough to paint an accurate picture of the consumer.
- Big Data rarely allows space for creativity and exploration of “out of the box” thinking. Small Data is all about creativity and out-of-the-box thinking.
- Big Data steers us away from innovation because many companies are mining the same set of data. Small Data always will see the world from a unique and differentiated point of view.
This article is adapted from the New York Times bestseller Small Data: The Tiny Clues That Uncover Huge Trends by Martin Lindstrom. Copyright (c) 2016 by the author and reprinted by permission of St. Martin’s Press, LLC.
