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:

  1. 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.
    small data cover Cover image courtesy of St. Martin’s Press LLC
  2. 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.
  3. 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.
  4. 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.
  5. 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.