Better Decisions in Less Time with Bigger Data and Smaller Egos

In their book Decisive: How to Make Better Choices in Life and Work, Chip and Dan Heath described a decision-making process they called multitracking—considering several options simultaneously. The Heaths argued that if we consider more options, even if we ultimately choose not to opt for any of them, we will make better decisions.

As an example, they recounted a study of graphic designers working on a banner ad for a web magazine. The designers were randomly assigned to use one of two creative processes. Half of them were instructed to design one ad at a time, receiving feedback after each new design. The other half were instructed to start with three ads and received feedback on all three. As it turned out, process mattered a great deal. The simultaneous designers’ ads were judged superior by the magazine’s editors and earned higher click-through rates in a real-world test. Interestingly, over 80% of the simultaneous designers said the feedback they received during the process was helpful. By contrast, 65% of the one-at-a-time designers took the feedback as personal criticism.

The study concluded the one-at-a-time designers began to take their work too personally, explaining that with only one design, the designer’s ego was conflated with the design. Multiple designs, however, separated each design from the designer’s ego, making them open to feedback as opposed to defensive of perceived criticism.

With the increasing demand for timely decisions, many business leaders may understandably fear that exploring more options will add too much time to the decision-making process. To that point, the Heaths shared a study of top leadership teams in Silicon Valley that found executives who weighed more options actually made faster decisions. The study cited three reasons why:

  1. Comparing alternatives helps executives understand the landscape of the decision (i.e., what’s possible, what’s not, and what variables are involved), which provides the confidence needed to make a quick decision.
  2. Considering multiple alternatives undercuts politics and keeps egos under control, since with more options people get less invested in any one of them, freeing them up to change positions as they learn more about the decision.
  3. When business leaders weigh multiple options, they have given themselves a built-in fallback plan, allowing them to make a decision without delay in the event their first choice is rejected or proved not actionable.

One of the lauded benefits of big data analytics is being able to weigh more options in our decision-making process. The more we can automate the processing and presentation of more decision-making options, the less we have to deal with any of those options becoming conflated with the ego of an individual decision-maker. Big data analytics, therefore, can enable businesses of all sizes to make better decisions in less time with bigger data and smaller egos.


This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies, or opinions.


Related Posts

Data is a Game Changer

Governing Big Data

Capitalizing on Big Data Analytics

Big Data is not just for Big Businesses

A Big Data Platform for Midsize Businesses

Smart Big Data Adoption for Midsize Businesses

Business Analytics for Midsize Businesses

Big Data Lessons from Orbitz

The Graystone Effects of Big Data

Sentiment and Sensibility

Will Big Data be Blinded by Data Science?

Talking Business about the Weather

Parmesan, Parkas, and Predictive Analytics

Driving a Data-Driven Connected Car

i blog of Data glad and big

The Need for Data Philosophers

HoardaBytes and the Big Data Lebowski

Magic Elephants, Data Psychics, and Invisible Gorillas

Exercise Better Data Management

A Tale of Two Datas