Behavioural Insights and "Moneyball"

25 February 2015Antonia Kendall

Categorybig data

We really enjoyed reading Jim Guszcza's most recent article on the relationship between behavioural insights and data analytics, featured in Issue 16 of the Deloitte review. Jim presented an early iteration of this paper at BX2014, and has kindly given us an overview of the article.

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We really enjoyed reading Jim Guszcza's most recent article on the relationship between behavioural insights and data analytics, featured in Issue 16 of the Deloitte review. Jim presented an early iteration of this paper at BX2014, and has kindly given us an overview of the article.

 

"The Last Mile Problem: How Data Science and Behavioural Science can work together" by James Guszcza, Chief Data Scientist US at Deloitte Consulting

 

Judgments and decisions are at the heart of two of the biggest intellectual trends of our time – “nudging” and “moneyball”. “Playing Moneyball” is the use of big data to enable more economically efficient decisions in business, health care, and public policy. Behavioral “nudging” denotes the clever use of behavioral insights to prompt people to act in ways that are consistent with their long-term goals. Yet these methods are typically discussed in isolation – and at first blush might seem to have little in common.

In fact, business analytics and the behavioral insights movement can be viewed as complements. Predictive models are excellent tools for identifying the riskiest workplaces, the most persuadable voters, the students at highest risk of dropping out, the health insureds most likely to develop chronic diseases. They can result in tremendous efficiencies by pointing the field worker to the cases in most need of attention. But no predictive model yields value unless its indications are appropriately acted upon. Models point field workers in the right direction, but do not suggest how best to prompt the desired behavior change. The science of behavioral nudges provides the tools to solve this “last mile problem”.

There is an emerging consensus that behavioral nudges should be part of policymakers’ toolkits. This essay goes further and argues that behavioral nudges should be part of the toolkit of mainstream business analytics as well. Conversely, behavioral nudges can be more effectively customized and delivered using data-enriched, digitally implemented, strategies. Data analytics and behavioral nudges can and should be viewed as two complementary parts of a greater whole.