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Editorial: Behavioral insights – Putting Humans in the loop

by Jim Guszcza, Mark Cotteleer
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    25 January 2016

    Editorial: Behavioral insights – Putting Humans in the loop Deloitte Review Issue 18

    26 January 2016
    • Jim Guszcza United States
    • Mark Cotteleer United States
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    As the march of “smart” technologies seemingly takes on a life of its own, it is worth remembering that advances in the behavioral sciences can better enable the human-centric design of programs, technologies, and organizations.

    JIM_GUSZCZA

    Big data, automation, digital economies, the Internet of Things: Technological advances continue to reshape business and societal landscapes alike. Amidst the excitement is concern: Are people in charge of technology? Or is technology making the rules?

    Mark Cotteleer

    It is therefore helpful to remember that another signature issue of our time has human nature at its core. This is the explosion of psychological and behavioral insights arising from the work of Daniel Kahneman and others. Concepts of modern psychology and behavioral economics have made their way into strategic business and public policy discussions as well as everyday conversation. More recently, they have begun to offer tools enabling us to better shape programs, policies, and products—and ultimately to design our technological future—in a human-centric spirit.

    A major discovery is that when making judgments and decisions, the human mind tends to rely on a collection of mental shortcuts (“heuristics”) that are systematically biased, often in surprising ways. We overgeneralize from personal experience, favor narratively coherent stories over logically coherent analyses, conflate familiarity with likely truth, and are generally overconfident in our judgments. The implications for economic, regulatory, and management theory are far-reaching.

    For example, behavioral economics teaches that, contrary to what the Efficient Market Hypothesis predicts, financial markets often misprice assets. Markets for talent can be even less efficient: Over a decade after Moneyball popularized analytics, most hiring decisions are still heavily influenced by unstructured interviews that reinforce cognitive biases. And many organizations are reluctant to run experiments to scientifically evaluate the effectiveness of management decisions. Though experimentation and data science offer the means to drive better decisions and economic performance, it takes time, effort, and strong leadership to move from intuitive to evidence-based decisions.

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    Deloitte Review, issue 18

    An equally far-reaching set of implications follows from psychological insights about the rich variety of environmental, social, and ethical factors—beyond economic incentives—that predictably influence human behavior. We can prompt better decisions by designing choice environments to go with, rather than against, the grain of human psychology.

    For example, employees are more likely to save for retirement if they are automatically enrolled in a savings program and allowed to opt out than if the default were reversed. People will eat better if their choices are arranged with human psychology in mind. Innovation and superior performance can be achieved by tapping into employees’ intrinsic motivation to excel on the job, and classical economic incentives can actually “crowd out” powerful intrinsic motivations. Analogously, citizens and customers can be “nudged” away from opportunistically fraudulent behavior by tapping into their intrinsic motivation to be honest actors. Programs based on cognitive behavioral therapy principles help injured workers to return to work sooner and keep at-risk youth out of gangs and in school. Varied as they are, these examples hardly scratch the surface of what is possible.

    As the march of “smart” technologies seemingly takes on a life of its own, it is worth remembering that advances in the behavioral sciences can better enable the human-centric design of programs, technologies, and organizations.

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    Written by: Jim Guszcza, Mark Cotteleer

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    Deloitte Review , Analytics

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    Jim Guszcza

    Jim Guszcza

    Jim Guszcza is Deloitte’s US chief data scientist and a leader in Deloitte’s Research & Insights group. One of Deloitte’s pioneering data scientists, Guszcza has 20 years of experience building and designing analytical solutions in a variety of public- and private-sector domains. In recent years, he has spearheaded Deloitte’s use of behavioral nudge tactics to more effectively act on algorithmic indications and prompt behavior change. Guszcza is a former professor at the University of Wisconsin-Madison business school, and holds a PhD in the Philosophy of Science from The University of Chicago. He is a fellow of the Casualty Actuarial Society and recently served on its board of directors.

    • jguszcza@deloitte.com
    Mark Cotteleer

    Mark Cotteleer

    Managing Director | Center for Integrated Research

    Mark is a managing director in Deloitte Consulting LLP’s Supply Chain and Network Operations practice with a specialization in Digital Supply Networks and Industry 4.0. He has 25 years of consulting experience leading teams in technology-enabled reengineering, supply chain strategy, business analytics, and process design. Mark’s experience with clients includes manufacturing, supply chain, business analytics, healthcare, and service industries. 

    • mcotteleer@deloitte.com
    • +1 414 977 2359

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