But focusing exclusively on big data and connected devices leads to an incomplete vision. The behaviors, insights and goals of people are crucial as well. After all, people are now part of the Internet of Things thanks to their smartphones, wearable technology and connected homes and cars. And more fundamentally, smarter cities, counties and states are ultimately about improving the lives of their residents.
In particular, ideas inspired by behavioral economics can bridge the gap that too often exists between digital technology and desired public outcomes. The data revolution coexists with the "behavioral nudge" revolution ushered in by the pioneering work of such researchers as Daniel Kahneman, Cass Sunstein, Richard Thaler and Amos Tversky. Predictive models based on big data can be used to flag issues most in need of attention, and behavioral insights can provide the tools for prompting the desired behavior change. Minor, often inexpensive tweaks to choice environments -- tactics known as "choice architecture" -- can yield outsized effects on people's actions.
While some criticize choice architecture as a form of manipulative social engineering, we see it as a thoughtful and innovative application of human-centered design thinking to help people better navigate challenging environments. And while emerging technologies hold the promise of vastly increasing the impact of choice culture, the power of the behavioral nudge all by itself has become firmly established.
Consider the case of Lake Shore Drive, once listed as one of Chicago's most dangerous stretches of road. To reduce the number of accidents near one curve, a decade ago the city painted a sequence of white lines on the pavement, each shorter than the previous one, on the approach to this hazard. The succession of shrinking lines gives drivers the illusion that they are speeding up, prompting them to slow down and take the curve at a safer speed. City traffic engineers reported 36 percent fewer crashes in the six months following the lines' introduction.
Philadelphia offers another example. Aiming to reduce delinquency in city tax payments -- in 2010, nearly 10 percent of city property taxes went unpaid -- Philadelphia has been rewriting the letters it sends to delinquent taxpayers, collaborating with academics and analyzing data to test different communications strategies. The city found, for example, that appealing to civic duty by citing specific public services that the property-tax revenues fund encouraged more people to pay up. The most significant impact of this tactic was on residents with relatively low levels of tax debt (up to $300).
New Mexico uses data-driven nudge communications to tackle a thorny problem: claimants improperly collecting unemployment insurance benefits due to inaccurate disclosure of earnings and other information. Officials at the New Mexico Department of Workforce Solutions recognized that most improper claims were the result of small slips, inaccuracies or misunderstandings -- not intentional efforts to defraud the system. So rather than taking the traditional (and expensive) approach of criminal enforcement, they employed a mix of data science and behavioral economics to nudge claimants toward more accurate disclosure.
Each week, claimants must certify that they are looking for work and document all earning. Most claimants do so through the department's website. When the system spots an answer that doesn't fit the usual pattern or range, it triggers a pop-up message emphasizing the importance of providing correct information. Administrators tested a dozen different messages, and because claimants must certify each week, New Mexico quickly learned which messages were most effective. In the year after the smarter system went live, improper payments fell by half and unrecovered overpayments were reduced by almost 75 percent, saving the state almost $7 million.
Clearly the nudge is a powerful tool on its own. Combining behavioral insights with the latest in digital technology and data science can take it to a new level, enabling smarter decisions by citizens, groups and the governments that serve them.
For more on this subject, see "Making Cities Smarter" in the January 2017 issue of Deloitte Review, or listen to this podcast.
