Across the globe, all people — poor or rich — sometimes make choices that are not conducive to their own well-being. Saving enough for retirement, eating healthy, investing in education. All too often we humans postpone intended actions to tomorrow, succumb to inertia, or get stuck in habits.
In light of the extensive research on the cognitive biases that influence human decision-making, there is a broad consensus that traditional economic models are insufficient for effective policymaking. Behind every policy lie assumptions about how humans will behave in light of new regulations and why we act the way we do.
Behavioral insights draw from research findings from psychology and neuroscience. These insights about how people make decisions matter for development. They matter for policy-formulation and addressing last mile problems.
Nonetheless, behavioral insights are only being leveraged by a relatively small, but growing number of policymakers around the globe. Now, however, United Nations agencies and funds are catching up.
In Busia, Western Kenya, many smallholder farmers do not use fertilizer. Research shows that it significantly increases yields, so a standard policy might assume that farmers aware of these benefits would invest in fertilizer. Therefore, that program might seek to raise awareness among farmers while providing subsidies for the product. Here, insufficient awareness was not the problem. Farmers expressed their commitment to purchase and use fertilizer in interviews, but most did not translate intent into action. A behaviorally informed intervention reframed the problem. What barriers prevent farmers from taking action? How can we redesign the choice environment to help farmers act in accordance with their long-term goals?
In this case, the intervention entailed parallel experiments, designed based on what we know about factors that influence decision-making such as mental accounting and friction costs. Most farmers have cash readily available immediately after harvest, but not later in the year when it is time to buy fertilizer. The first experiment helped farmers set aside money in different mental accounts, by offering the option of purchasing vouchers for fertilizer at harvest time to solve mismatches in timing. The second experiment offered free delivery in order to remove friction costs — the extra costs associated with traveling to purchase fertilizer that represent a seemingly small barrier, yet deter action. The results of the randomized control trial showed that 14 percent of the farmers in the control group purchased and used fertilizer, compared to 36 percent in the treatment group that was offered vouchers and free delivery.
The farmers were successfully nudged to act in accordance with their long-term goals. Nudges change the choice architectures that surround us, while maintaining freedom of choice. An example of a nudge is placing healthy food at prominent places in school cantinas. Banning fast food in the same cantinas is not a nudge. Nudges are usually based on careful empirical testing, very often through randomized control trials. Good nudges have high benefits and low costs. In the U.K., simple changes to reminder letters on taxes resulted in approximately 210 million pounds of additional tax revenue. In Guatemala, the most successful variant of a reminder letter increased payments by 43 percent.
Applying behavioral insights and its rigorous monitoring and evaluation frameworks to achieving the Sustainable Development Goals has the potential to better address last mile problems. Many development challenges are not primarily policy-problems, but rather, implementation challenges.
Last mile problems in this context are the challenges created when users interact with policies and services. The term was coined from the early days of the telegraph. The new technology enabled words to travel much faster than by mail, but the telegraphed messages only reached the end of the telegraph line. They still had to be taken to their respective households — they had to go the last mile. In the context of public policy, last mile problems refer to the failure of adoption of government programs. For example, scientific innovations that can combat diarrhea and the distribution of the drugs are first mile problems, whereas the proper adoption and use of the drugs are examples of last mile challenges.
In Moldova, many adults treated for tuberculosis discontinue medical treatment. Relapses have significant impacts on the individual’s health and on the economy. To address this last mile problem, the U.N. Development Programme partnered with the U.K. Behavioral Insights Team and explored the behavioral barriers preventing medical adherence. We found that a major barrier was the mandatory regular visits to a clinic to take the drugs in the presence of a doctor. To test whether more patients would follow through if allowed to take medication at home while connected through their phone-cameras to a doctor or nurse, a randomized control trial was set up. Early results indicate a 20 percent increase in the treatment group as compared to the control group. An important premise of these experiments is: if you want to encourage people to do something, make it easy,
Another one is: let’s move from raising awareness to facilitating action.
In January 2016, the U.N. secretary-general appointed two behavioral insights advisors for initially six months. They worked with the UNDP Innovation Facility to improve uptake of an e-waste recycling solution in China, crowdfunding efforts for green energy in Ecuador, the anti-corruption initiative Phones Against Corruption in Papua New-Guinea, among others.
The initial results will soon be shared by the U.N. secretary-general’s office. The World Bank — as well as governments in Australia, Denmark, Germany, the Netherlands, Singapore, the United Kingdom and the United States — have all launched dedicated initiatives to leverage behavioral insights to address policy and last mile challenges. The work of these teams shows that approaching development challenges with behavioral insights leads to better diagnoses of problems and to better designed solutions. It is time to scale this approach across the SDG achievement efforts.
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