Pictured above: This image refers to a recent experiment in Zambia explored how giving students soap-on-a-rope to take as an entry pass to the bathroom led to significant increases in handwashing behavior among the children. Photo credit: Shutterstock, By Tatsiana Hendzel

“The best-laid plans of mice and men / Go oft awry.” As development professionals, our challenge is to anticipate why projects might go wrong. To do that, we require more than sophisticated financial models or deep sectoral expertise. We also need to understand the context in which our projects play out, and the behavior of the institutions and individuals who will be affected. There are both risks here—and opportunities.

Fortunately, behavioral science provides us with tools to better understand human behavior. It offers insights and design principles that can be incorporated into existing programs, often at low cost, to increase program reach, effectiveness, and sustainability.

To illustrate some of the opportunities, a recent IEG report assembled examples of effective behavioral approaches from three sectoral domains: education, health, and social protection. We interviewed practitioners and reviewed hundreds of project documents, all while leveraging expertise within eMBeD (the World Bank’s behavioral unit) and IEG.

Some highlights of our findings:

  • Teacher absenteeism. In Peru, random spot checks conducted by the Ministry of Education suggest that on any given day, 9 percent of school directors were absent. This absenteeism is linked to decreases in pupils’ performance in mathematics and reading.[1]
    • Behaviorally-informed solution: As a response, the World Bank’s Mind, Behavior, and Development Unit tested the effect of sending school directors emails highlighting either the current level of attendance—the norm—or the positive effects of attendance on student performance. The norm message increased the presence of directors by 3.7 percentage points, suggesting behavioral emails could be a cost-effective way to affect directors’ performance.
  • Tobacco addiction. The WHO estimates that 30.1 percent of men in the Philippines smoke cigarettes daily.[2]
    • Behaviorally-informed solution: In the Philippines, smokers were offered a savings account (CARES) in which they deposited funds for six months; after which they take a urine test for nicotine and cotinine. If they pass, their money is returned; otherwise, their money is forfeited to charity. Of smokers offered this CARES program, those randomly offered CARES and voluntarily participated were three percentage points more likely to pass the six-month test than the control group. More importantly, this effect persisted in surprise tests at 12 months, indicating that CARES produced lasting smoking cessation.
  • An estimated 172 million people worldwide were unemployed in 2018.[3]
    • Behaviorally-informed solution: The complex task of identifying the right job opportunities can overwhelming. Moreover, without timely information available about opportunities, a job search can become costly and time-consuming. In Peru, job seekers were sent text messages about job opportunities. Compared with job seekers in the traditional programs who received information through normal channels, job seekers in Peru who received text messages were 17 percent more likely to have found work by the first month.[4]

Based on our review of these examples (and many others), we concluded that behavioral insights can help improve project design.

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First, behavioral insights can help to better diagnose the problem. We can shed light on potential “behavioral biases” (a systematic error in thinking that can lead an individual to make a less desirable choice); pre-existing mental models (someone's thought process about how something works in the real world); and underlying social norms. For instance, in India, 35–50 percent of low-income women report that the correct treatment for a child with diarrhea is to reduce fluid intake because their mental model attributes diarrhea to ingesting too much fluid.[5] This behavioral insight allows practitioners to understand the underlying problem causing poor health outcomes: a faulty mental model rather than, say, the undersupply of oral rehydration solution (ORS).

Second, behavioral insights can help to improve the design of the intervention itself. Continuing the illustration, practitioners would not just provide a oral rehydration solution (ORS), but couple its provision with easy, attractive, social, and timely (EAST)[6] action. For example, individuals with high social capital in the community could be trained to demonstrate the use of effective oral rehydration. In essence, by identifying the behavioral bottlenecks, the efficiency of an intervention can be increased in cost-effective ways.

Third, behavioral insights can improve the evaluation of the intervention. By looking at behavioral responses to projects, evaluators can better appreciate the real-world impact of their projects. This requires new approaches—looking beyond traditional metrics, to new indicators and more nuanced baselines. Evaluators should always be asking: “What indicators can be collected to measure people’s behavioral responses (or lack of them) to an intervention and the impact on outcomes?”

Read IEG's Report

Learn more about eMBeD

The report was written by Sana Rafiq under the guidance of Soniya Carvalho (Task Team Leader), Abigail Goodnow Dalton, Ann Elizabeth Flanagan, Varun Gauri, and Renos Vakis. Gaby Loibl assisted in preparing the paper. Overall direction was provided by Emanuela Di Gropello (former Manager, IEGHC) and Galina Sotirova (Manager, IEGHC). The paper was part of an IEG Learning Engagement with eMBeD as the operational cosponsor. Inputs from World Bank staff from the Poverty, Education, Health, and Social Protection global practices are gratefully acknowledged.



[1] World Bank, eMBeD project, 2018.

[2] WHO Report on the Global Tobacco Epidemic: Country Profile Philippines (2019), availlable at https://www.who.int/tobacco/surveillance/policy/country_profile/phl.pdf.

[3] International Labor Organization, 2017.

[4] Dammert, Ana, Galdo, Jose, and Vigilio Galdo. 2015. “Integrating Mobile Phone Technologies into Labor-Market Intermediation: A Multi-Treatment Experimental Design.” IZA discussion paper no. 9012.

[5] Datta, Saugato, and Sendhil Mullainathan. 2014. “Behavioral Design: A New Approach to Development Policy.” Review of Income and Wealth 60 (1): 7–35.

[6] Behavioral Insight Team, EAST Framework.