Many human services programs are designed such that individuals must make active decisions and go through a series of steps in order to benefit from them, from deciding which programs to apply for, to completing forms, attending meetings, showing proof of eligibility, and arranging travel and childcare.
Program designers often implicitly assume that individuals will carefully consider options and make decisions that maximize their well-being. But research in the area of behavioural economics has shown that human decision-making is often imperfect and imprecise. People procrastinate, get overwhelmed by choices, and miss important details. As a result, both programs and participants may not always achieve the goals they set for themselves. In addition to all these challenges related to getting started, they must keep showing up for training or employment no matter their personal challenges or motivation levels.
Insights from behavioural economics, which combines findings from psychology and economics, suggest that a deeper understanding of decision-making and behaviour could improve human services program design and outcomes. Principles from behavioural economics can both shed light on decision-making and offer new tools to improve outcomes for program participants. For example, small changes in the environment can facilitate desired behaviours, planning and commitment devices can be used to improve self-control, and default rules can produce positive outcomes even for people who fail to act.
These small changes have come to be known as “nudges” which Thaler & Sunstein define as any aspect of the choice architecture that alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives…Putting fruit at eye level counts as a nudge. Banning junk food does not.
Can they be used in youth employment programs?
In recent years, behavioural economics and specifically nudges have moved from research into policy design across a wide range of areas including adult education, workforce development, and job retention. In many countries, there is an interest in leveraging cost-effective nudges to gently push children, adolescents, parents and teachers towards better education decisions and greater educational attainment. In the United Kingdom (UK) the Behavioral Insights Team has developed a helpful tool called the “EAST framework,” which states simply: if you want to encourage a behaviour, make it Easy, Attractive, Social and Timely (EAST).
This framework combined with defining the outcome, understanding the context, building the intervention, and then testing, learning and adapting, has been used in the UK to successfully improve several programs and services across the country. Similarly, the U.S. Office of Planning, Research and Evaluation sponsored the Behavioral Interventions to Advance Self-Sufficiency (BIAS) project which uses a behavioural economics lens to examine programs that serve low-income families.
Exploring nudges: Behavioral diagnosis and design
Our process begins by following an agile, yet systematic approach called behavioural diagnosis. The process consists of identifying major pain points, establishing that these issues, if successfully addressed will be significantly impactful, and then sanity checking that these can realistically be addressed with nudges. Simply stated, we ask three questions; What’s the problem? Does it matter? Can we fix it?
Getting started- We follow the lean methodology of build-measure-learn where the goal is to build a simple intervention, measure its performance, and learn what worked and what didn’t. This cycle is repeated until the desired results are achieved. The methodology, when well executed, accelerates the process of trial and error, which in our experience is a critical factor in arriving at a working solution, especially in a sector where each improvement connects to improving people’s lives.
If this is the first time a team is experimenting with nudges, it’s helpful to familiarize them with the basic principles of behavioural economics and how these principles can be used to influence behaviour.
Case Study: WAVE
Introduction to WAVE
WAVE (West Africa Vocational Education) is a Nigeria-based social impact enterprise that addresses widespread youth unemployment in West Africa by training underserved but self-motivated youth with industry-relevant work skills and crucial employability skills. WAVE operates a four-phase model which begins by screening applicants, followed by job training and placement, and continues with alumni support.
What’s the problem?
WAVE identified four areas where nudges could potentially improve outcomes, these were course completion, employer engagement, alumni engagement, and job self-placement. For the pilot, we selected course completion (of their training program) as the targeted outcome. This was selected for several reasons. Firstly, course completion is a major outcome which, if improved, enhances the economics of training, since more people make it through given fixed costs; secondly, completing training impacts job seekers vis-à-vis employability; and lastly, because course completion is strongly influenced by motivation which is fertile ground for nudges.
Does it matter?
In establishing whether nudges are relevant or not, it’s important to frame the issue through the lens of a sensitivity analysis to determine if the issue being tested is a significant driver of the undesirable behaviour presented. This entails unpacking the major causes of a specific phenomenon. Which in our case is drop-out, and then to rank these causes in order of magnitude. This initial process is required to establish whether it’s worthwhile to allocate resources to improve the problem. In cases where the factor being addressed is a major cause then it’s worth proceeding further in the process. Despite the common-sense nature of this step in the process, it’s helpful to filter out solutions which even if successful would not move the needle.
Can we fix it?
There are many causes for student drop-out in short vocational courses. In situations where motivational factors are a common cause of drop-out, nudges can be very effective. Other common causes for drop-out such as family medical emergencies, inability to pay for transport, the need to drop out to earn income, etc. are beyond the capabilities of light-touch interventions like nudges.
For this experiment we applied the following four behavioural economics principles; (1) commitment, in the form of a Certificate of Graduation serving as a commitment device, (2) the endowment effect, the higher value placed on these certificates which they now own, (3) loss aversion, the fear of losing their certificate, and (4) goal framing, motivating students by framing losing of the certificate as a penalty and not a reward.
WAVE students participate in a three-week vocational training course with an average of forty students per cohort. The average completion rate for the course is 72%. WAVE experimented with a commitment device in the form of a Certificate of Graduation which was to be “awarded” to students on their first day of training. The certificate would then be “taken away” and the students would be informed that, upon successful completion of the course, they would have “their” certificates returned. The goal of the experiment was to test whether this had any impact on course completion rates.
Following the build-measure-learn method, the simple intervention was launched with the very next cohort. The results were humbling, zero impact. To extract learnings from this failure the team investigated further, and it emerged that the certificates were issued three-days late and without much fanfare. After the first experiment, it was unclear whether the problem was with the experimental design or implementation. To answer this question, it would need to be repeated. In the second experiment, WAVE implemented the experiment as designed. We tracked the performance like a high-stakes sports game. After the first week of training, the completion rates were promising at 98% compared to 80% for the control group. The result was an unprecedented 89% course completion rate- a solid 24% improvement.
Following the initial experiments WAVE learned two major lessons about nudges, firstly, execution matters and secondly, they were onto something which could make a real difference. It was decided to run the experiment on a few more cohorts to establish replicability. Over the next 12 months, WAVE repeated the experiment 5 times. The results have exceeded expectations with completion rates increasing between 5–35% per cohort, with an average increase of 19%- all these gains came at practically no additional cost. To frame this in terms of added value and impact on people’s lives, the experiment led to 34 more people completing the training and 27 of them likely getting employed.
Where to from here?
Following the success of the loss aversion experiment, WAVE is testing scalability by piloting it in other locations. The Umsizi Fund is supporting several similar nudge experiments in the field with WAVE and other demand-driven skills trainers. Active experiments include; increasing job retention rates in entry-level jobs in the MENA region, increasing English language levels for employment in Rwanda, and increasing incomes for unemployed youth and connecting them to jobs through life skills training programs in Nigeria.
The purpose of such experiments is not to find a silver bullet for tough social challenges. Nudges are contextually dependent and may or may not be replicable across diverse population groups. However, the goal of this work is to spotlight a useful tool and agile process to identify potential tweaks in engagement models, which, if successful, can improve organizational effectiveness. Which in the social context means measurably and significantly improving people’s lives. We encourage others to tinker with the status quo.