In partnership with 60 Decibels and the Bill and Melinda Gates Foundation, Busara conducted behavior change research with five digital farmer service (DFS) providers. This research included identifying the barriers to adopting the digital services offered by our partners and designing and testing solutions to overcome these barriers.
Behavior change research integrates behavioral science and human-centered design to develop effective, user-centered solutions. Behavioral science examines why and how people make decisions, helping us identify key factors influencing DFS adoption, such as beliefs, preferences, and perceived value. By applying these principles, we gain a holistic understanding of the drivers and barriers to adoption.
Human-centered design is a problem-solving approach that places the target population (i.e., the intended users of these services) at the core of the design and development process. Through co-design workshops, researchers, partners, and the target population collaboratively create solutions. This approach ensures solutions are practical, user-friendly, and aligned with real-world challenges.
We rolled out the behavior change research in three phases: 1) identify the challenge, 2) co-design solutions to overcome the challenge, and 3) test if the solutions change behavior. Each phase builds off the insights from the previous phase.
Phase 1: IDENTIFY the Challenge
This phase focuses on uncovering the underlying barriers to adoption. To begin, we identified the specific adoption-related behavior we wanted to change. Examples include encouraging extension agents to use digital data collection tools, motivating farmers to act on digital advisory information, and improving engagement between farmers and digitally-equipped extension agents.
Then, we analyzed the different factors that inhibit the target population from following through on this behavior. Under the DIG-it-AL project, we conducted interviews with farmers, extension agents, and other relevant groups to understand their experiences and perspectives on adopting and using our partners’ digital services.
Phase 2: CO-DESIGN Solutions to Overcome the Challenge
After identifying a few key barriers, we organized co-design workshops with farmers, extension agents, and other relevant groups to co-create solutions to overcome these barriers. We mobilized participants to a central location and conducted a series of activities to build empathy with the target population and brainstorm solutions around their challenges. These activities included empathy mapping, posing “how might we” questions, story completion, and “1-2-4-All.”
Phase 3: TEST if the Solutions Change Behavior
We turned the most promising ideas from the co-design workshops into prototypes and tested whether they changed the behavior of the target population. This phase began by defining an “outcome measure,” or a quantifiable metric to capture adoption behavior. For example, if our goal is to encourage extension agents to use digital data collection tools, then an appropriate outcome measure would be the number of extension agents using digital data collection tools.
We implemented the prototyped solutions with a select sample of the target population and compared outcome measures between this sample and a sample that did not receive the solution (i.e., the control group). A control group helps isolate the solution’s impact by showing what would have happened without it, ensuring that any changes are due to the solution itself rather than external factors. In other words, having a control group allows us to say with a degree of certainty that the solution is effectively changing the behavior of the target population.
In Phase 1, look beyond infrastructure challenges like poor internet access and consider behavioral factors such as capacity, perceived value, and mistrust, which can have just as much impact on whether farmers adopt the service. This blog post explores these barriers in more detail.
In Phase 2, tailor brainstorming activities to your target population. Co-design workshops often use “how might we” questions to reframe problems as questions, helping participants generate solutions. However, if open-ended brainstorming might feel intimidating to the target population, story completion exercises can offer a more structured and comfortable way to share ideas.
It may be tempting to end behavior change research after Phase 2 once prototypes are developed. However, we strongly recommend testing them on a small scale to ensure they deliver the intended results. In the DIG-it-AL project, several promising prototypes fell short of expectations during testing. For more details, see this blog.
Don’t get discouraged if your solutions don’t work, and continue iterating on your ideas. Even well-designed solutions may not work as expected, requiring further investigation and refinement to better address barriers, improve implementation, and ensure lasting behavior change.
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