How can behavioural design thinking help improve uptake of your innovation?

This blog post was written by Solomon Tesfaye, Senior Programme Associate at R4D.

The Resilient Health Systems (RHS) theme of COVIDaction consists of awardees that harness the power of technology to improve health data and service delivery. The commonalities between awardees’ objectives and challenges allowed the team to put together a shared learning agenda that could be used to enhance coaching support across RHS. Following our first and second blogs in the RHS learning series, we now share what we found from exploring the second question in the RHS learning agenda: How do we determine the needs of an innovation’s target audience and increase the likelihood of uptake by end-users?

A resilient health system must be able to prepare for and effectively respond to crises. One of the most important dimensions of resilience, as we have come to learn throughout the COVID-19 pandemic, are the people on the ground who contribute to making the health system function day in and day out during extreme changes and shocks.

The work of the COVIDaction’s Resilient Health Systems (RHS) awardees support individuals working within the health system and the communities they care for by leveraging tech-enabled, innovative solutions that have the potential to contribute to the improvement of core attributes of health system resilience. In order for these solutions to work, potential users need to be willing and able to use the technology, and this doesn’t happen overnight. The COVIDaction team wanted to better support RHS awardees in understanding end-user needs and increasing engagement with their solutions, so we asked the following question: How do we determine the needs of the target audience and increase the likelihood of uptake of their technology by end-users?

More specifically, we looked into (1) effective approaches to targeting end-users to raise awareness and uptake of the innovations, (2) building capacity of partners who help deliver the innovation, (3) ways to obtain feedback from end-users, and (4) adapting the innovations to the local context. We employed key informant interviews with behavioural science experts from academia and non-governmental organizations as well as a scoping review of the literature to unpack these questions.

In exploring these research questions, we hoped to be able to speak to the best way to encourage behaviour change as it pertains to uptake of an innovation or new technology. Greater uptake of a technology is the key to unlocking the potential these technologies have to enable and that sustain resilience in the health system.

Here’s what we found…

Facilitating uptake of a technology by end-users requires a broad range of activities and approaches drawn from the fields of psychology, behavioural economics, sociology, and anthropology. Pulling components and approaches from several different fields of work allows us to create contextual and somewhat comprehensive explanations of human behaviour in response to innovation design. The aim of a behavioural approach is to identify potential bottlenecks in the local context and current mechanisms of service delivery, to hopefully inform design and increase how much a new technology is used.

Traditional approaches tend to focus on fixed or structural barriers, rather than the differing preferences of end-users — which is very context specific. If you want to understand how to get people to use an innovation, you have to figure out how they make decisions and act within their given locale and the complex circumstances they are working under.

*Adapted from Ideas42 (2015)

Using a behavioural approach to promoting uptake of a new technology follows a simple four-step process:

1. Understand & Define The Problem: Define the problem that you’re trying to optimise for clearly and concretely. Identify the target audience, or an identifiable actor whose behaviour you want to change, including their relevant behaviours, and the context they operate within (e.g., stock attendant, pharmacists, government stakeholders, etc.)
2. Diagnosis: Next, diagnose the bottlenecks that prevent target end-users from carrying out the desired behaviour. This is the part where we use behavioural science to uncover factors and develop hypotheses about which psychological and/or economic concepts may be a barrier for technological adoption of an innovation. Sometimes bottlenecks are tied to structural factors as well, and it’s important to account for this during the diagnosis and design stages.
3. Design: Once potential bottlenecks have been identified, this is where you think through solutions and design interventions that will help mitigate some of the key bottlenecks you’ve just identified in the previous step. These do not have to be big interventions. Simple, low-cost solutions like sending SMS reminders, for example, can work well.
4. Test: After you have designed some possible solutions, this is the stage where you test your hypothesis to find out whether the solution works. And if it did work, you might consider reiterating to address a different bottleneck.

It is important to note that iteration and adaptation is an implicit theme that runs throughout this process. Once you have a promising idea for a solution, and you go out to implement it in a real-world setting, you should draw lessons from the implementation process and re-define, re-diagnose, and re-design other potential interventions until you find the solution that yields the most optimal result. In reality, the “simple” four-step process looks more like this:

*Adapted from WDR (2015)

So what are some examples of bottlenecks…

There are many possible behavioural bottlenecks that may be contributing to the problem you have defined, and the target behaviour you are trying to change. We have identified three bottlenecks that often contribute to technology rejection.

1. Cognitive overload
   Many health-related innovations require the end-users to be engaged in understanding and incorporating new tools into their day-to-day practices and decision-making. When the end users are health workers, in addition to their current workload — whether they are managing resources, doing data collection, focusing on patient care, or all of the above. When the end users are members of the population, the innovation has to compete with all the demands and distractions of daily life. This can be cognitively taxing in the fast paced environment that we live in.
2. The power of inertia
   In general, people want to stick to current behaviours and habits, especially when it is cognitively easier to stay the course. When a new technological innovation is introduced — no matter at what level or whomever is involved — we tend to refuse to give up our current way of doing things, even when the benefits of adopting the innovation outweigh the costs.
3. Ambiguity aversion
   People have the tendency to favour the known over the unknown, so that when front-end or back-end tasks are ambiguous, people are more likely to reject or ignore a new technology or innovation.
   If end-users are having to estimate how long a new or unfamiliar task will take, or if they are unsure how the innovation will benefit them and the people they serve, then they will be less motivated to follow through with the desired behaviour.

The uptake assessment tool

To put this learning into practice, we developed an uptake assessment tool for awardees to use that walks through the first three stages of the behavioural approach. The assessment entails a series of questions that correspond to each aforementioned behavioural problem to help awardees identify which bottlenecks may be affecting uptake of their technology. For example, for cognitive overload, we ask innovators — using a psychometric 5-point Likert scale — how much they agree with the following question/statement: In terms of usage and implementation, are the steps that are required to use the innovation demanding on the end-users mental resources (i.e., does it require them to pay attention to details or dedicate lots of time to learn how to use it)?

After diagnosing which bottlenecks are at play, the assessment tool provides specific examples for how to address each bottleneck in the technology’s design and implementation. For cognitive overload, some examples include making instructions easier, sending SMS reminders, aligning the physical location of the innovation with end-users workstreams. The tool also contains a repository of best-practice research methods and customer segmentation tools to help identify demand and the needs of target users.

For technology-enabled innovations to impact resilience, the end user — whether a healthcare worker, a regular person, or a government decision maker — must use the innovation. behavioural tools we created will be used going forward to help us understand why people behave and choose the way they do, and how to inform those behaviours to create a more robust and sustainable health system.

We hope this post might be useful for you as well. What other behavioural bottlenecks do you think are key to innovation uptake?

To read more about findings from previous rapid learning cycles conducted by the same team, check out these two blogs: Rapid Research Cycle 1 and Rapid Research Cycle 2.