From theory to practice

The two-hour session introduced participants to the Applied Behavioural Science Field Guide: a flexible framework structured around seven steps, from initial scoping through to implementation and evaluation. While the full framework was presented, the workshop focused in depth on three stages where behavioural science adds the most value: Define, Diagnose, and Design.

Participants were guided through practical exercises to build confidence in applying each step. First, they explored how to define behaviours clearly using a simple but powerful structure, who does what, where, and when. Facilitators emphasised that effective programmes depend on specifying observable, measurable actions rather than abstract goals.

From there, the session moved into diagnosis, introducing the COM-B model (Capability, Opportunity, Motivation) as a way to understand why behaviours do or do not occur. This helped participants identify common pitfalls, particularly the risk of designing solutions without fully understanding underlying barriers.

Finally, participants applied these insights in the design phase, using the NEAR framework to develop interventions that make behaviours more normal, easy, attractive, and routine. This reinforced a key insight: effective behavioural solutions are often counterintuitive and require moving beyond awareness-raising toward more targeted, evidence-based approaches.

An important and distinctive feature of the workshop was the integration of AI augmentation guidance. Participants explored how tools like large language models can support behavioural work by generating hypotheses, structuring research, or suggesting intervention ideas, while also recognising their limitations. The session emphasised that AI outputs must be grounded in local knowledge and validated with real users, rather than taken at face value.

Outcomes and next steps

The workshop achieved several important outcomes. It introduced stakeholders to a practical, usable set of tools for applying behavioural science, built confidence in using those tools, and generated early feedback to inform further iteration of the Starter Pack. It also helped shift perceptions of behavioural science from a specialist add-on to a core component of effective innovation design.

More broadly, the session demonstrated how behavioural science can act as a catalyst for more rigorous, structured, and evidence-based approaches to innovation. By encouraging teams to define behaviours clearly, test assumptions, and iterate based on real-world feedback, it strengthens the overall quality and impact of programmes.

The February workshop also forms part of a wider engagement journey. It was complemented by additional sessions, including a full-day workshop and ongoing support to help teams integrate behavioural tools into their programme and funding lifecycles. As the Starter Pack is finalised and rolled out, these engagements will play a key role in embedding behavioural science across FCDO’s work.

Ultimately, this initiative represents a shift from recognising the value of behavioural science to operationalising it in practice. It equips stakeholders with accessible tools and practical guidance, supporting FCDO’s ambition to make behavioural science a core enabler of inclusive, sustainable innovation and improving development outcomes. The workshop concluded with a clear takeaway: you know your innovation – behavioural science helps ensure it works in the real world.