In 2022 we decided to restructure the way we were doing R&D at Stby. We wanted a clearer framework to boost our internal knowledge and make sure R&D directly impacted our client projects and proposals.
Since then, we’ve completed 28 internal R&D projects, allocating about 90 days per year to R&D across our two studios in the UK and Netherlands. We’ve learned a ton about managing the process and measuring how much our team’s collective knowledge grows. These projects have been an important way for us to keep pioneering our practices as the tech and social environment changes, and to deepen our explorations across our existing service portfolio.
As Lead of R&D at Stby, I observed three key learnings along this journey that make R&D work for us:
1. Keeping R&D closely tied to client projects
We found that having two types of R&D projects—one part of a client project and one standalone—gives us the flexibility to balance short-term and long-term impact.
When R&D is part of a client project, we can target our efforts to directly impact client deliverables while we’re working on them. Any team member can propose R&D. We define a clear scope for the objectives and anticipate what impact it can possibly have on the client deliverables within the timeframe.
While R&D projects outside client work usually do not serve a particular client directly, we are always on the lookout to use these projects as foundational learning that leads to new clients and new partners or as examples for new project proposals.
2. Creating Conditions for Sharing and Transferring Knowledge
We learned pretty early on that working in teams of 2-3 people is the sweet spot. It means learning isn’t isolated to one person, but our team is still small enough to be agile as we explore new knowledge territories.
As we plan R&D projects, we schedule moments of sharing with the team for wider learning across the company; but we also make sure to bring different combinations of team members together for R&D. Therefore, learning from one project can pollinate to another quickly by hands-on collaboration with different colleagues in designing and running R&D experiments together.
The aim of R&D is clear, to create learning for the entire company. Therefore, these moments of collective learning have to be clearly defined at the beginning to ensure they deliver their promises.
3. Building Topic Clusters and Series
Our four R&D themes (see below) are aligned to our service offering, meaning the effort and resources we put into R&D are in line with our expertise and pioneering practices.
However, as time goes by, we see clusters of R&D ideas accumulating around specific topics or sub-theme within the R&D themes. Last year, we intentionally started nurturing R&D projects as a series within a cluster, so every new effort could build on the last. We quickly saw the compounding impact of one project on another, which then created a great ripple effect on our client offering and PR activities such as conference presenting and podcast creation.
In 2025, 9 out of the 16 R&D projects we completed were developed within the AI R&D series. On the basis of these projects, we made direct impacts on three different client projects by using AI to generate new forms of deliverables, speeding up data analysis and writing processes, and using AI as part of the experiments within workshops with internal stakeholders from the client organisation.
Reflecting on these three years, the most significant takeaway is simple: a thoughtful R&D structure truly works for a small pioneering agency like ours. Our progress centers on three core commitments: tightly connecting R&D to client work, creating clear moments for team-wide sharing, and intentionally building expertise through our topic series.
This dedication is essential as we navigate a fast-changing environment in service design and social innovation. It ensures we stay agile, pioneer our practices, and always bring the most valuable, cutting-edge learnings to our clients and partners.
Curious about the immediate impact of our AI R&D series? Explore our latest podcast on AI-focused insights here.