How user-centred design can enhance collective intelligence to support decision-making 

It should come as no surprise that decision-makers in government have a tough job. Those big decisions are loaded with complexity and always have an impact. Sometimes the impact is small but quite often, there can be global consequences. This might be why the idea of collective intelligence is gaining a lot of traction. 

Collective intelligence is the collaborative effort between a group of people who try to solve a problem. People in the group often bring different types of expertise. This approach joins up the best of what people and technology can offer. When you bring the right people together, there are the added benefits of: 

• improved ways of working
• better understanding of users
• creative and innovative problem-solving

Collective intelligence in practice

A security and intelligence client asked us to explore the need for a cross-government economic decision-making model to ensure the UK’s resilience and security. We worked as part of a consortium of consultants, with our focus on user-centred design. Our collaborative aim was to bring a fresh perspective to a very complex challenge. We were keen to understand: 

• what a decision-making model might look like
• who the users of the decision-making model may be and the environment within which they work
• potential features of the model, as well as information and data sources
• the current process of decision-making and associated challenges

Designing for users 

We championed the use of GOV.UK discovery and alpha guidelines throughout the project. Our iterative, agile design process involved the continuous testing and refinement of assumptions. A collaborative approach to design enabled cross-functional participation and knowledge-sharing in the team. We also maintained active engagement with stakeholders spanning academia and different government departments.

During the discovery phase, we interviewed 23 participants who provided key insights into the problem space. We analysed these insights during collaborative workshops. These findings were fed into design-thinking sessions which informed early ideation.

During the alpha phase, we prioritised 3 assumptions from our findings. These were that:

• a GOV.UK user interface would carry more authority than a custom-styled interface
• users would gain value from a feature which checks the credibility of information
• implementing a channel between academics and civil servants would result in better knowledge-sharing

We created high-fidelity Figma prototypes to test these assumptions. We then carried out moderated usability testing sessions to uncover deeper insights into these assumptions.

Prioritising user needs

Our research revealed that knowledge-sharing and collaboration – the very core of collective intelligence – can be enhanced by technology. One of our interviewees noted:

“Policymakers are time-poor so a solution design needs to be something easily used with headline information and links to deeper information if they wish to explore further.” 

This quote highlights the need for a digital enabler of collective intelligence. It also captures the kind of experience users expect to have – one which helps them make the right decisions. 

We also uncovered a need for a tool for actuaries, economists, academics,and policy advisors who rely on different sources of data to support their work. Because of this, these user groups expect that any digital solution should:

• be easy to use
• avoid technical terms and jargon
• allow for collaboration with subject matter experts

We compared reactions to a GOV.UK and custom-styled interface using A/B testing. This confirmed our hypothesis that a GOV.UK user interface would carry more authority and be more effective. Users gave similar reasons for preferring the GOV.UK user interface – it’s trustworthy and represents what good services should look like.

Future iterations

Our work confirmed that effective economic-decision making can be supported by a collective intelligence tool. However, to be effective more work is needed to design a solution that can balance user needs for trust, speed and clarity, while maintaining diverse sources of complex information.  

There are vast information sources, not all of them trustworthy. An ocean of data exists, and some is easier to analyse than others. Collaborating and getting real subject matter expertise is essential. Capturing a full range of expectations needs more research to validate other potential user groups. This would also help to refine assumptions and iterate the prototype.

Our most interesting finding was that there’s a real appetite for improved collaboration between civil servants and academics. Though we worked with a small subset of specific users, the benefits of collective intelligence could be a game-changer if realised across government. We envision less duplication, more efficiency, and better-informed policy outputs. It sounds idealistic, and it needs buy-in from government and academia, but it’s a vision we believe should be explored.

Is the collective intelligence approach worth it?

Collective intelligence is a valuable approach – no question about it. Having the opportunity to work with a diverse team of experts really opened our eyes to new ways of working. Everyone on the team brought something unique and fresh to the table. We’d love the opportunity to work under a collective intelligence model again, and we’d wholly endorse its use to tackle any wicked problem, both in and outside of government.

Read more about user-centred design on the Made Tech blog.

About the Authors