The discovery phase provided a rich seam of knowledge to inform the next phase of the project: alpha. During discovery, DfT learned lots about colleagues who use the department’s transport data and what their needs are. From that research 4 personas were developed, representing real users from the policy, statistics, modelling and research and analysis areas.
By moving quickly onto alpha, the team could progress with building prototypes for an index and showcase these in front of people. This does not mean that user research has finished - quite the opposite. The team have been continuing to hold more in-depth interviews with users to validate and update the personas (though they have stood up pretty well so far). Additionally, they have set up a user group alongside the steering group to ensure users can hold the team to account - scary!
What’s the story? To be as open as possible, an agile area was set up in different parts of the building for each phase. One of the first actions taken was to draw up a user storyboard – this looks similar to a cartoon storyboard (see picture below). To do this, a persona is taken and their ‘ideal journey’ is drawn, for example when a user needs to gather evidence for a report. This journey is then tested with policy colleagues who identify any pain points in the process that need fixing. The storyboard is adjusted as per feedback, to help develop prototypes that work well in real life. Prototypes are then built and users are asked to try them out!
Priya storyboard example – this technique has been replicated across all personas.
What else are they up to? Lots. The team are looking at the data in greater detail, joining the dots between where data is and how users want to go about finding it. For instance, some want to go straight to the raw data; others want to find an expert who can explain it to them. It’s an important area to understand, and the phrase ‘discovery vectors’ has been coined to describe what’s being done. The research explains that users need to find information in all sorts of ways: by place, team, mode of transport, theme, phrase and keyword.
We’re finding out in more detail:
· how the users need to discover data and information in different circumstances
· what methods they use
· what questions they ask during their search (for example, by analysing emails of data requests made to DfT’s statisticians)
· what factors contribute to the ‘moment of truth’ when users find the information they need
This is captured in a service blueprint - a set of key requirements that will determine what form the service needs to take.
Talk is cheap. The continued increase in availability of data represents a great opportunity to improve public services. Therefore DfT are not the only ones trying to make it easier to exploit this opportunity. During discovery and into alpha, the team have met up with colleagues from other departments across government and learned from each other, including at the event pictured below.
The team working with other Government departments to share Data Index Alpha findings.
This blog has been adapted from Richard Phillips’ (pictured in action below!) writing on the Department for Transport blog page, available to view here.