Stats NZ needed to modernise the way it worked and was looking for a way to present its Business Data Collection to the public. Ackama was engaged to perform this work due to our strong experience in the design and development of new products. Ackama led a human-centred design process which focused heavily on the discovery of who Stats NZ’s customers are, and what they wanted. Ackama worked collaboratively with internal stakeholders to identify existing data processes and create alignment around a migration and change to adopt new tools and adapt to an identified technology toolset.

To understand the problems Stats NZ customers faced, Ackama completed an intensive discovery phase involving user research. This research helped validate or invalidate assumptions about the project and delivered a good foundation to work from. The discovery phase included:

• analysis of the existing user landscape and Stats NZ personas to identify whom to base our user research on,
• creation and adaption of a research strategy to suit a work-from-home situation due to the Alert Level 4 COVID-19 lockdown,
• focus groups conducted with people who work directly with Stats NZ customers – this gave us an understanding of common complaints and pain points received by the customer service team,
• user interviews with people that use Stats NZ tools regularly – by talking with customers directly from an external perspective, customers were honest and open about their experiences with the tools,
• investigation of popular internal and external tools with similar functionality and to identify best practices for web-based statistical tools.

Based on our insights from this research, Ackama identified that the experience is primarily for new users and those with low technical knowledge of statistics, a previously underserved group for Stats NZ. We generated a design brief outlining the need to create an inclusive experience by revealing the essence of the data, its key stories and critical insights. 

By framing the insights gathered during discovery as a design brief and breaking individual parts into ‘how might we’ statements, Ackama was easily able to create a backlog of high-level feature work for a solution. These features were then translated into wireframes and tested with potential users in order to understand which should receive prioritisation in the final product. High fidelity prototypes were created incorporating the features that had been deemed as the highest value for the tool, and from there the backlog could be finessed and prioritised in order to establish what shape the final product would take.

An essential outcome for the final product was that it needed to be maintainable and extendable by the internal Stats NZ team. In order to support this outcome Ackama opted to build the tool using the R language and Shiny web framework. The combination of R and Shiny was something that Stats NZ had previous experience building their own tools with, and R as a language was something that their data analysts were more familiar with.

Over the course of roughly six weeks in partnership with the internal Stats BDCE team, Ackama built-out a high value MVP containing the most essential features identified during the user testing process while ensuring that critical processes such as data updating could be performed after the project was completed and handed over to the Stats team for future iteration.