Workshop facilitation, user research, prototyping, concept validation
Conner Hunihan (Product Manager)
Kristen Zhou (Product Manager)
Carlo Liquido (Data Engineer)
How should the product balance simplification and technical robustness?
Specifically, how should the platform cater to the needs of the various distinct user groups?
20+ interviews, two workshops, and a community survey revealed distinct user groups within ADP, each of which had their own data needs, technological proficiencies, and preference for learning. While knowledge needs varied across these groups, there were unanimously reported frustrations with transparency of data, as well as with understanding the process of using the platform.
In collaboration with a consulting team from Fjord, core ADP functionality was divided into four distinct product categories: Analytics, Data, Core Services, and Support. Within those categories lay individual product experiences, the most complicated of which was selected as a candidate for prototyping.
Utilizing the existing data portal property would take advantage of existing awareness within the community, but the information architecture needed revision in order to suit the new product categorization.
The information required by users was organized into hierarchies in order to restructure the data portal. This provided not only a foundational information architecture, but an engagement model for actually using products, as well.
A typical journey of using the Development / ETL product was mapped to visually represent paint points, dependencies, and areas of opportunity that exist throughout the process. The exercise suggested that technical users required three distinct pieces of knowledge throughout their engagement with ADP: process (An overview of the process required to use the various softwares of ADP), details (detailed explanations of permissions, points of contact, and use case-dependent instructions) and context (Notes of what works and what didn’t for teams that have gone before).
A low-fidelity, clickable prototype of the “Development and ETL” data product was designed around three core concepts: clarifying the process, surfacing resources, and including technical details. This was tested on-site with data engineers over two sessions.
Comments from usability tests were incorporated into a final, high-fidelity mockup that was delivered to the Data Strategy and Experience team.