Brightspace Insights Portal is an in-house data visualization solution that provides a full picture of users across an organization (learning institution, school, college, etc) to allow faculty to measure various metrics, such as engagement and learner progress. Despite this, there is still a large learning and understanding curve amongst less data-savvy individuals.
Type
UX, Accessibility
Web-based platform
Role
Product Designer / Design Lead
on the Data & Analytics experience team
Timeline
7 Months
May to December 2022
During the majority of 2022, I was one of two lead product designers for the Data & Analytics experience who own the Brightspace Performance+ add-on, which empowers organizations to make data-driven decisions through analytics solutions. We have a long-term goal of unifying the design language and standards of our analytics tooling, and ensuring our in-house dashboards were consistent was one of our pillars to provide a better user experience for beginners and power users alike.
The result of this work has echoed across multiple engineering teams and experiences who are also contributing to our analytics tooling, and are now following in our footsteps (and contributing!) to our vow for accessible data visualizations and design.
Upon inception, our in-house dashboards were inconsistent for both our primary users as well as the data and analytics team
This sort of inconsistency not only made for a poor user experience, but it made it difficult for sales teams to sell the Performance+ product, and it also made it challenging to onboard and support our users whenever they had questions about the analytics dashboards.
Therefore, we sought to align our design language across Performance+
We aimed to align to existing patterns and best practices for data visualizations to reflect industry standards and our users' mental models. Apply previous UX research done in the space to our existing visuals. Create a cohesive experience for all dashboards.
However, this design language was not created in a day. Similar to Rome, extensive and repetitive user research was conducted over the past couple of years to learn user behaviour and ultimately tweak and refine these guidelines
A design and technology analysis was completed to understand how our data visualizations within the platform were built. Additional considerations and conversations surrounding data ethics and guard rails were determined. Exploration and usability research was done via Fable to understand the state of the UI. Implementation requirements were set, and a design guideline draft was proposed.
We then began to explore accessible charting stylers to aid with quick implementation, with further testing done on the newly revamped dashboards.
Despite all of this, this was only the ground work to our long-term solution...
We looked at each individual dashboard and its use case to iterate on our proposed guidelines, by slicing final details into development milestones
1 : Data visualization interactions & user orientation
Bring all the dashboards into alignment, adhere to proposed design guidelines. Improvements to legends, chart interactions, drill paths, and zooming.
2 : Full dashboard filtering
Leverage the Daylight design system and accessible data visualization design language to innovate filtering via sidebar for all relevant dashboards. Fix any outstanding filtering bugs.
3 : Save and share dashboard views
Currently, there is no direct way on the user interface to save and share analytics dashboard views with other users. We aim to implement this by leveraging existing Daylight components.
The remainder of this project contains sensitive information and is under NDA. To learn more about our explorations, usability testing, and all of the nitty-gritty, please contact me to learn more 🔐
As a summary, multiple iterations of these dashboard details were critiqued by other fellow designers, developers, product managers, and client-facing teams to bring a fully-rounded perspective on the end result. I both facilitated and analyzed several rounds of user research to inform the design. In addition, I streamlined the dev & design handoff and QA process to ensure designs were being implemented to a high standard before being put into production.
Lastly, the results of this project gave way to a secondary project which spearheaded the Data & Analytics team's accessible data visualization design guidelines, which acts as the north star for all things analytics. These guidelines have been iterated and referred to by multiple different engineering teams at the organization who work in the analytics space to continue to breath life into our Performance+ offering.
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