Since each report has varying users (usually a Sr. Director or VP of Supply Chain) I worked closely with Product and UX Researchers to identify requirements through Discovery Research. This process started from when the data was prepared and analyzed. I also involved Development early on to ideate, identify feasibility, and understand data limitations. Sometimes, there were existing reports in the legacy business intelligence application (Qlik) that we could reference for key filters and data frameworks.

Research focused on understanding what is important to see within each metric, and how to surface this data while allowing for deeper analysis. Discovery Research was mostly conducted through interviews, as users were responsible for different areas of warehouse operations such as Safety or Performance. Later in the project, we planned to implement surveys for NPS scores and additional feedback.

When I started working on this project early in 2024, there were no established report design standards or style guides, with each Power BI Developer designing reports as they saw fit. Besides lacking consistency, reports were not accessible and report creation was the "Wild West" with lots of back and forth on what "looked" right or not. This also led to a lot of repeat work, as each developer had their own way of creating reports.

Working with the data lead for Supply Chain, we established documentation for other developers to reference, along with style guides and examples based on learnings from Data Visualization books and courses.
For example, I drew heavy inspiration from the Okabe-Ito color palette to use for our enterprise reports, which is important for people with color vision deficiencies as color is often used to compare and differentiate data points.

Below are several examples of the reports that I designed for various Supply Chain metrics. You can see what the reports looked like before and after the enterprise design standards were applied. The goal was to present the data in a clear, and easy to understand way while allowing for further exploration and analysis. Actual data has been redacted.
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I also conducted heuristic analyses of dashboard projects for other initiatives, and provided recommendations based on the enterprise standards that we established for all Power BI reports at the company. These combined practical changes in Power BI, as well as call outs based on Nielsen Norman Usability Heuristics.

With a streamlined workflow and the team becoming accustomed to building reports with enterprise design standards, we noticed faster project completions with more visually consistent data visualizations that met Web Content Accessibility Guidelines.

Feedback from the Business was positive, stating that these reports helped reduce the manual work spent analyzing data in Excel spreadsheets, and sourcing data from various databases and email threads. Since this data comes directly from the source, there was increased confidence in data accuracy and validity - important in decision making.

Future work includes creating more standardized JSON files that developers can re-use while building Power BI reports, enhancing documentation and Power BI training resources, and eventually replacing all reports in the legacy business intelligence application (Qlik) as all the company functions adopt a modernized data platform.