Overview
The Digital Command Center (DCC) is a data visualization tool powered by Predix. It offers operational insight into the key factors driving GE Digital's business. Delivering timely, accurate, actionable business insight matters because it builds a culture of transparency and accountability.
My role
I led UX visual design for the DCC, collaborating closely with interaction designers and leading design for product onboarding, data visualization, and responsive behavior — ensuring the app worked on small screens as well as large-format displays.
- In a paired design collaboration I worked with another UX designer to create a robust self-service chart and dashboard building feature, letting users ingest data, choose visualizations, and build custom dashboards for their needs.
- Worked closely with data scientists and engineers to create elegant solutions to specific business requirements.
- Led design of all data visualizations in the application, creating a design system to ensure consistency while still allowing user customization.
- Ran rapid design, prototyping, and user testing to keep the product simple and intuitive while powerful enough to meet the business need.
- Worked in an agile environment, creating and reviewing user stories to ensure proper requirements and acceptance criteria.
Beyond product design, I championed an initiative to educate and evangelize data visualization best practice throughout GE. I synthesized my research into a detailed Data Visualization Best Practices document shared across the organization, and ran Data Visualization Design Bootcamp sessions to help other teams design visualizations and work with complex data.
This project taught me to adapt quickly and deliver quality in a high-pressure, fast-paced environment. I worked directly with some of the most senior executives in the company, solving problems and responding to new requests on the fly.
Exploration and ideation
During discovery we explored a range of future-thinking ideas, including concepts using projectors and large touch screens.
Anomaly detection with machine learning
Partnering with the technology team, we developed an anomaly detection system using machine learning to identify when something is not right. A planned release would let users define their own thresholds for the anomalies they wanted to be notified about.
Design system and chart library
I researched data visualization best practice extensively to build a scalable UI and a versatile design system for data visualization. All designs were created to meet accessibility standards in both dark and light themes.
Chart and dashboard builder
The builder lets users create their own charts and dashboards to display the metrics most relevant to them. I worked closely with another interaction designer to develop a chart-building tool that met real user needs.
Large-format displays
The application is fully responsive and supports large-format displays such as office televisions and touchscreens.
Impact and results
- Consistency without rigidity. The visualisation design system kept every chart in the product reading the same way, while the builder still let users compose views for their own metrics — the hard part of any charting system is allowing both.
- The practice outlived the product. I synthesised the research into a Data Visualization Best Practices document that circulated across GE, and ran Data Visualization Design Bootcamp sessions for teams outside this one.
- Accessible in both themes. Dark and light were held to accessibility standards rather than treated as a preference toggle bolted on at the end.
- Executive-facing under pressure. The DCC was used by GE Digital's senior leadership, which meant shipping quality on short cycles with requirements changing mid-sprint.