Shell
Case study
The partnership that led to an innovative solution for mining operations
Overview
Project duration
9 months
Services
UX Research
Experience Concept Development
User Journey Definition
Information Structuring & Content Mapping
Wireframing & Interactive Prototyping
Stakeholder & Creative Collaboration
My role
UX Designer responsible for defining the experience concept, user journeys, and prototypes in collaboration with the creative team, helping translate ideas into actionable and technically feasible solutions.
Brief
Improving operational efficiency in mining through AI and predictive insights
Shell partnered with Intellisense.io to develop a digital solution for the mining industry. The goal was to combine Shell’s Remote Sense oil condition monitoring technology with Intellisense.io’s AI models to help mining teams plan maintenance more effectively, reduce disruptions, and improve operational efficiency.
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Challenges
Designing for complex, high-stakes operational environments
The project faced tight timelines and limited resources, while requiring deep understanding of mining operations. Each mining team had unique workflows, planning horizons, and maintenance practices.
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A key challenge was designing an experience that supported both long-term and short-term planning, while making complex data, predictions, and alerts easy to understand and act on in real operational contexts.
Approach
Translating complex data into actionable decision support
The work focused on understanding how mining teams plan, schedule maintenance, and respond to operational changes. Based on these insights, I developed clear user flows and interaction patterns that supported dynamic planning and rapid decision-making.
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Working iteratively from concept to MVP, the experience was shaped around real operational scenarios, ensuring that alerts, predictions, and data visualisations were timely, relevant, and easy to interpret.
Visuals
Flows, dashboards, and MVP delivery
These visuals show key screens from the application, including core user flows, dashboards, and alert states. They illustrate how real-time and historical data were structured into a clear, usable interface that supports planning, coordination, and rapid response across mining operations.
Outcomes
A proactive and data-driven maintenance experience
The final application integrated Shell’s Remote Sense technology with Intellisense.io’s predictive models to proactively identify equipment issues and support maintenance planning.
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Dynamic alerts enabled teams to respond quickly to schedule changes, improving coordination and reducing operational disruption. By combining real-time and historical data, the platform supported earlier interventions, improved safety, and more efficient use of resources.
