Product-Service System, UXUI, Systemic Design, Enterprise UX
6 month, 2024
Background
As part of the Traton Group, Scania CV is a world-leading provider of transport solutions, offering a wide range of commercial vehicles and services. It's developing driverless trucks for various applications and drives to shift towards a sustainable transport system.
What happens when the "eyes and ears" of truck fault detection disappear?
Currently, truck drivers are essential when vehicles experience faults—they detect issues, communicate with service teams, and make critical decisions. But as the industry moves toward driverless trucks and Transport as a Service (TaaS) business models, this human-centric system faces systemic changes.
Project Goal
Scania needed to transform its fault-handling system to support uptime and reliability in autonomous truck operations while building trust in remote diagnosis—a system where no human is physically present with the vehicle. The goal was about reimaging the service ecosystem and the digital interfaces in the critical fault handling scenarios.
Systemic design methods are chosen to develop proposals for such a complex product-service system. With 'Research through Design' as the research approach to explore this speculative field, the research process is designed to iteratively and collaboratively develop design artifacts that visualize possible futures and open up discussions within the organization.
Process & Role
I led this project end-to-end as the primary Researcher and Designer
Key challenges tackled in this project
🕹️ Business models transformation: How technology and workflow adapt to the change?
👩💻 Organizational roles: Who does what when there is no information from the human sensor (the driver)? Which role in the current workflow has the potential to be trained to be the future 'user'?
📊 Information architecture for trust-building: What data matters for a remote setting?
🤲 Defining Human-AI Collaboration: The challenge of avoiding both human and algorithmic "black boxes" while leveraging each party's strengths —human judgment for unknown situations vs. AI's pattern recognition capabilities.
Developed the future Fault-handling Workflow that integrates AI in the decision-making process
🤝 Human-AI Collaboration: This workflow balances automated detection and prioritization with human expertise for analysis and decision-making, where AI handles data processing and initial analysis, and humans make final decisions and handle edge cases
⏱️ Mission-Critical Prioritization: The system considers both safety levels and uptime impact, ensuring that life-threatening issues take precedence while maintaining operational efficiency.
👁️ Continuous Monitoring: The workflow doesn't end with a decision - it includes ongoing monitoring to catch any developing issues.
🔗 Service Integration: Built-in coordination with external services like Scania Assistance ensures seamless execution of repair decisions. This was discussed during the first workshop and added to the workflow afterwards, which refers to the business models and resource integration.
Two complementary interfaces supporting different roles
Screen A - Fleet Overview Dashboard
⚙️ Key Design Features
At-a-glance fleet health: Uptime percentages and active team members are visible immediately
Geographic context: Map showing vehicle locations relative to service infrastructure
Alert prioritization: Color-coded cards showing safety criticality vs. mission impact
Collaborative awareness: Team status and case assignments visible to all
Screen B - Diagnostic Analysis Tool
🤖 Trust-Building Elements
AI Transparency: Shows confidence levels (85% brake pad failure) and data sources used
Human Override Capability: Operators can adjust AI parameters and re-evaluate
Decision Traceability: Clear record of who made what decisions when
Progressive Information: Basic → detailed → expert-level data as needed
🔧 Examples of the improved details and design considerations gathered from design critiques
Want to know more about analysis and how I managed the process? Click here for the full report ↗
Summary & Closing Thoughts
Business Model Drives Design: Understanding TaaS implications was crucial for creating realistic system requirements
Speculative Design Challenges: Designing for users who don't exist yet required extensive artifact-based discussions
Social Structure Matters: Technical transformation requires understanding current trust relationships and power dynamics
I am happy with how this project turned out in six months. It was a rewarding journey - building the design context, bringing new perspectives through design workshops, exploring speculative design, and reflecting on the role of a designer and the power of design when driving change within the organization.
🚛 Want to drive the future together? Let's connect!
