Digital Twins

We’ve partnered with a leading transport organisation to harness the power of Digital Twins—bridging the gap between physical operations and digital intelligence. By creating real-time, data-rich digital replicas of assets and processes, we helped teams identify inefficiencies, predict disruptions, and optimise workflows at scale. Whether improving fleet coordination in transport or streamlining production lines in manufacturing, our Digital Twin solutions delivered measurable gains in operational visibility, responsiveness, and efficiency. These case studies highlight how we’ve turned complexity into clarity, enabling smarter, faster, and more adaptive operations.

Electric Transport Company

Optimising Operational performance

In an industry where uptime, efficiency, and reliability are critical, transport companies are increasingly looking toward advanced digital technologies to optimise performance. By implementing Digital Twins for key operational entities—vehicles, drivers, routes, and logistics processes—we are transforming the way transport operations are monitored, managed, and improved.

The Challenge

Business Challenges

Fragmented Operational Data: Data related to vehicle health, driver behaviour, and route

performance existed in silos, making it difficult to generate holistic insights.

Reactive Maintenance: Maintenance decisions were often based on fixed schedules or emergency

events, leading to either excessive downtime or costly breakdowns.

Inefficient Process Improvements: Without accurate, real-time feedback, process optimisation

relied on assumptions and static models.

Customer Challenges:

Inconsistent Service Quality: Variability in driver performance and vehicle condition affected

punctuality and reliability.

Limited Visibility: Clients lacked access to real-time insights on transport execution and delivery

conditions.

Sustainability Concerns: Growing pressure to reduce carbon emissions required new strategies to

monitor and optimise fleet performance.

The Solution

Through the lens of design thinking and user experience research, we reimagined how Digital Twins could serve frontline operations and decision-makers in a major transport organisation. Our approach focused on co-creating intuitive, insight-driven tools that bridged complex data with real-world usability. By deeply understanding user needs—from drivers and fleet managers to operations analysts—we shaped Digital Twin solutions that were not just technically advanced, but also practically impactful.

  • Fleet Experience Design: Vehicle Digital Twins were made accessible through user-friendly dashboards, allowing teams to monitor performance, anticipate failures, and schedule maintenance without technical barriers.

  • Driver Behaviour Interfaces: We designed personalised driver profiles that translated telemetry into easy-to-read performance insights, fostering safer and more accountable driving behaviours.

  • Scenario Modelling Tools: Our UX research informed the development of interactive route simulations, enabling planners to dynamically test route outcomes based on real-time constraints like traffic and weather.

  • Process Visualisation and Alerts: Logistics workflows were mapped and digitised with human-centric UI design, allowing teams to spot and act on bottlenecks faster through visual cues and alerts.

  • Design System for Twin Evolution: A modular lifecycle framework was co-developed to scale and evolve Digital Twin features over time, ensuring continued usability and business alignment.

This initiative demonstrated the power of pairing Digital Twin technology with thoughtful design, resulting in smarter systems that people actually want to use.

Impact

The Digital Twins initiative are a significant milestone in the digital transformation of the transport company, enabling real-time operational control, predictive analytics, and long-term process optimisation.

Reduced Maintenance Costs: Predictive diagnostics and automated alerts reduce reactive maintenance incidents.

Improved Efficiency: Route simulations and process optimisations reduce average delivery times.

Lowered Operational Complexity: By modelling shared behaviours across similar entities decreases system overhead.

Enhanced Safety and Compliance: Driver insights enable targeted training and proactive risk management, improving safety metrics across the fleet.

Sustainability Gains: Real-time data optimised fuel efficiency and minimised idle times, contributing to a measurable drop in carbon emissions.