Why Do We Not Ask Why? A Reflection on Technology and Process in the Rail Industry

In the rail industry, we often witness the introduction of new technology without a corresponding shift in processes. Advanced signalling systems, automated ticketing, and predictive maintenance tools have revolutionised certain aspects of railway operations. Still, how rail companies conduct day-to-day tasks may remain entrenched in decades-old procedures. This tendency to innovate technologically while maintaining outdated processes raises a critical question: why do we not ask why?

The Comfort of Tradition

One reason is the comfort found in tradition. The rail industry is built on a legacy of long-established practices that have proven reliable. For example, the operation of rail networks is heavily regulated, with safety protocols deeply embedded in the industry's culture. Even with better technology, deviating from these routines can feel risky when safety is a top priority. Take the case of Network Rail in the UK, which relies heavily on traditional maintenance schedules despite deploying new predictive maintenance tools. While technology enables rail operators to identify potential faults before they become critical, many teams continue to follow routine inspections. The hesitancy to fully embrace data-driven maintenance lies in the long-standing trust in manual checks and the fear of system failure if the process is changed too quickly.

Case Study: Tokyo Metro's Digital Innovation and Process Stagnation

Japan is renowned for its rail efficiency, particularly in high-tech urban systems like the Tokyo Metro. The network has introduced cutting-edge technology, such as automated train control systems and real-time passenger flow analysis. However, while technology has improved service reliability, some manual processes remain unchanged. For instance, despite the use of AI and sensors to detect issues on the tracks, manual inspections are still performed in much the same way they were decades ago. Tokyo Metro workers continue with the exact schedules and routines for track inspections, partly due to regulatory requirements and an ingrained trust in traditional practices.

This situation exemplifies a broader industry-wide trend: technology improves around the edges, but core processes need to be faster to adapt. Tokyo Metro’s reluctance to fully transition to a digital maintenance framework reflects the challenges of implementing systemic change, especially in a safety-first industry.

The Gap Between Technology and Workforce

Another factor is the disconnect between technology and the workforce. Workers on the ground are often experts in the systems they've used for years, and retraining them to adapt to new technological interfaces or tools may face resistance. For instance, the introduction of Siemens’ Digital Rail Services in Germany has brought advanced analytics and machine learning to optimise rail networks. However, despite the technology’s potential, many operators rely on their long-standing manual systems, preferring routine checks over predictive models. The disconnect between the digital experts who create these systems and the railway staff tasked with using them often results in partial implementation and missed opportunities for entire efficiency gains.

Case Study: India’s Railways and the Struggle to Modernize

Indian Railways is another example where a shift has not matched the adoption of new technology in processes. Over the last decade, the Indian government has invested heavily in modernising its rail network, introducing GPS-based tracking systems and data-driven scheduling. However, many of the processes remain the same as they were before. Train dispatch, ticket checking, and even basic maintenance routines still follow manual procedures despite the availability of modern tools.

In this case, the sheer scale of Indian Railways, with its millions of passengers and complex infrastructure, makes it challenging to modernise processes fully. Additionally, with such a large workforce, retraining all staff to use new technologies is a mammoth task. As a result, technology and old processes coexist, often leading to inefficiencies and system bottlenecks.

Legacy Systems and Infrastructure

With its vast infrastructure and reliance on interconnected systems, the rail industry can also find it challenging to overhaul processes without considerable investment. Introducing a state-of-the-art scheduling algorithm may help optimise train timetables. However, the efficiency gains will be limited if the underlying infrastructure is still based on manual signalling protocols. For example, the UK’s Great Western Railway (GWR) upgraded its rolling stock with new high-speed trains, but the signalling systems in some areas remain analogue. This mismatch between technology and infrastructure means that, while the trains have the potential to run faster, the outdated signalling prevents them from operating at total capacity.

Cultural Resistance to Change

The reluctance to ask "why" often comes down to organisational inertia. Like many large sectors, the rail industry has a well-established hierarchy and culture. Leadership may push for innovation, but middle management and operational teams responsible for day-to-day functions may be less inclined to embrace the change. In the U.S. rail industry, for example, Positive Train Control (PTC) systems designed to prevent train collisions have faced years of delays in implementation. Despite the apparent safety benefits, many rail operators resisted change due to the complexity of integrating new technology into existing processes and infrastructure. In some cases, the resistance came from concerns over cost and disruption, but in others, it stemmed from an adherence to traditional operating procedures.

Safety and Regulatory Concerns

The rail industry is heavily regulated to ensure passenger safety and operational efficiency. Safety concerns may prevent new technology from fully integrating, as regulations require extensive testing before process changes occur. In France’s SNCF rail network, for example, autonomous trains have been piloted, but the regulatory environment and safety concerns have slowed its rollout. While autonomous trains offer the potential for greater efficiency and fewer delays, the rigorous safety standards and regulatory approval processes have resulted in a cautious approach to process changes, with human oversight still heavily embedded in the operation.

The Importance of Asking Why

Why do we not ask "why" more often when adopting new technologies and transforming processes? The answer lies in a combination of fear of change, a deep respect for tradition, and the complexity of the rail industry's infrastructure. However, as technology continues to evolve rapidly, it is crucial that the rail industry not only adopt innovations but also critically examine whether their processes are keeping up.

I asked "why" can be the first step toward aligning technology and processes for better efficiency, safety, and customer satisfaction. Case studies like those of Tokyo Metro, Indian Railways, and others demonstrate that while new technology is often adopted, the process adaptations that fully unlock its potential are too usually neglected.

In conclusion, by asking why outdated processes persist, rail operators can avoid falling into the trap of technological stagnation, where innovation is only surface-deep. By fostering a culture of inquiry, the rail industry can better leverage its advancements to create more innovative, safer, and more efficient operations.