As climate change accelerates, the infrastructure we rely on is becoming increasingly vulnerable to a host of environmental challenges. Increasing temperatures, intense rainfall, rising sea levels, and occasional heatwaves, are already imposing a significant strain on UK roads, bridges, and essential public services. They are shortening the lifespan of our infrastructure, increasing maintenance costs, and placing an unprecedented demand on maintenance and resilience of these infrastructure assets.
These emerging climate risks underscore the urgent need for a proactive, data-driven approach for not only managing our infrastructure assets but more crucially, preserving and protecting them. This is where asset management comes into the fold. Traditionally, asset management predominantly focused on maintenance and lifecycle planning based on historical data and assumptions. However, as the UK’s existing road and infrastructure systems were designed for past climate conditions, there is now a widening adaptation gap. As such, the infrastructure of the future must be built and managed with the ever-changing and uncertain climate conditions in mind.
In this article, we will explore the growing need for more data-driven infrastructure management, the possible barriers to adoption that need to be considered, and the immense opportunities that it brings in protecting and preserving critical infrastructure.
Enhancing infrastructure resilience with smarter decision making
Asset management is the means of maximising the whole-life value of our infrastructure, trading-off cost, performance and risk in order to achieve our strategic and business objectives. In the past, infrastructure maintenance relied mostly on routine scheduling and reactive repairs. However, this approach has been shown to be sub-optimal in terms of achieving business objectives plus it can no longer keep pace with the growing pressures of our changing climate. In order for us to protect and prolong critical infrastructure, we have had to take a more proactive approach to asset management - one driven by real-time data analytics.
Real-time data has revolutionised the way we manage our infrastructure assets, now offering us a truly transformative advantage. By continuously monitoring the performance and conditions of assets in real-time, we can identify issues and potential vulnerabilities before they become major problems. For instance, sensor technology embedded onto roads, bridges, and drainage systems, can help to track load stress, temperature levels, and even early signs of metal and material fatigue over time. Once the health status of these assets have been determined, this information can then be relayed to the relevant stakeholders to determine the right interventive measures.
Data also allows us to model how assets will behave under different operational scenarios. As a result, asset management teams are able to predict maintenance needs, optimise resource allocation, and deal with smaller issues before they escalate to costly disruptions. This data-driven approach not only protects infrastructure assets but also extends their lifespan, helping asset owners to make more informed, and cost-effective decisions.
A good example of this is the use of Amey’s in-house Bridge Management System, a digital asset management solution that tracks, monitors and models the structural health of bridge infrastructure. The system is used to maintain the Severn Bridges through cyclic maintenance, daily structure inspection checks and safety patrols, as well as tracking and responding to any incidents that could impact the structural integrity of the bridges.
The system also leverages machine learning technology to predict the effects of adverse weather conditions on bridge structures, including any potential issues unseen from ground level, preventing harm to road users and operational teams from issues such as high winds, ice bombs or severe weather. This bridge management system was first introduced in the maintenance of the Forth Bridge following a critical structural issue in 2015, which saw the Forth Road Bridge closed to all traffic, costing taxpayers £1 million a day. Such costly disruptions can now be avoided through proactive tracking of asset health and earlier interventions.
Data-driven asset management strategies – challenges and barriers to adoption
Data-led asset management has the clear potential to reduce costs, improve performance and enhance resilience in the face of climate change; however, several barriers hinder its widespread adoption, particularly when it comes to roads and highways.
A data-led asset management system involves a different approach to decision-making from that of traditional infrastructure maintenance. By definition, if the same decisions are made, using the same old procedures, then the same outcomes will result. This implies a change programme that goes beyond simply introducing new technology. Organisations which have successfully adopted data-driven asset management have changed their approach to decision-making. This requires investment in organisational change, and often cultural change, which can be a significant challenge to successful adoption.
Poor data maturity also hinders the adoption of modern asset management practices. Many authorities lack reliable records of assets, their location, condition and performance. Major asset owners may store data on several discrete databases, which are not integrated and cannot share records.
Financial constraints are another barrier. Whilst data-led asset management has been proven to increase whole life value of infrastructure systems, it requires a ‘spend-to-save' approach. This typically involves initial investment in data collation, procurement of an enterprise asset management system, changes to the organisation’s practices and procedures, and installation of remote monitoring technology. Many public and private sector organisations find it difficult to shift their focus away from short-term problem solving onto long-term value enhancement.
Another barrier is the difficulty of aligning policy goals with the whole-life value outcomes delivered by asset management. There can be a disconnect between asset management and key policy objectives such as sustainability and innovation. Asset resilience and decarbonisation are often seen as two separate issues whereas in reality, they are both elements within the same sustainable infrastructure system. This therefore limits the opportunity to integrate asset management into infrastructure planning, making it harder to adopt advanced technologies like real-time data analytics.
Short-term cost considerations also take precedence over long-term value creation. These challenges are compounded by a shortage of skilled professionals, who possess the experience to make compelling business cases for such technological solutions and the expertise and training to implement data-driven asset management practices effectively.
To ensure the successful adoption of smart asset management, organisations must first identify and address these challenges head-on. Tackling funding and knowledge gaps, skill shortages, and policy misalignment early on will enable the adoption and integration of data-led solutions and set the foundation for long-term infrastructure resilience.
The benefits and opportunities for smart asset management
Despite the barriers, the adoption of data analytics in asset management presents significant opportunities for organisations looking to enhance infrastructure resilience. With the growing availability of real-time data from sensors and other technology devices, asset managers can now monitor the condition of infrastructure assets more closely than ever before. As a result, organisations can identify the most vulnerable assets, allowing them to dedicate focus and investment where needed.
This data-driven approach also enables the development of long-term, holistic strategies for managing infrastructure assets. It also factors in the current and future needs and expectations of users, stakeholders, and regulators, as well as the potential impacts of climate change, population growth, urbanisation, and technological innovation. Additionally, through lifecycle costing and risk management, asset managers can optimise resource allocation, balancing preventive and reactive maintenance and making informed decisions between rehabilitation and replacement.
What's more, data analytics fosters better collaboration between different agencies and stakeholders involved in infrastructure management, promoting a culture of continuous improvement. It also enhances the flexibility and adaptability of infrastructure assets by incorporating design features and technologies that reduce exposure to risks and improve coping capacities. Lastly, data analytics also provides opportunities for monitoring and evaluating the performance of assets, allowing organisations to use feedback and lessons learned to refine asset management strategies, ensuring highway infrastructure remains resilient and sustainable over time.
As the effects of climate change intensify, the need for resilient infrastructure has never been more critical. Asset management, powered by real-time data analytics, offers a powerful tool for safeguarding infrastructure against future challenges. By addressing barriers such as funding constraints, skills and knowledge gaps, and policy misalignment, organisations can harness the potential of data-driven decision-making to extend asset lifespans and reduce long-term costs. The adoption of smart asset management strategies not only enhances the understanding of asset performance but also fosters collaboration and innovation between different stakeholders. It is essential for organisations to embrace these technologies, prioritise investment in vulnerable assets, and continuously refine their asset management strategies and practices. Doing so will ensure that our infrastructure is robust, cost-effective, and ready to meet the demands of future climate challenges.