I avoid mixing politics with work and I’m not going to start now. I’m certainly not going to offer subjective opinion about specific clients or indeed any specific government or political party.
However - the origin of the professionalisation of asset management is deeply connected to some big matters of economics which are worth unpacking. I think it’s interesting! But more importantly, it provides important context for anyone interested in asset management and infrastructure management more broadly.
One caveat- all the following views are my own. This is informed by my 20 years professional experience in industry, academic studies at The University of Exeter and Lund University, as well as formal training in engineering, asset management, management consulting, including some time studying utilities regulation at the University of Oxford’s Saïd Business School.
Let’s start with some suitably sweeping statements…
Economic basis for regulation
Unconstrained Capitalism will lead to the pursuit of profit at the expense of everything else. And that’s a really important consideration – because while profit is tangible and relatively easy to define, the everything else is messy and complicated. Ultimately, profit at the expense of everything else leads to terrible outcomes. Taken to its most extreme – slavery is profit at the expense of our humanity.
And that’s why we have laws and state regulators. The goal of a regulator is to ensure the delivery of outcomes that an unconstrained free market would not. Defining what those other outcomes should be is complicated. And agreeing how regulators should achieve their remit is contentious. But that core principle is pretty universal.
So how does this link to infrastructure?
Infrastructure Privatisation
Let’s go back to 1970s Britain. Most major industries and infrastructure organisations were state-owned. They ran on fixed annual budgets, often disconnected from the purpose and effectiveness of those organisations. Decisions were often made on the basis of individuals and their power and influence. Many of those leaders were dedicated and earnest and we rightly celebrate how they drove positive impacts through their strong personal convictions. However this system also had many flaws- with perverse incentives and inadequate checks and balances on decision making. Most regulation was around safety and protecting the public from harm.
At the same time the UK was facing economic stagnation, high inflation, and industrial unrest (e.g. the Winter of Discontent 1978–79). It’s debatable exactly how and to what extent these issues were connected, but regardless, a general belief emerged that the state sector was inefficient.
1979 saw the election of the Thatcher Government which was heavily influenced by free-market economists like Milton Friedman and the neoclassical Chicago School of thought. As such, they pursued a policy of reducing state ownership and increasing competition. This government saw privatisation as a way to improve efficiency through profit-driven incentives.
Many of the organisations privatised were natural monopolies (you can’t exactly change the pipes that supply drinking water to your home). Others were public monopolies (for example the post office act of 1969 made it literally illegal for anyone else to sell delivery services for letters and lower value postage).
A big challenge of privatisation was setting up these companies in a way which encouraged mechanisms to exploit the targeted profit-driven incentives with limited opportunities for competition for customers.
Also, it should be noted that many of these privatisations were delivered in a hurry. The general culture in much of the civil service at the time (which you have to remember before privatisation saw the organisations in question as part of their own system and not as separate entities) were reluctant to deliver on the government’s agenda. Additionally, there is always pressure due to the limited terms of a parliament. This was before the fixed term parliament act but there was still a relatively short window for this incoming government to deliver their agenda. And so many of the privatisations gave priority to getting it done over getting it right.
Before formal asset management
Before asset management became a formal discipline, infrastructure organisations (obviously) did operate, maintain and invest in physical assets. However, that management was fragmented. As already explored, decision making tended to be disconnected from clear strategic goals.
The effect of this from an organisational perspective was that engineering departments handled maintenance. Separately, accountants tracked costs. And separately again strategic planning was largely capital project–focused (favouring vanity projects with good PR value) rather than lifecycle-focused.
To quickly digress, political movements tend to centre on one of two messages depending on whether it’s those in power speaking, or those in opposition trying to get elected (or influence policy). Both result in a political bias towards delivering status projects.
When you are in power you’re pushing a message of competence:
Look at this new project which demonstrates how I’m making things better. I’m building the future!
Here is some tangible evidence that I’m delivering on my promises.
Look at this photo of me putting a spade in the ground or cutting the ribbon on some big new shiny thing.
And when you are out of power, you’re arguing that it is time for change:
X is broken which shows the status quo is bad. Someone needs to do something about the Y problem!
Here’s some tangible evidence that those with power are not delivering on their promises
Here are some promises that I would deliver, and here’s my vision for how that would be better than where we are today
Vote for me and I’ll build X!
So why does this political behaviour matter in an asset management context?
Without a structured connection between the “vision” and the “reality” on the ground, it’s common to see divergent plans based on local priorities. And more importantly, when organisations experience direct political interference, they orientate themselves towards political needs (pictures of politicians cutting ribbons around shiny new futuristic technology) rather than practical needs - keeping the lights on, maximising value and minimising cost (1).
Asset management as a response
So the context is:
that we regulate to deliver outcomes that an unconstrained market would otherwise expend for the sake of profit.
After privatisation we had a whole set of natural monopolies operating with profit based incentives.
These new companies had immature management systems, developed in a hurry by combining fragmented functional processes from different national authorities, and a top layer of private owners (primarily interested in a return on their investments).
I should acknowledge that this is before my time, but I’ve read up on this period (especially when I was working in the rail sector). I also had the privilege of interviewing lots of experienced engineers (who had lived through privatisation) as part of my job when I was doing asset performance and reliability improvement projects (2).
Asset management practices emerged over time, informally at first and still in a fragmented way.
Building on standard management accounting practices, privatised companies needed a transparent, justifiable way to report on their assets under regulatory scrutiny.
The regulators in turn expanded their remits to cover financial regulation, and so wanted evidence-based investment decisions, building towards risk-based maintenance, and long-term value planning.
At the same time within engineering departments, concepts like whole-life cost and risk-based decision-making started to formalise. As the practice of Reliability Centred Maintenance continued to add value to organisations, the approach started to influence thought more broadly.
From the late 1990s Asset Management started to mature as a discipline when large infrastructure owners realised that integrating engineering, finance, and risk delivered better value and resilience. Importantly, by linking these departments together, infrastructure owners were better able to assure regulators that they were competent in their stewardship of the assets.
The different regulators for different industries had various powers over these infrastructure owners. These powers also changed (and generally matured) over time. This influenced the speed and manner of asset management adoption.
The infrastructure owners typically held concessions rather than outright ownership. These concessions are often competitively let, and poor performance can lead to early loss of those concessions.
In various forms regulators (and related government agencies) monitor and have powers to enforce safety standards. And many regulators operate “control periods” where the infrastructure owners have to agree to formal business plans with defined prices for defined services and performance targets.
As these infrastructure companies improved internal alignment to meet both their regulatory obligations and obligations to shareholders, the first formal definitions and frameworks emerged.
A key aspect of this was the use of “asset registers” supported by integrated asset information systems. Specifically, most regulated infrastructure businesses hold a “regulated asset base” which forms the basis of their management accounts. By nature this drives the organisation towards improving surety of what assets they have, how confident they are in asset performance, as well as the costs of those assets.
Hopefully this is starting to sound familiar and would be recognisable as what we think of as asset management today. Much of this shared understanding of asset management is codified through common standards.
So how did that happen and who is driving that standardisation?
The Institute of Asset Management
The Institute of Asset Management (IAM) was founded in 1994 in the UK as a not-for-profit professional body to promote and develop the discipline. Originally driven by a small group of utility sector professionals, the aim was to share good practice, develop a common language, and professionalise asset management.
This group’s early focus was around networking and knowledge-sharing through conferences and working groups. From this, standard terminology and principles started to emerge. This is before ISO standards existed. Given the context, this group worked in close collaboration with regulators, (especially in energy and water).
As the group grew in terms of numbers of members and influence within their organisations, efforts started to be coordinated to formalise and codify their approaches.
The IAM worked with the British Standards Institution to develop Publicly Available Specification 55, aka PAS 55 (2004 & 2008). This was the first formal specification for optimised management of physical assets which fairly quickly became the international benchmark.
PAS 55, along with more effort from The IAM and wider asset management community heavily influenced the ISO 55000 family of standards for asset management, which expanded the discipline beyond physical infrastructure to all asset classes.
As asset management practice started to be shared and adopted globally The IAM helped to cofound the Global Forum on Maintenance and Asset Management - an umbrella organisation of professional asset management and maintenance bodies from around the world. The global forum has published (and continue to develop) the asset management landscape (3) which is essential reading for anyone working in the asset management profession.
So, now that asset management practices have been formalised establishing a distinct profession, what does this mean for asset management in today’s political and economic climate?
Asset Management Today
I expect the standardised approaches that have been codified in the various documents within the asset management community will continue to develop and grow. Through the global forum (including The IAM) we now have a robust mechanism to share knowledge and understanding as well as codify that learning into formal standards.
And now that the foundational principles of asset management have been established (and more or less agreed) the next big opportunity is to apply that learning in the context of emerging challenges and opportunities.
From my perspective, one of the most pressing issues that we face impacts literally every aspect of humanity. I am of course talking about the climate emergency.
Climate Change
The earth’s climate is changing. Unchecked this is existential. Mitigated climate change will be manageable. While it’s not always palatable to point out, with deliberate and focused policy, there are actually lots of opportunities. I’m not saying climate change is good because we can profit from climate change. I’m saying if we are going to have to deal with the consequences of climate change, we should take the opportunity to build things that are better and we should build them more efficiently. If I burn down my house, I’m not better off by having to rebuild it. But I also don’t have to build the exact same house and build it the same way it was built the first time.
Due to climate change, basic assumptions around the life, cost, and value of assets are being challenged.
This is felt across the whole asset lifecycle:
How we plan new infrastructure given the changing climate. For example how tracts of land are becoming vulnerable to floods, wind storms, droughts and fires etc.
Standards to which we design assets need to move from resilience to a worst case climate event, to natural hazards occurring at unpredictable frequencies and in totally different ways. Thinking needs to move from “1 in 100 years” to “everything possible over 100 years”
Given that most of the assets we need already exist, we also need to contend with increased operational costs and maintenance requirements as well as shortening remaining asset lives.
As we realise the negative climate impact of our assets we need to find ways to reduce the impact of assets. Less embodied carbon. Less energy use. More nature based solutions. Improved maintainability. More operational resiliency for the expected increase in disruptions and asset failures.
If you’re interested or passionate about this subject, The IAM Climate Emergency working group might be the group for you!
Public Perception
Another massive shift is on public and political attitudes. The formation of asset management practices are, in their roots, linked back to perceptions of public sector inefficiency - with good asset management helping to improve decision making and demonstrate competence.
Today it is undeniable that there is a growing perception of failures of infrastructure companies- or at least a dissatisfaction with services and outcomes. Without going into specific examples the aforementioned “time for change” political narratives are being directed more towards infrastructure companies, as they become recognised for their role in delivering services to the general population.
Asset management as a profession should be (in theory) neutral to those criticisms. Good asset management provides transparency and clarity over difficult decisions around the cost, performance, and uncertainty of choices.
However, consultants like myself can be seen as part of the status quo. We should not pretend that there is no challenge with individual people with individual incentives (including the quite reasonable desire to be remunerated for their labour) moving freely between the infrastructure companies, the regulating organisations, and the service suppliers to both. This is a nuanced problem as, on the one hand it’s good to share knowledge and experience, and there is a clear argument to protect an individual’s freedom to work (or not work) for whoever is willing to compensate them. In the other hand, relationships can easily get too familiar and there is an obvious risk of moral hazard.
Additionally, it is worth acknowledging that part of the public perception is related to the apparent inefficiencies and challenges with how major capital investment projects are delivered. The reality is that there are more specialist interest groups than in the past, with specific agendas that in isolation are rational and logical. But in the context of a massive long term strategic project can add complexity and delay. The caution here is that as asset managers drive towards robust processes within well-defined management systems, that we avoid making things over complicated and unwieldily. We should also seek to ensure specific considerations should be made with some level of proportionality to the bigger picture. Let’s not let the perfect be the enemy of the good.
Economics
Building on the theme of trying to keep the big picture front of mind, we should also consider the economic outlook - more importantly the general feeling with all infrastructure businesses is that money is quite tight at the moment.
This feeling is really down to two economic trends that impact infrastructure organisations- the cost of delivering work has relatively increased (specifically, inflation means that the value of money is decreasing) and the availability of funding for work is diminishing.
To address funding - UK public sector net debt is now around 100% of GDP and is at the highest sustained level since the early 1960s. As importantly, the annual budget deficit (the gap between spending and tax revenue) has been stubbornly high. This jumped with the 2007/2008 financial crisis and again after COVID-19. The emergency spending precipitated an enormous transfer of wealth, which massively contributed to a growing inequality (more on that later).
A key challenge this has created is that, with the reduced value of money and increased debt servicing costs (where the UK now spends considerable amount on paying interest on its debts) infrastructure funding is struggling to compete with other spending priorities.
This limits availability of funding for assets where the government has retained primary funding responsibilities (roads, schools, hospitals, defence) as well as in privatised sectors which are subsidised by the state (like public with transport, ports or energy generation).
Additionally, even where infrastructure is owned by private companies (so the assets don’t sit on the government balance sheet) many of those companies rely on borrowing from capital markets subject to the same pressures. Essentially all infrastructure debt is now more expensive and therefore all funding is constrained.
Adding into this challenge is that service charges that go towards privatised infrastructure (e.g. your water bill or electricity bill) are also increasing - so while this isn’t direct taxation, this contributes to increased costs of living which makes people less well off with less money available for taxation, and also further contributing to inflation.
Coming back to that point about growing inequality, those who were relatively wealthy before the financial crisis and covid benefited considerably from the emergency spending, with financial asset values increasing much faster than the wider economy’s growth or average salaries.
Generally, in an otherwise unconstrained capitalist system, wealth accumulates roughly at pace with the compounding effect of interest and economic growth. Ordinarily this would (at least theoretically) be kept in check by ‘frictions’ like creative destruction and market competition. While the whole economy is growing there are winners and losers from specific investments, with larger businesses of aggregated wealth being devalued by disruptive technologies or superior competitors. In addition to these market actions, taxation and policy can also lessen the accumulation of wealth.
However, in the context of the financial crisis and covid, many of these ‘frictions’ to wealth accumulation were simply overwhelmed.
And those with accumulated wealth, will rationally seek to invest that wealth to retain or even improve the value of their wealth further. The net effect of this is that more and more assets end up being owned by a smaller and smaller proportion of people, with those assets being brought and rented back to the original users. There are of course many examples of this - but the important point for infrastructure is that for most infrastructure users (which is most people) services feel like they are less good and more expensive. And what that means for asset managers is that it becomes increasingly challenging to find an acceptable answer to the cost/benefit aspect of the financial planning. At its worst, we’re perfecting the frameworks with beautiful equations that very competently conclude that we can’t afford to do the required maintenance. We can’t square the circle…
Or can we?
Well that got a bit gloomy! Perhaps we need a more positive way to conclude things.
Computer science
Given my academic background and professional experience in applied computer science, and in the context of all the AI hype, I’ve recently focused in on Artificial Intelligence. I’ve tried to balance the genuinely amazing technology shift we are living through, with a certain amount of realism about what technology can do, and scepticism about the more wild claims.
To summarise:
No, AI isn’t going to replace all jobs.
Yes, AI is going to change every aspect of our lives.
No, the world won’t be recognisable to you next year because of AI
Yes, when we look back in 10 years time every aspect of our lives will have in some way been affected by AI
You can read my posts about AI here.
I don’t want to limit this section to Artificial Intelligence. To be totally honest it’s a bit of a buzzword and while it is interesting, it’s only one overhyped aspect of a much larger trend: the digitisation of every aspect of life.
Everything else that I’ve discussed so far will be affected by improvements in technology. From politics to business to economics and everything in between. And of course this has profound implications for professional asset management.
We actually wrote about this at the centre for asset studies a couple of years ago (4)
We can think about digitisation as a systematic use of technology to turn physical, analogue, or manual processes into digital, connected, and automated ones. I have grouped these into value opportunities, from an asset management perspective.
Value Opportunity for Information Access, Sharing, and Collaboration
New technologies allow for faster (sometimes instantaneous) communication. Systems and approaches are being established that support rapid sharing of asset condition from asset sensors and operational teams on the ground, to update control centres who can prioritise interventions and manage the operational responses to incidents, and can rapidly instruct maintenance teams or contractors. All of this condition and intervention data can be recorded and made available to support asset management analysis and planning.
The improved access and speed to information sharing gives huge opportunity for faster and better informed decision making, and supports much deeper analysis and understanding of the organisation’s assets and wider business.
Decision at all levels, and across all functions of an organisation can be made with access the same, up-to-date asset data and information without gatekeeping. A helpful way to visualise some of the information flows and use cases is looking at the 10 box conceptual model, aligned to the global forum landscape groupings.
And it’s easier than ever (from a technology perspective) for data to be shared between organisations. To take one example, in the railway there are many organisations that network rail, the main infrastructure manager, must exchange information with. Line side neighbours, bridges and structures going over or under tracks, emergency service involved in operations, other transport organisations, as well as commercial retailers, utilities suppliers and so on. Organisational barriers are sometimes defined through contracts, statutory requirements, and formal agreements. Sharing data across organisations can be difficult due to risks and liabilities associated with data quality. Additionally the investment required to make data available for external organisations is often considered to be of a lower priority than all of the international organisational priorities. Both issues around data quality liabilities and cost of effort are significant opportunities for technological advancement.
Value Opportunity for Data Capture and Sensing
As physical computing continues to get smaller, cheaper, and more robust, there are more and more opportunities to put more sensors in more things. Additionally, device connectivity continues to be refined and improved. And with each generation, new local computers (like control systems) are more able to share more data more easily.
I’ve heard more than one person describe this as an Internet of Things Digital Twin Meta-Cyber-Physical Mesh, which is certainly a more fancy way of saying “putting sensors on stuff and using the data”. But, to decode some of that more complicated language:
Internet of Things (IoT) refers to physical devices connected to the internet that collect and share data automatically. For example, sensors on railway tracks send temperature and vibration data in real time to help maintenance teams prevent faults.
A Digital Twin is a virtual replica of a physical asset or system that is continuously updated with live data. For example A 3D model of a water treatment plant that updates with pump performance and flow rates to support operations as well as to help with asset management planning.
Cyber-Physical refers to the increasing interconnection between the physical “real” world and the virtual digital world.
And so, a Meta-Cyber-Physical Mesh would be a (largely theoretical) interconnected web of multiple digital twins and IoT systems working together to coordinate large, complex infrastructure networks. For example, if all the UK’s bridges, tunnels, and roads would be linked in a shared data environment, allowing traffic, structural health, and weather impacts to be analysed together for better decision-making.
One of the more useful trends in asset condition surveying the use remote sensors which reduce on the ground labour effort and reduce the operational disruption required to provide a safe working environment for survey teams. This would include things like drones, LiDAR, and satellite imagery. These approaches can inspect large or inaccessible assets quickly and repeatedly. They do have limitations, cloud cover can reduce visibility, weather can impact use, and some assets have restrictions during operations that limit the realisation of one of the main justifications for the use of remote sensors. For example, drone based runway inspections can’t be delivered during normal airport operations.
Types and applications of sensors are constantly evolving- with new and innovative approaches being developed and tested all the time. For example, acoustic sensors have started to be used for leak detection, thermal cameras can be used to understand energy loss, vibration sensors can detect for early fault detection.
One of the challenges with new methods is obtaining enough data to tune measurements and validate against traditional methods. Also, new methods can improve accuracy and frequency of measurements which can make current standards problematic.
An example I think I’m safe to share from when I worked in the Network Rail Track discipline area, the introduction of plain line pattern recognition (PLPR). Really cool use of computer science where super high definition images are taken of the track under full line speed trains. Using image pattern recognition software(s), faults could be immediately identified and raised. This started flagging huge numbers of faults which, based on the then unchanged track standards, required action. Historically these faults would have been identified during a track walk and logged for actions on a much lower frequency. The track wasn’t any less safe, but the work bank ballooned and quite a significant effort was required to rebalance standards to provide more flexibility from when a fault was detected to when it needed to be corrected. Obviously, this has resulted in a huge improvement in the long term, but in the short term it presented significant challenges trying to prioritise work. Especially as the roll out of PLPR was done in phases meaning that without careful consideration it could have led to lines monitored with PLPR getting a disproportionate amount of resource allocation.
This also links to a wider point about improving accuracy of measurements as more precise measurement reduces reliance on infrequent manual inspections and subjective visual assessments.
Value Opportunity for Data Analysis, Trend Recognition, and Insight Generation
All of these improvements together are driving a significant shift in several aspects of asset management. Asset managers can use historic and live condition data together to anticipate failures before they occur, supporting a transition from reactive maintenance to predictive maintenance.
Where Root Cause Analysis used to require significant manual effort, as computer modelling competence improves, investigations to understand why failures happen and prevent recurrence can be undertaken as a standard practice in asset management teams rather than relying on specialist engineering teams. Additionally this allows for Cross-Asset Insights: where infrastructure performance data can be linked with environmental, usage, and financial datasets for holistic decision-making.
And another emerging trend is for improved Investment decision making where raw performance data can be more easily used for evidence for prioritising different renewal, refurbishment, or replacement strategies.
Value Opportunity for Automation of Processes
We can consider the end-to-end process, from acquiring asset data, to putting it into context to create information, to using that information in analysis modelling to improve decision making and improve asset management planning. Within each of these processes we can automate workflows. For example, maintenance scheduling can be triggered automatically when asset condition hits a threshold. We can automatically update operational plans based on asset condition and planned maintenance tasks. Compliance Reporting can be streamlined with automatic generation of regulatory submissions from live asset data.
Likewise, asset systems can become more ‘intelligent’ by Self-Adjusting. We already have basic things like intelligent lighting in toilets that come on when they detect movement saving power when not required. And thermostat controls for HVAC systems are an old technology, with newer systems predicting adjustments required based on occupancy and scheduling patterns.
To be fair, there is a constantly growing catalogue of intelligent asset systems…
Smart lifts/elevators, Grouping and scheduling lift journeys based on predicted passenger flows to reduce wait times and energy use.
Adaptive traffic signals, (Smart Motorways and Smart Junctions) with Traffic lights that adjust timings and signs that adjust speed limits in real time based on congestion, accidents, weather, or special events.
Self-adjusting escalators, Escalators that slow down or stop when no one is on them, then restart when passengers approach.
Intelligent irrigation systems, Watering systems in public parks that adjust based on soil moisture, rainfall forecasts, and usage patterns.
Smart grid transformers, Power transformers that balance loads automatically across the grid in response to demand fluctuations.
The list is huge and constantly growing. The challenge isn’t so much as coming up with assets that could be automated, but prioritising which assets are worth investing in and the associated business change effort to bring in the new assets with new standards and new processes.
Value Opportunity for Improved Stakeholder and Customer Experience
Often in large infrastructure businesses, the end user or end customer feels like a lower priority than dealing with all the other responsibilities and processes required to operate, maintain and renew the assets. And yet, the entire built environment is ultimately built for humans. People centred asset management is fundamental, and how humans are considered can be the critical factor between success and failure.
I’ve been exploring inclusivity within asset management recently having formed an informal institute of asset management working group. In essence, inclusivity is a measure for how included people are - and we can apply this across the whole life of an asset system. This covers factors like:
Have we limited who can maintain the asset? With western countries experiencing shrinking and aging workforces it’s more important than ever to make assets as easy as possible to maintain.
Have we limited who can safely operate the assets? If the emergency stop button is at the top of a ladder we’ve unintentionally massively narrowed the proportion of people who can operate the assets.
And this is especially relevant for applications of computer science in asset management. For example, Service Disruption can be minimised (the most obvious impact on customers) through faster detection and resolution of asset faults helping to reduce downtime for end users.
And regardless of any service disruptions that might happen, these can be mitigated through Transparent Service Levels and performance. Public dashboards showing asset performance build trust with customers and regulators, and can allow users to plan around disruptions.
Conclusion
The story of asset management is, at its heart, a story of adaptation. Born out of the tensions between profit, regulation, and public need, the discipline has grown into a professional framework that helps organisations navigate complexity and demonstrate competence. From its roots in fragmented practice and (hurried) privatisation, asset management has evolved into an internationally recognised profession with robust standards, a common language, and a global community.
What might make asset management powerful is it’s neutrality: the same principles can be applied in nationalised industries, privatised monopolies, or hybrid models. They provide a way of making difficult trade-offs visible, linking vision with delivery, and balancing value, cost, risk, and performance over the whole life of assets. And yet, this is also a significant risk - where asset management is seen as part of the status quo: the “unelected bureaucrats” who so often become the bogeymen in simple political narratives.
Looking forward, the context really has shifted. Climate change, digital transformation, strained public finances, and shifting public expectations all present new challenges. But they also reinforce why asset management exists: to bring evidence, structure, and adaptability to decisions that otherwise risk being short-term, fragmented, or politically driven.
Ultimately, when I think about the continuing professionalisation of asset management, I feel incredibly hopeful. Asset management provides a framework to realise all of the positive changes that can be realised from technology. There is always going be hype about different technologies and buzzwords (like AI). Through good asset management we can actually anchor that potential into practical, real things, on the ground, that will actually make a real improvement in infrastructure organisations, the built environment, and ultimately in people’s lives.
Footnotes
(1) Last Week Tonight with John Oliver did a fantastic segment on this…
(2) That was such a cool job! First when working for Network Rail, and then later whilst consulting for CPC Systems with KAD. Both times I had full autonomy to undertake technical investigations, going around the country to speak to our experts and various academics to try to solve complicated engineering problems. I had some fantastic bosses who gave me the support (and space) so that I could be at my best and really get into some very complex challenges. They also gave me the professional respect to genuinely challenge my findings and help me develop robust arguments for change and improvement. If you’d ask me for examples of good engineering leadership I’d have to point to Nigel Wilson, Richard Schofield, Jerry England, Joe Little, Paul Rankin, Matt Slade
(3) Asset Management Landscape
(4) Huge thanks to Chris Charlwood for his contribution!
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