By Berend Booms, Head of EAM Insights, Ultimo
For much of their history, maintenance and asset management have been viewed through the lens of cost control - a necessary overhead to be minimised rather than a strategic function to be cultivated. That perception is changing and changing fast. Over the past two years, Enterprise Asset Management (EAM) has evolved into something far more consequential: a value creator, a board-level priority, and increasingly, a competitive differentiator for asset-intensive organisations navigating one of the most challenging operational environments in recent memory.
A market in transition
The shift has been driven by a confluence of pressures, not least the workforce crisis playing out across industries and geographies. Labour shortages are making skilled maintenance professionals harder to recruit and retain, whilst the median age of maintenance technicians continues to rise. The consequence is that critical operational knowledge - the kind accumulated over decades of hands-on experience - sits with a shrinking pool of individuals and risks disappearing entirely when they find employment elsewhere or stop working altogether.
Forward-thinking organisations have recognised that EAM software offers a practical solution: a means of capturing, centralising, and democratising that institutional knowledge before it walks out the door. In this context, investing in EAM maturity is not simply an IT decision; it is a knowledge retention strategy.
Alongside workforce pressures, the broader operational environment has grown considerably more complex. Geopolitical instability has created a volatile global economy, and supply chains - already fragile following recent years of disruption - remain under constant strain. In sectors such as automotive manufacturing, the inability to source a single critical component can bring an entire production line to a halt. When downtime carries such significant financial consequences, asset reliability moves swiftly up the strategic agenda.
Sustainability imperatives are adding further weight. The transition to net zero means that ESG reporting and energy efficiency have become genuine business requirements rather than aspirational commitments. Managing these obligations demands a level of data quality and process discipline that reactive maintenance simply cannot provide.
From digitisation to optimisation
Perhaps the most significant shift in the EAM landscape, however, has been the arrival of artificial intelligence (AI) as a mainstream expectation rather than an experimental
curiosity. Two or three years ago, many organisations were still in the midst of digitising their operations - moving from paper-based records, deploying mobile devices for the first time, and building the data infrastructure that any intelligent system requires as its foundation. Today, those conversations have moved on. Leadership teams are no longer asking whether to digitise; they are asking how AI can help them optimise.
This change in expectation has been reflected in the development of EAM platforms themselves. AI functionality embedded within modern EAM systems is helping maintenance teams to work faster, smarter, and more collaboratively - surfacing insights from asset data that would previously have gone undetected, flagging emerging failure patterns before they result in unplanned downtime, and enabling more informed decisions about asset investment. The technology has become a significant enabler for boosting employee productivity and maximising asset availability.
The illusion of control
Yet for all these advances, a substantial number of organisations remain stuck in reactive or semi-controlled maintenance. Understanding why requires some honesty about the psychological and structural barriers involved.
In reactive environments, there is often a highly visible and rewarding role for maintenance teams. Responding to a breakdown, diagnosing the fault, and restoring operations carries a certain urgency and satisfaction. Reactive maintenance can feel like the safe strategy - the team knows exactly what to do when something goes wrong. The problem is that responsiveness is not the same as predictability, and it does not build long-term resilience. Repeated failures erode customer trust, damage reputations, and make it progressively harder to establish any clear strategic direction.
Structural factors compound the problem. A lack of clean, reliable data; inadequate governance around the maintenance process; an absence of clearly defined strategy; and insufficient executive sponsorship can all conspire to keep organisations anchored at a particular level of maturity. The longer they remain there, the harder it becomes to modernise. Without the foundational data quality and process discipline required by advanced technologies such as predictive maintenance, organisations find themselves locked in a cycle they cannot easily break.
This inertia carries real commercial risk. Rising maintenance costs, competitive disadvantage, and an inability to scale are the inevitable consequences for businesses that fail to progress.
Software is not a silver bullet
One of the most common misconceptions in the EAM market is that purchasing a software platform is, in itself, a transformation. It is not. Buying software is a transaction; improving asset management maturity is a journey that demands sustained effort across three interconnected dimensions: technology, process, and people.
Technology provides insight and information, but processes must be in place to act on those insights in a consistent, auditable, and repeatable way. Without process governance, even the most sophisticated platform will fail to deliver its potential.
Equally important is the human element. No EAM investment will be successful without a corresponding investment in the people who use it. That means upskilling maintenance
teams, giving them genuine ownership of the system, and helping them understand how the data they generate will be used to support their day-to-day activities and enable better decision-making. The goal is for end users to be as comfortable with their digital tools as they are with their physical toolkit. Where that comfort and confidence is absent, deployment will fall short regardless of the platform's capabilities.
A logical progression
Ultimo's EAM maturity model is comprised of five stages. Reactive, In Control, Proactive, Smart, and Ultimate. This reflects the reality of how organisations evolve rather than how they might like to imagine they do. It is a journey, not a binary switch.
A typical progression begins with the reactive stage, where maintenance is entirely fault driven. Moving into the In Control stage introduces structured processes and the use of historical data to schedule maintenance activities. The Proactive stage applies risk-based strategies to minimise failures and optimise asset availability. At the Smart stage, organisations are using the full breadth of their data to make informed, evidence-based decisions. The Ultimate stage extends that view beyond the EAM system itself, positioning assets within the broader organisational and operational context.
What is striking, and important to acknowledge honestly is that organisations frequently overestimate where they sit on this scale. A business that carries out some preventive maintenance may believe it has reached the Proactive stage, when proactive maturity means genuine optimisation, not simply scheduling work orders. A rigorous assessment looks beyond perception to examine the quality of the asset register, the clarity and depth of the maintenance strategy, compliance and auditability, and the degree to which data is being actively used to drive decisions.
Earning the right to advance
Organisations operating at the Smart or Ultimate stages share a common characteristic: they have shown patience and determination, building their capabilities systematically over years, in many cases, decades. They have not attempted to shortcut the journey by skipping foundational stages in pursuit of the most advanced asset management strategy that is unlocked by growing maturity.
This is perhaps the most important lesson for organisations at earlier stages of maturity. The ambition to implement predictive maintenance or AI-driven decision support is entirely legitimate, but it cannot be fulfilled without first establishing the data quality, process governance, and organisational alignment that those technologies depend upon. Attempting to build advanced strategies on weak foundations does not accelerate progress; it undermines it.
Maturity, in this sense, is not achieved through aspiration. It is achieved through informed, disciplined action — understanding precisely where the organisation stands today, identifying the specific gaps that need to be addressed, and prioritising the initiatives most likely to deliver measurable progress towards the next stage.
For organisations looking to realise a better tomorrow, the path forward begins with an honest assessment of where they stand today.
Ultimo offers organisations the opportunity to carry out an instant EAM maturity self-assessment and book a session with a Solutions Engineer to identify the most pragmatic route to their next maturity stage. See https://www.ultimo.com/about-us/eam-maturity-model/self-assessment#demo for details.
