The
State of
ASSET MANAGEMENT
in Australia & New Zealand
The Obstacles to Achieving Asset, Maintenance, and Reliability Management Excellence
For nearly three decades, the MAINSTREAM research team has engaged with Australian and New Zealand-based Asset, Maintenance, and Reliability leaders to understand their collective challenges and opportunities as they work toward asset management excellence. The 2025 report presents the most pressing obstacles facing organisations today based on extensive research including roundtable discussions, surveys, and in-depth interviews with industry leaders across sectors such as mining, utilities, manufacturing, rail, energy, and defence.
This year’s findings reveal a shifting landscape where traditional challenges persist alongside emerging complexities. Organisations continue to struggle with workforce transitions, data integration, and organisational alignment, while facing new pressures from technological transformation, decarbonisation initiatives, and evolving stakeholder expectations.
The insights gathered in this report enable leaders to benchmark their challenges against peers, understand best practices, and make informed decisions that drive performance improvements within their asset management functions.
Report Highlights
• Critical Skills Crisis: 62% of asset-intensive organisations report critical shortages in maintenance and reliability roles, with projections indicating Australia will face a deficit of approximately 25,000 qualified maintenance professionals by 2027.
• Workforce Knowledge Exodus: 37% of technical knowledge in mining operations is undocumented and resides solely with experienced personnel, with organisations losing approximately 4.5% of critical operational knowledge annually through retirements and staff turnover.
• Digital Disappointment: While 83% of industrial companies have invested in digital asset management technologies, only 34% report achieving their expected return on investment.
• Misalignment Costs: Strategic misalignment between corporate objectives and asset management execution costs Australian asset-intensive industries approximately AUD $4.3 billion annually.
• Mental Health Impact: Maintenance professionals in heavy industry experience mental health challenges at rates 23% higher than the general workforce, costing Australian industry approximately AUD $13.6 billion annually in reduced productivity, increased accidents, and higher turnover.
• Productivity Gap: Australian industrial organisations average only 29% wrench time for maintenance personnel, significantly below the international best practice benchmark of 55-60%.
• AI Implementation Struggles: While 72% of asset-intensive organisations are exploring AI applications, 76% of these initiatives fail to achieve expected returns due to poor implementation.
• Data Overwhelm: 78% of organisations report collecting more maintenance data than they can effectively analyse, with maintenance professionals spending 14.6 hours per week (38% of their time) searching for, validating, or reconciling data.
• Decarbonisation Challenge: Industrial decarbonisation will require the modification or replacement of approximately AUD $893 billion in existing assets across Australian industry by 2050.
• Diversity Dividend: Organisations with more gender-diverse maintenance teams experienced 23% fewer unplanned equipment failures and 17% higher availability rates, yet women represent only 16.8% of the maintenance workforce.
• Safety-Maintenance Connection: 27% of serious workplace incidents in heavy industry have maintenance-related contributing factors, yet only 28% of organisations have achieved substantial integration between safety and asset management functions.
Shifting Workforce Dynamics and Knowledge Retention
One of the most pervasive challenges facing asset-intensive organisations remains the changing workforce landscape. The demographic shift is accelerating as experienced personnel retire, taking with them decades of institutional knowledge, while organisations struggle to attract and develop new talent.
According to Engineers Australia’s 2024 Engineering Skills Forecast, 62% of organisations in asset-intensive industries report critical shortages in maintenance and reliability engineering roles. The forecast projects that Australia will face a deficit of approximately 25,000 qualified maintenance professionals by 2027 if current trends continue.
A 2024 analysis by the Australian Industry Group reveals that maintenance technician positions take 83% longer to fill compared to five years ago, with regional operations facing even greater recruitment challenges.
The Australian Institute of Mining and Metallurgy’s workforce study found that 37% of
technical knowledge in mining operations is undocumented and resides solely with experienced personnel. Their research suggests organisations lose approximately 4.5% of critical operational knowledge annually through retirements and staff turnover.
“We’re experiencing a perfect storm — losing experienced people faster than we can replace them, while also dealing with changing skill requirements due to new technologies and decarbonisation. It’s not just about filling positions; it’s about transferring critical knowledge before it walks out the door.”
Maintenance Manager, Power Generation
Our research indicates that 68% of organisations report critical knowledge gaps in technical roles, with 47% having trouble filling specialised maintenance and reliability positions. This challenge is particularly acute in regional and remote operations, where competition for skilled labour has intensified.
We have to create a capable, balanced and stable workforce in an unbalanced and unstable economic/political environment.
Head of Asset Management, Aviation & Defence
of organisations in asset-intensive industries report critical shortages in maintenance and reliability engineering roles
The nature of workforce challenges has evolved from previous years in several ways:
How Different Generations Approach Things
Different learning styles and career expectations between experienced workers and newer generations require organisations to rethink knowledge transfer mechanisms. While experienced workers often relied on memorised procedures and informal knowledge sharing, younger workers expect digital access to information and structured development pathways.
“The newer workforce wants to understand the ‘why’ behind everything. They won’t just follow procedures because ‘that’s how we’ve always done it.’ They expect information to be accessible digitally, and they’ll question established practices, which can actually drive improvement if we manage it properly.”
Reliability Lead, Mining
Research from Deakin University’s Centre for Workplace Futures indicates that Generation Z workers in technical roles
are 3.2 times more likely to seek employment elsewhere if they perceive knowledge is being hoarded rather than shared.
The Australian Manufacturing Growth Centre has identified that companies implementing cross-generational mentoring programs see a 28% improvement in time-to-competency for new maintenance professionals and a 36% increase in retention of institutional knowledge when senior staff retire.
Digital Skill Requirements
The increasing digitalisation of asset management has created new skill demands that traditional training pathways may not address. Organisations report significant gaps in data analysis, automation, and technology integration skills, even among technically proficient staff.
Most organisations that participated in our research have implemented or are implementing at least one new digital solution in their maintenance function, but only a small group feel they have adequate internal capabilities to maximise the value of these investments.
Asset Data Management: Transforming Data Overload into Strategic Value
One of the most significant challenges facing maintenance and reliability leaders today is effectively managing and extracting value from the overwhelming volumes of data generated by ERP and APM systems, condition monitoring technologies, sensors, manual processes, drones, and other advanced equipment. While organisations have unprecedented capabilities to collect data, they struggle to transform this information into actionable insights that drive meaningful business decisions.
According to a 2024 study by the Australian Industrial Transformation Institute, 78% of asset-intensive organisations report collecting more maintenance and reliability data than they can effectively analyse, with only 23% indicating they systematically convert this data into actionable business insights.
The MAINSTREAM 2025 Benchmark Report found that organisations with mature data management practices achieve 37% higher asset perfor-mance, and 29% lower maintenance costs compared to those with ad hoc approaches.
A comprehensive survey by Deakin University’s Centre for Digital Enterprise found that maintenance and reliability professionals spend an average of 14.6 hours per week searching for, validating, or reconciling data across multiple systems, representing approximately 38% of their available work hours.
“The biggest challenge we have is capturing the relevant data at the right time. We often have too much data or not enough to make a meaningful decision.”
Asset Manager, Utilities
Research indicates that while 91% of organisations view data as a strategic asset, only 34% have implemented formal data governance frameworks for maintenance and reliability information. The key challenges include:
Data Quality and Integrity Issues
Poor data quality remains a fundamental barrier to effective analytics and decision-making. According to the Australian Bureau of Statistics’ 2024 Digital Business
Data quality isn’t a problem, finding ways to clearly communicate the data is the real challenge.
Maintenance Manager, Infrastructure
Indicators report, maintenance professionals rate the reliability of their asset data at just 5.8 out of 10 on average, with data inconsistency identified as the primary concern.
“The taxonomy has to be really, really good in terms of your naming convention for your parts, because if it’s not, it can create absolute chaos.”
Reliability Manager, Energy
System Fragmentation and Data Silos
Organisations continue to struggle with disparate systems that don’t communicate effectively. The Australian Digital Transformation Agency’s 2024 industrial assessment found that asset-intensive organisations operate an average of 11.3 separate systems containing critical asset information, with only 26% achieving meaningful integration between these platforms.
Analytical Capability and Skills Gap
Organisations face significant challenges in developing the specialised capabilities needed to translate maintenance data into business insights. According to Engineers Australia’s 2024 Skills Forecast, 71% of organisations report critical shortages in data science and analytics skills specific to asset management.
Contextual Intelligence Deficiencies
A fundamental limitation in many data management approaches is the lack of contextual intelligence—the ability to un -
derstand data within its operational environment. Raw asset data without context has limited value for decision-making, yet most data collection systems capture metrics without the surrounding operational conditions, maintenance history, and business constraints that give them meaning.
This contextual deficit significantly reduces the usefulness of historical data for predicting future performance or optimising maintenance strategies. Organisations that have made progress in this area have implemented structured approaches to capture and integrate contextual information alongside traditional asset performance data, enabling more nuanced and accurate analyses.
Information Lifecycle Management Challenges
As data volumes grow exponentially, organisations face increasing challenges in managing information throughout its lifecycle. Most lack structured approaches for data retention, archiving, and eventual disposal, leading to bloated systems that compromise performance and create compliance risks.
The absence of effective information lifecycle management creates particular challenges when decommissioning legacy systems or migrating to new platforms. Without clear processes for identifying and preserving critical historical data, organisations risk losing valuable information during these transitions, potentially compromising longterm asset management effectiveness.
of asset-intensive organisations report collecting more maintenance and reliability data than they can effectively analyse
Strategic Approaches
Leading organisations are addressing these challenges through multifaceted strategies:
• Implementing robust data governance frameworks with clear ownership, quality standards, and lifecycle management for asset information
• Creating cross-functional data teams that combine maintenance domain expertise with data science capabilities
• Developing comprehensive master data management strategies to ensure consistency across systems and processes
• Implementing targeted data literacy programs for maintenance and reliability professionals
These approaches enable organisations to transform their data from an overwhelming burden into a strategic asset that drives performance improvement, cost reduction, and risk mitigation across their asset portfolios. 78%
• Creating clear data-to-decision pathways that connect information gathering to specific business outcomes and performance metrics
• E stablishing data quality measurement frameworks that track improvements and identify priority areas for enhancement
• Implementing integrated asset intelligence platforms that reduce system fragmentation and provide holistic views of asset performance
Alignment Between Asset Strategy and Enterprise Objectives
Despite years of industry focus on strategic asset management principles, a persistent gap remains between enterprise strategy and asset management execution. This misalignment frequently results in conflicting priorities, inefficient resource allocation, and suboptimal decisions.
Research from the MAINSTREAM 2025 Benchmark Report shows that organisations with strong alignment between asset strategies and corporate ob-jectives achieve 32% higher return on assets compared to those with poor alignment. How-ever, the same survey indicates that only 26% of Australian asset-intensive organisations have formal mechanisms to translate corpo-rate strategy into asset management plans
Survey respondents identified this align-ment challenge as a significant barrier:
“Our biggest challenge is alignment and prioritisation across multiple departments on the key value adding tasks.”
Supervisor, Oil & Gas
A study by the University of Wollongong’s Asset Management Research Group found that 71% of asset failures with significant business impact could be traced to misalignment between corporate strategy and maintenance execution. Their research indicates that strategic misalignment costs Australian asset-intensive industries approximately AUD $4.3 billion annually through suboptimal resource alloca -
tion and missed improvement opportunities.
Our research indicates that only 23% of organisations believe their asset management strategy is fully aligned with and understood within the broader organisation. The primary challenges include:
Communication Barriers
Technical teams frequently struggle to communicate asset needs in terms that resonate with executive leadership. The inability to translate technical requirements into business language creates barriers to obtaining necessary support and resources.
“We’re engineers — we speak the language of reliability, condition assessment, and risk mitigation. The executive team speaks the language of market share, profit margins, and shareholder returns. When we can’t connect these worlds effectively, our initiatives don’t get prioritised.”
Asset Strategy Manager, Manufacturing
Competing Timeframes
A fundamental tension exists between the long-term perspective required for optimal asset management and the shorter-term focus of many business planning processes. This is particularly evident in publicly traded companies facing quarterly reporting pressures.
Survey data indicates that 67% of asset managers believe their organisations prioritise short-term cost reduction over long-term
67% of asset managers believe their organisations prioritise short-term cost reduction over long-term asset performance
Our executives talk about asset performance being critical to business success, but when it comes to resource allocation, maintenance is still treated primarily as a cost centre rather than a value driver. We’re constantly fighting for investment that would actually improve overall business performance.
Head of Asset Management, Energy Distribution
Technology Integration and Digital Transformation Challenges in Asset Management
The proliferation of digital technologies has created both opportunities and significant challenges for asset-intensive organisations. Our research reveals growing frustration with the gap between the promised benefits of digital solutions and the realised value.
“We’ve implemented five different digital solutions in the past three years, but we’re still struggling to integrate them effectively. We have more data than ever, but extracting actionable insights remains challenging, and user adoption has been inconsistent at best.”
Asset Intelligence Manager, Water Utility
A 2024 KPMG survey of Australian industrial companies found that while 83% have invested in digital asset management technologies in the past three years, only 34% report achieving their expected return on investment.
The same survey revealed that organisations with mature data governance frameworks were 2.4 times more likely to achieve targeted benefits from digital transformations.
A recent report from the Digital Transformation Agency of Australia found that asset-intensive industries spend an average of 3.7% of revenue on digital initiatives, yet 62% of these projects fail to meet their objectives.
The primary challenges in technology integration include:
System Fragmentation and Data Silos Organisations continue to struggle with disparate systems that don’t communicate effectively. Survey respondents report an average of 8-12 separate systems containing critical asset information, making it difficult to obtain a comprehensive view of asset performance.
We struggle to ensure operational readiness and getting teams (both processes and systems) ready for digital transformation. It’s a challenge to balance proactive maintenance, limited resources, and integrating new technologies to boost efficiency and enhance capabilities.
Specialist Lead, Manufacturing
“If I want to understand everything about a critical pump, I need to access the CMMS for maintenance history, a separate condition monitoring system for vibration data, the process control system for operational parameters, the document management system for technical specifications, and the financial system for cost information. It’s incredibly inefficient and creates data integrity issues.”
Engineering Manager, Manufacturing
Research by the Cooperative Research Centre for Industrial Transformation indicates that maintenance technicians spend up to 23% of their work time navigating between different information systems, representing a significant productivity loss.
“We have increased complexity related to use of the network. WE have to get better at streamlining data from maintenance and inspection teams in a way that helps inform our decision making.”
Maintenance Manager, Power & Water Utilities
Data Quality and Integration Issues
Poor data quality remains a significant barrier to effective analytics and decision-making. While organisations have improved data collection capabilities, many still struggle with standardisation, completeness, and accuracy. Only 24% of survey respondents expressed confidence in the quality of their maintenance and reliability data.
Change Management and User Adoption
Technology implementations frequently falter at the adoption stage, with technical solutions outpacing organisational readiness. Success stories consistently highlight the im -
portance of user involvement in solution design and comprehensive training programs.
“We spent millions on an advanced asset performance management system but underestimated the change management aspects. Two years in, we’re still struggling with basic data entry compliance because the frontline teams don’t see the value in the additional work required of them.”
Maintenance Superintendent, Mining
Balancing Innovation with Fundamentals
A recurring theme in the roundtables was the tension between implementing advanced technologies and maintaining excellence in fundamental maintenance practices. Organisations often pursue digital solutions before establishing the foundational processes necessary for success.
“We jumped straight to predictive analytics before we had reliable preventive maintenance processes in place. The result was sophisticated algorithms trying to analyse poor quality data from inconsistently performed inspections. We had to take a step back and fix the basics first.”
Reliability Manager, Rail
The Digital Vision-Reality Gap
A significant but often unaddressed challenge is the substantial gap between executive vision for digital transformation and the operational realities of implementation. Many digital initiatives are launched with ambitious expectations shaped by vendor promises and industry hype, but without adequate appreciation of the underlying complexity in asset-intensive environments.
Work Management and Business Process Optimisation
Effective work management remains a foundation of asset management excellence, yet many organisations continue to struggle with optimising the core processes that drive maintenance efficiency and effectiveness. The research reveals significant opportunities for improvement in planning, scheduling, and execution disciplines.
According to the MAINSTREAM 2025 Benchmark Report, Australian industrial organisations average only 29% wrench time for maintenance personnel, significantly below the international best practice benchmark of 55-60%. The same study found that effective planning and scheduling processes could increase this productivity by up to 70%.
Process optimisation and work man-agement challenges figured prominently in our survey responses:
“We have under-invested in the basic tools and fundamentals which reduces the capability, efficiency and abilities to showcase to higher management and therefore the business the long-term benefits of applying good reliability and maintenance.”
Specialist Lead, Power & Water Utilities
Research by the University of South Australia’s Industrial Optimisation Group indicates that maintenance teams spend an average of 31% of work time waiting for parts, documentation, or access to equipment due to planning and coordination deficiencies.
Our research indicates that organisations estimate an average of 35% of maintenance labour hours are wasted due to inefficient processes, with planning and scheduling deficiencies being the primary contributors. The key challenges include:
We’ve invested in sophisticated technologies and predictive tools, but we still struggle with basic work management fundamentals. The reality is that no amount of advanced analytics can compensate for poor execution of maintenance tasks or inadequate planning.
Maintenance Manager, Mining
Process Adherence and Discipline
Organisations frequently develop comprehensive work management processes but struggle with consistent execution. Only 41% of survey respondents reported high levels of compliance with established planning and scheduling procedures.
“The gap between our documented processes and actual practice is significant. We have detailed procedures for planning, scheduling, and job closure — but in the daily rush to keep production running, these disciplines often get compromised.”
Planning Lead, Manufacturing
Resource Constraints
Dedicated planning and scheduling resources are often insufficient, leading to reactive approaches and compressed timeframes. Survey data indicates that 56% of organisations have fewer planning resources than their documented processes require.
Information Quality and Accessibility
Maintenance teams frequently lack access to comprehensive information needed for effective job planning. Technical documentation, previous job histories, and asset condition data may be fragmented across multiple systems or unavailable at the point of need.
“Our frontline maintainers spend excessive time searching for information that should be readily available — equipment manuals, previous solutions to similar problems, isolation procedures. This significantly impacts productivity and job quality.”
Maintenance Superintendent, Rail
Cross-Functional Coordination Challenges
The interfaces between maintenance and other functions—particularly operations, supply chain, and engineering—create persistent friction points that undermine work management effectiveness. The handoffs between these groups often lack clear protocols, creating delays, miscommunication, and missed opportunities.
Our research reveals that coordination inefficiencies at these interfaces account for approximately 42% of maintenance execution delays. The most common pain points include production release negotiations, parts availability, and engineering support for technical issues during execution. Organisations with mature work management systems have established formal interface agreements that clearly define responsibilities, communication protocols, and escalation pathways.
Digital Work Management Capability Gaps
The transition from paper-based to digital work management systems has created new challenges that many organisations struggle to address effectively. While digital platforms offer significant potential benefits, they also introduce new failure modes and capability requirements that weren’t necessary in traditional systems.
Organisations report significant challenges in areas such as digital work package design, mobile technology utilisation, and integration of real-time data into planning processes. These capabilities require different skill sets than traditional planning approaches, creating development needs that many organisations have not adequately addressed.
Reliability Engineering Capability Development
The critical role of reliability engineering in driving asset performance continues to be underappreciated in many organisations. Our research indicates a growing capability gap as reliability requirements increase due to economic pressures, ageing assets, and changing operating contexts.
Engineers Australia’s 2024 workforce capability assessment identified reliability engineering as one of the top five skill shortage areas across Australian industry, with 67% of organisations reporting difficulty filling these specialised positions.
“Reliability engineering should be central to our asset management approach, but in practice, it’s often marginalised. We expect reliability engineers to drive improvement, but don’t provide the organisational support, clear role definition, or career pathways to make them successful.”
Asset Strategy Manager, Energy
Survey data indicates that while 82% of organisations identify reliability improvement as a strategic priority, only 37% believe they have adequate reliability engineering capabilities to achieve their objectives. The key challenges include:
Role Definition and Expectation Clarity
Many organisations have unclear expectations for reliability engineers, resulting in role confusion and misaligned activities. Engineers may be pulled into reactive
problem-solving rather than focusing on systemic improvement opportunities.
Analytical Capability Gaps
The increasing complexity of reliability analysis requires sophisticated statistical and data interpretation skills. Organisations report significant gaps in capabilities such as failure mode analysis, statistical process control, and root cause analysis techniques.
Influence and Authority Limitations
Reliability engineers frequently lack the organisational influence to drive change, particularly when improvement opportunities cross departmental boundaries or require operational compromises.
“Our reliability engineers can identify improvement opportunities, but implementing recommendations often requires influencing production schedules, capital expenditure decisions, or operational practices. Without sufficient organisational authority, their effectiveness is limited.”
Engineering Manager, Oil & Gas
Reliability Culture Barriers
Beyond technical skills and organisational positioning, reliability engineers face significant cultural challenges in environments where short-term production priorities consistently override long-term reliability considerations. This cultural context undermines even well-designed reliability initiatives and creates persistent barriers to sustainable improvement.
67% of organisations reported difficulty filling specialised reliability engineering positions
Our reliability engineers spend most of their time responding to the latest failure rather than analysing patterns and driving preventive strategies. Without clear protection of their time for proactive work, they default to firefighting mode.
Maintenance Manager, Manufacturing
Our research indicates that organisations with strong reliability performance have established explicit cultural norms that balance immediate production needs with long-term reliability requirements. These organisations have developed leadership behaviours and decision-making frameworks that visibly prioritise reliability alongside productivity, creating the cultural foundation necessary for effective reliability engineering.
Integration of Advanced Analytics into Reliability Practices
A growing challenge is effectively integrating advanced analytics capabilities into traditional reliability engineering practic -
Strategic Approaches
es. While these technologies offer significant potential for identifying complex failure patterns and optimising maintenance strategies, organisations struggle to blend data science approaches with domain expertise in ways that deliver practical value.
This integration challenge has both technical and organisational dimensions. On the technical side, reliability engineers often lack the statistical and programming skills to effectively leverage advanced analytics. Organisationally, many companies struggle to create effective collaboration models between data scientists and reliability specialists that combine the strengths of both disciplines.
Organisations successfully developing reliability capabilities are:
• Creating clear role definitions with protected time for proactive analysis
• Developing reliability governance structures that provide implementation pathways for improvement recommendations
• Implementing structured training programs covering both technical and influence skills
• Establishing formal reliability improvement processes integrated with work management systems
• Creating communities of practice to share knowledge across operational units
• Providing career pathways that recognise and reward reliability expertise
Decarbonisation and Sustainability Pressures
A significantly intensified challenge compared to previous years is the pressure to adapt asset management practices to support decarbonisation and broader sustainability goals. Organisations across sectors report increasing stakeholder expectations, regulatory requirements, and economic incentives driving fundamental changes in how assets are designed, operated, and maintained.
According to the Clean Energy Regulator’s 2024 industry report, 84% of large industrial companies in Australia have established formal emissions reduction targets, with 62% targeting net-zero emissions by 2050.
Survey respondents highlighted sustainability challenges affecting asset management practices:
“Ageing fleet and changes in asset service have soon, certain and often severe impacts from a reliability perspective... The biggest challenge – how do we balance the commercial agility requirement, that keeps us in business, with the longer-term asset management sustainability?”
Maintenance Manager, Rail & Transport
Research from CSIRO indicates that industrial decarbonisation will require the modification or replacement of approximately AUD $893 billion in existing assets across Australian industry by 2050, creating unprecedented asset transition management challenges.
Research indicates that 78% of asset-intensive organisations have established carbon reduction targets, but only 34% have fully integrated these commitments into their asset management strategies. The key challenges include:
Managing Asset Transition Periods
Many organisations are operating hybrid asset portfolios combining traditional and low-carbon technologies, creating complex transition management challenges. Different maintenance approaches, skill requirements, and performance metrics may apply across the portfolio.
“We’re maintaining ageing fossil fuel assets while simultaneously introducing renewable technologies. The first set needs to remain reliable during a planned phase-out period, while the second involves new technologies with limited operating history. Balancing these conflicting asset strategies is incredibly complex.”
Maintenance Manager, Power Generation
Changing Reliability Parameters
Low-carbon technologies often present different reliability characteristics and failure modes compared to traditional assets. Organisations report significant challenges in developing appropriate maintenance strategies for technologies with limited operating history or different performance characteristics.
Skill and Knowledge Gaps
The transition to sustainable technologies is creating urgent requirements for new tech -
Decarbonisation is transforming everything from our asset selection criteria to our maintenance strategies to our workforce skill requirements. It’s not just about complying with regulations; it’s reshaping our entire business model and asset lifecycle management approach.
Head of Engineering, LNG Production
nical skills. Survey data indicates that 82% of organisations anticipate significant workforce capability gaps related to low-carbon technologies within the next three years.
“Our maintenance team has decades of experience with combustion engines and hydraulic systems. Now we’re asking them to maintain electric drivetrains, battery storage systems, and hydrogen infrastructure. The knowledge gap is enormous, and traditional training pathways haven’t caught up yet.”
Fleet Manager, Mining
Circular Economy Integration Challenges
Beyond carbon reduction, organisations are grappling with broader circular economy principles that fundamentally challenge traditional asset lifecycle management. These approaches require consideration of material recoverability, component reuse, and design for disassembly—concepts that weren’t part of traditional asset management frameworks.
Strategic Approaches
The circular economy transition introduces new complexities in asset strategy, from procurement specifications that consider end-of-life recovery to maintenance practices that preserve component reusability. Organisations report significant gaps in both frameworks and capabilities to address these emerging requirements.
Investment Justification in Transitional Contexts
A particularly challenging aspect of the sustainability transition is justifying investments in existing carbon-intensive assets that may have shortened service lives due to decarbonisation targets. Maintenance and reliability professionals struggle to secure funding for assets planned for phaseout, even when these investments would deliver positive returns within the transition timeframe.
This creates a serious risk of accelerated degradation in critical infrastructure during transition periods, with potential impacts on safety, reliability, and operational performance. Organisations report difficulties in developing appropriate investment frameworks that balance transition objectives with operational requirements during extended phase-out periods.
Leading organisations are addressing these challenges through:
• Creating dedicated transition management teams with expertise in both traditional and emerging technologies
• Developing comprehensive asset transition roadmaps aligned with carbon reduction commitments
• Partnering with equipment manufacturers and technology providers on training programs
• Implementing pilot projects to build organisational capability before full-scale deployment
• Adapting reliability frameworks to accommodate different performance parameters of low-carbon technologies
• Engaging with industry associations and research institutions to share emerging practices
Artificial Intelligence Integration: Opportunities and Implementation Challenges
The rapid advancement of artificial intelligence technologies presents both significant opportunities and complex implementation challenges for maintenance and reliability functions. Our research indicates growing interest but considerable uncertainty regarding how to effectively leverage AI to transform asset management practices.
“AI has moved from a theoretical concept to a practical tool with real applications in our maintenance operations. The challenge isn’t whether to adopt these technologies anymore — it’s how to implement them effectively, build workforce capabilities, and integrate them with our existing systems and processes.”
Digital Transformation Lead, Mining
According to a 2024 study by CSIRO’s Data61, 72% of Australian asset-intensive organisations are exploring or implement-
ing AI applications in maintenance and reliability, yet only 23% report achieving significant operational benefits to date.
“One of our most pressing challenges is to create a safe internal AI environment.”
Head of Asset Management, Aviation & Defence
A comprehensive analysis by the Australian National University’s Autonomous Systems Laboratory found that organisations implementing AI-driven predictive maintenance solutions achieve an average 41% reduction in unplanned downtime and 23% decrease in maintenance costs when the implementation is supported by robust change management and data governance. However, their research also indicates that 76% of AI initiatives in asset management fail to achieve expected returns due to poor implementation approaches rather than technology limitations.
There’s a critical shortage of people who understand both AI technologies and the practical realities of maintenance operations. We need translators who can bridge these domains to identify valuable use cases and implement effective solutions.
Asset Strategy Manager, Utilities
72% of Australian asset-intensive organisations are exploring or implementing AI applications in maintenance and reliability
Data Quality and Accessibility Limitations
AI systems require massive amounts of high-quality, labelled data to deliver reliable results. Many organisations struggle with fragmented, inconsistent, or incomplete maintenance and asset performance data, severely limiting AI effectiveness.
“We’ve implemented sophisticated AI tools only to discover that our historical maintenance data wasn’t recorded consistently enough to train reliable algorithms. We’ve had to take a step back and focus on improving data capture practices before we can realise the potential benefits.”
Reliability Manager, Manufacturing
Research by the Australasian Centre for Data Innovation indicates that organisations typically need 18-24 months of consistent, high-quality data collection before machine learning algorithms can deliver reliable predictions for complex equipment.
Workforce Capability Gaps
Organisations report significant challenges in developing the specialised capabilities needed to implement and leverage AI effectively. This includes both technical skills in data science and machine learning, and the domain expertise needed to apply these technologies to maintenance and reliability challenges.
Trust and Change Management
Building workforce trust in AI-driven recommendations represents a significant challenge, particularly for safety-critical decisions. Organisations report resistance from experienced maintenance personnel who question algorithmic recommendations that contradict their experience-based judgment.
The Operational Context Challenge
A frequently overlooked barrier to AI implementation is the dynamic nature of operational contexts in asset-intensive environments. Unlike consumer applications that operate in relatively stable environments,
industrial AI must contend with frequent changes in operating parameters, maintenance practices, and equipment configurations that can invalidate established models.
“Our maintenance technicians have decades of experience and have developed strong intuition about equipment health. When an AI system contradicts that intuition, they’re understandably sceptical. Building trust requires transparency, involvement in system design, and demonstrating reliability over time.”
Maintenance Superintendent, Oil & Gas
This contextual volatility creates significant challenges for model development and maintenance, requiring sophisticated approaches to detect context shifts and adapt accordingly. Organisations report that maintaining model relevance in changing operational environ -
Strategic Approaches
ments often requires more ongoing effort than initial development, creating resource demands that weren’t anticipated in project planning.
Ethical and Governance Considerations
As AI applications move from peripheral support tools to central components of critical decision processes, organisations face complex ethical and governance questions that few are prepared to address. These include issues around decision accountability, transparency requirements, workforce impacts, and appropriate boundaries for automation.
Our research indicates that less than 15% of organisations implementing AI in asset management have established formal governance frameworks addressing these considerations. This governance gap creates significant risks, particularly as applications expand into safety-critical decisions and areas with major operational or financial implications.
Organisations successfully integrating AI into maintenance and reliability functions are implementing several key strategies:
• Starting with clearly defined use cases that address specific business problems rather than implementing AI for its own sake
• Investing in data quality and governance as a foundation for AI applications
• Creating cross-functional teams that combine data scientists with experienced maintenance personnel
• Implementing staged adoption approaches that build trust through demonstrated success
• Developing specialised training programs that build both technical and domain-specific AI capabilities
• Establishing clear processes for validating AI recommendations, particularly for safetycritical decisions
• Creating transparent AI systems that can explain their recommendations in terms maintenance personnel understand
64% of organisations report increasing mental health challenges among maintenance & reliability personnel
Strategic Approaches
Organisations addressing these challenges effectively are implementing multi-faceted strategies:
• Incorporating mental health considerations into job design and workload planning
• Training supervisors and managers to recognise and respond to wellbeing concerns
• Creating peer support networks specific to maintenance and reliability functions
• Implementing fatigue management programs incorporating both work and home factors
• Designing change management approaches that acknowledge cumulative impacts
• Providing targeted support during critical periods such as shutdowns and major projects
staffing levels, creating overtime requirements and reduced recovery time between shifts.
“Our maintenance planners are constantly juggling competing priorities with insufficient resources. They know the potential consequences of poor decisions — both for asset performance and safety — and that pressure takes a toll over time.”
Reliability Engineer, Manufacturing
Organisational Change Fatigue
Continuous change initiatives, system implementations, and organisational restructures have created change fatigue in many organisations. This is particularly evident in sectors undergoing significant business model transitions, such as energy and utilities.
“Our teams have experienced three major system changes, two organisational restructures, and the introduction of multiple new technologies in just the past two years. Even positive changes create stress and uncertainty when they come too quickly and without adequate support.”
Asset Manager, Energy Distribution
High-Consequence Decision Pressure
Maintenance and reliability professionals face unique psychological pressures associated with
high-consequence decision environments. The knowledge that equipment failures can lead to safety incidents, environmental damage, or significant financial losses creates a burden that accumulates over time, particularly in contexts where resources are constrained.
This decision pressure is especially pronounced for professionals working with ageing assets or in operations with limited redundancy, where the margin for error is minimal. The psychological impact of this responsibility is often underestimated in organisational support systems designed primarily for operational roles.
Time-Critical Maintenance Windows
The compressed timeframes of planned outages and shutdowns create intense pressure periods that significantly impact mental wellbeing. During these critical windows, maintenance professionals often work extended hours in high-pressure environments with substantial consequences for delays or quality issues.
Our research indicates that these high-intensity periods contribute disproportionately to burnout and mental health challenges, yet few organisations have developed specific support strategies for these predictable pressure points. Leading organisations are beginning to apply the same intensity to planning for human sustainability during these periods as they do for technical execution.
27%
of serious workplace incidents in heavy industry have maintenancerelated contributing factors
System and Data Fragmentation
Different functional areas typically use separate systems with limited integration. Safety incidents, near-misses, hazard reports, risk assessments, and maintenance activities are often recorded in isolation, making it difficult to identify patterns and relationships.
“We had a safety incident involving equipment failure but couldn’t easily connect it to previous maintenance deferrals that might have contributed. The maintenance history was in the CMMS, the risk assessment in a different system, and the incident investigation in yet another platform.”
Maintenance Manager, Manufacturing
Competing Priorities and Resource Allocation
Without integrated decision frameworks, organisations struggle to allocate resources effectively across safety improvements, reliability initiatives, and production requirements. This frequently results in reactive approaches to compliance rather than proactive risk management.
Siloed Expertise and Knowledge
Safety specialists, risk managers, and maintenance professionals often have limited understanding of each other’s domains. This creates communication barriers and reduces the effectiveness of collaborative approaches to asset performance and risk management.
Risk Ownership Disconnects
A fundamental challenge in integration efforts is confusion around risk ownership and accountability. Asset risks frequently span multiple organisational boundaries, with no single function having complete visibility or control. This creates scenarios where risks are either duplicated across multiple systems with inconsistent assessments or, more dangerously, fall into gaps between functional responsibilities.
Our research found that organisations struggle particularly with integrating operational risks that manifest through complex interactions between equipment condition, operating practices, environmental factors, and human behaviours. These multifactorial risks require collaborative approaches that traditional siloed risk management systems cannot adequately address.
Regulatory Compliance vs. Operational Reality
The increasing complexity of safety and environmental regulations creates tensions between compliance documentation and operational effectiveness. Maintenance and operations personnel report growing frustration with compliance systems that they perceive as disconnected from operational realities and adding administrative burden without proportional risk reduction.
This disconnect is particularly evident in documentation requirements that don’t align with field conditions or practical constraints. Organisations that successfully navigate this challenge have found ways to design integrated systems that satisfy regulatory requirements while supporting, rather than hindering, operational effectiveness.
Strategic Approaches
Leading organisations are making progress through:
• Implementing integrated asset performance management platforms that incorporate safety, risk, and maintenance data
• Creating cross-functional teams with responsibility for holistic asset performance
• Developing common risk assessment frameworks that apply across operational domains
• Training maintenance personnel in safety management principles and safety professionals in asset management concepts
• E stablishing shared key performance indicators that highlight the connections between safety outcomes and asset reliability
The talent shortage in maintenance and reliability roles is partly self-inflicted. We’re competing for a limited pool of candidates because we haven’t effectively engaged with diverse talent sources or created truly inclusive workplace cultures where different perspectives can thrive.
Head of Asset Management, Rail 16.8%
Women in the maintenance and reliability workforce in Australian heavy industry
Conclusion and Future Outlook
The asset management profession in Australia and New Zealand continues to evolve in response to changing business expectations, technological capabilities, and workforce dynamics. While many of the fundamental challenges remain consistent with previous years, their manifestations and potential solutions are evolving.
The 2025 research highlights both persistent challenges and emerging trends that will shape asset management practices in the coming years. The interconnected nature of these challenges requires integrated approaches that address multiple dimensions simultaneously.
“We are currently in a build phase so project handover to business as usual is a challenge, incomplete documentation, poor maintenance routines with low detail, not good spares identification etc handed over in a constrained capex, opex and head count environment.”
Maintenance Manager, Power & Water Utilities
This statement from a survey respondent encapsulates the multifaceted nature of the challenges facing asset management professionals, where workforce, data, process, and financial pressures interact to create complex operational environments.
Several key trends will shape the asset management landscape in the coming years:
Integrated Technology Ecosystems
The fragmented technology landscape will gradually evolve toward more integrat-
ed ecosystems as organisations recognise the limitations of siloed solutions. This will require deeper collaboration between operational technology and information technology functions, as well as more sophisticated approaches to data governance.
“Integrated data management including financial, resource management, maintenance program and reliability insights.”
Specialist Lead, Power & Water Utilities
Industry research from Gartner indicates that by 2026, 65% of asset-intensive organisations will implement integrated asset intelligence platforms that combine condition monitoring, CMMS, ERP, and analytics functions.
Workforce Transformation
The demographic transition will accelerate, forcing organisations to implement more systematic knowledge management approaches and redesign roles to accommodate changing workforce expectations. This will create opportunities for innovation in work organisation and capability development.
The Australian Industry Group projects that by 2027, more than 40% of current maintenance professionals in asset-intensive industries will retire or change careers, creating an unprecedented knowledge transfer challenge.
Decarbonisation Integration
Sustainability considerations will become increasingly embedded in asset management decision-making rather than managed as sepa -
rate initiatives. This will drive evolution in asset lifecycle management practices, performance metrics, and technical skill requirements.
A 2024 analysis by the Climate Council of Australia projects that by 2030, over 35% of industrial assets will require modification or replacement to meet emissions reduction commitments.
Holistic Performance Management
Leading organisations will continue to break down traditional silos between safety, reliability, and operational functions, creating more integrated approaches to asset performance management. This will create opportunities for more sophisticated risk-based decision-making across asset portfolios.
Research from MAINSTREAM projects that organisations implementing integrated asset performance management frameworks will achieve 26-38% improvements in overall equipment effectiveness compared to those maintaining siloed approaches.
Adaptive Resilience Development
Beyond traditional reliability approaches, organisations are increasingly focusing on developing adaptive resilience—the ability to maintain critical functions through disruptions that exceed design parameters. This shift recognises that in a world of increasing uncertainty, perfect prediction and prevention are impossible, making recovery capabilities equally important as failure prevention.
This evolution extends traditional asset management thinking beyond avoiding failures to encompassing rapid detection, effective response, and accelerated recovery. Leading organisations are incorporating these resilience principles into their asset strategies,
maintenance approaches, and workforce capability development—creating systems that can withstand unexpected disruptions whether from climate events, supply chain failures, or other emerging threats.
Ethics and Responsibility in Asset Decisions
As social expectations evolve, organisations face increasing scrutiny regarding the broader impacts of their asset management decisions. This extends beyond compliance to encompass ethical considerations around community impacts, environmental stewardship, and social responsibility.
Forward-thinking organisations are developing frameworks that explicitly incorporate these dimensions into asset lifecycle decisions, recognising that social license to operate depends increasingly on demonstrating responsible asset stewardship. This trend will continue to reshape how organisations approach major asset decisions, from design choices to end-of-life strategies.
Organisations that can effectively address these challenges while maintaining excellence in fundamental asset management practices will be positioned for superior performance in an increasingly complex operating environment. The foundations of success will continue to be robust work management processes, effective knowledge transfer mechanisms, and clear alignment between asset management activities and organisational objectives, even as technology and workforce landscapes evolve.
This continued focus on fundamentals, combined with strategic adoption of emerging technologies and approaches, will characterise the most successful asset management organisations in the coming years.
Experience/retention of planners is a collaboration between blue – and white-collar teams. The best outcomes come from good collab between all teams with a perspective from varying positions
Maintenance Manager, Rail & Transport
MAINSTREAM Conference 2025
The insights from this report will inform the program development for the upcoming MAINSTREAM Conference, 28-29 July 2025 –Australia’s largest, most progressive asset management conference.
About MAINSTREAM Community
Founded in 1996, MAINSTREAM is an award-winning B2B community – serving asset-intensive industries with research, information, events, training courses and digital communication solutions that celebrate the successes, accelerate the careers, and optimise the performance of Asset, Reliability and Maintenance professionals.
Note of Thanks
This report was developed by the MAINSTREAM research team based on extensive engagement with the asset management community across Australia and New Zealand. We thank the many professionals who contributed their insights and experiences to this research.
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