Brisbane: An Energy Economy Under Transformation

Brisbane at night. Picture credit: storybridgeadventureclimb.com.au 

Queensland is one of Australia’s most consequential energy and resources economies. Its generation mix is shifting fast: coal’s share fell from 61% to 59% between 2022 and 2024, while renewables climbed from 24% to 28% over the same period, driven by solar, wind, and biomass. LNG exports reached 24 million tonnes in 2024-25 (5% of global LNG production), generating $15 billion in business since 2015. The state hosts 19 of the world’s most sought-after critical minerals, and its Mining, Equipment, Technology and Services (METS) sector contributes $704.8 million in exports annually.

In this environment, the stakes of asset reliability and maintenance excellence are measured in billions of dollars, regulatory obligations, and community energy security. It was against this backdrop that SAP, Wood, and PiLog Group organised a senior Executive Roundtable on Asset Performance Management (APM) in Brisbane on 22 Apr 2026, bringing together 16 leaders from the gas, power generation, renewables, oil and gas, and mining industries.

What the Industry Told Us

Despite operating across different sectors with fundamentally different assets, participants converged on the same core challenges – the common thread of ensuring reliability and delivering maintenance efficiently.

• Criticality assessment remains unsolved. The roundtable’s longest discussion centred on a deceptively simple question: Do you know which of your assets are truly critical? The answer across the room was “it is not as straightforward as we would like”. Criticality is multidimensional. It changes over the life of an asset. It depends on usage patterns, asset age, position in the process chain, supply chain exposure, changing geopolitical winds, and inherent risk at commissioning. Organisations correlating “critical” with “expensive” or “old” are making prioritisation decisions on incomplete foundations – and the answer to the criticality question is at the heart of ensuring reliability and delivering maintenance efficiently.  It impacts WHAT you do (maintenance strategies and schedules), and HOW you prepare for it (spare parts planning and supply chains)
• Data is the opportunity nobody has mastered. Data was the most frequently discussed topic, and the most frustrating one. Organisations have more data than they can process, but the right data rarely reaches the people and systems that need it most. Work management layers are often disconnected from OT, IoT, and ERP sources. Master data quality is poor across the board, and most migrations have been ‘lift and shift’ rather than standards-aligned, carrying forward existing problems into new systems (or abandoning the gold hidden in historical data altogether in the migration process!). One telling observation from the room: rescheduled work orders are among the strongest leading indicators of asset risk, yet this signal is routinely invisible because the data never makes it into the right system. On top of that, data collection is expensive and with too much data being collected, neither the cost equation nor decision-making benefits! To illustrate this point, it was insightful to note that all the participant organisations were using or trialling to allow data captured in the field to be seamlessly transferred into the ERP source systems.  However, the temptation in this process was to ‘overload’ the field-data capture process, adding more data and fields to the information to be captured in the field, without considering the frustration this might cause with front-line workers.  Changes, however well-intentioned, must be carefully managed.  Sometimes, less is more.

• AI interest is outpacing AI readiness. Every participant was interested in AI-driven reliability improvements. But the honest assessment was that most organisations are not yet ready to realise that value, precisely because of the data quality gap. The sequencing matters: data governance and master data integrity must come before, or at least with AI, not after it.
• Growth adds complexity. For energy companies adding solar, wind, and battery assets to legacy portfolios, the volume and diversity of new assets create their own management burden. Automating asset build processes, integrating reliability and ERP platforms, and managing the knowledge risk from retiring workforces are immediate operational challenges, not future ones.

What Good Looks Like

The roundtable reinforced that solving APM at scale requires three capabilities working together: deep reliability engineering knowledge, leading data quality and governance practice, and integrated digital platforms and processes. This is precisely why Wood, Pilog and SAP came together for this event.

The practical roadmap for most organisations follows a clear sequence. Establish data quality and criticality frameworks first. Then connect data flows across systems so that you can apply AI to optimise preventive and corrective maintenance, identify failure patterns, and ultimately move toward closed-loop and autonomous asset management, where agentic AI continuously refines strategy based on real asset behaviour.

Organisations that attempt to shortcut this sequence, deploying AI on top of poor master data, or incomplete or incorrect maintenance records, will not get better outcomes faster. Instead, they will see limited benefits from their initial trials and will question whether there is a business case to scale these efforts to the rest of the enterprise. A guided APM-specific Health Check was proposed as a pragmatic way to get started on an Asset Management improvement journey.  In a focused engagement, it assesses data quality against international standards, functional location hierarchy completeness, criticality framework maturity, technology readiness, and consistency of business processes. This allows a prioritised, actionable improvement roadmap to be generated, without requiring a programme-scale commitment upfront.

The Conversation Continues

APM is not a solved problem. It is an evolving capability challenge in an industry undergoing structural transformation across its energy mix, asset base, and workforce simultaneously.

The organisations that lead in reliability over the next decade are investing now in the fundamentals: clean data, robust criticality frameworks, integrated platforms and business processes, and the human capability to act on what those platforms reveal.

If these challenges sound familiar, we would welcome the opportunity to continue the conversation.

What did you think about this post? Please leave your feedback, thoughts, and suggestions in a comment below.

Also, please follow the co-authors: Andrew Miller, Amarendra Singh, @pavneetbedi  so that you do not miss any future posts.

You may also be interested in the following blogs: