{{item.videoDuration}}
{{item.title}}
{{item.text}}
{{item.videoDuration}}
{{item.text}}
Operating with discipline in a more demanding era
Inflation. Asset complexity. Digital acceleration. Workforce shifts. Geopolitical volatility. Combined, these forces create structural pressure on oil and gas operations—pressure that isn’t likely to ease anytime soon.
In an era where the oil and gas industry faces both internal and external challenges, it’s not enough to create isolated initiatives. To drive competitive advantage, high-performing operators are developing an integrated transformation agenda around four interconnected priorities.
How can energy operators build competitive advantage amid inflation, complexity, and volatility? Here’s how you can seize the edge.
1. Use data to drive efficient and low-cost operations
The situation
Cost inflation has become a persistent issue across the energy value chain as oil and gas companies compete with other infrastructure sectors for labor and materials. Tariffs on critical inputs such as steel, equipment, and components are adding another layer of cost pressure, compounding inflation beyond traditional supply-demand dynamics. Sector-wide cost-cutting and restructuring will likely continue through 2026. At the same time, companies are under pressure to improve reliability and increase production or throughput from existing assets—particularly at critical pinch points such as midstream takeaway from the Permian Basin.
Winning operators are making a shift from siloed metrics to enterprise-wide performance management.
The solution
After years of collecting vast amounts of operational data, leading oil and gas companies are adopting a more continuous, connected approach to cost and performance management. But most can do a lot more. By aggregating data across enterprise asset management (EAM), field service management (FSM), production systems, and financial platforms, companies can develop a unified view of asset performance and cost drivers across the value chain.
This integrated data foundation enables more informed decisions on strategic imperatives around reliability and throughput. For example, companies can better quantify the true cost of downtime, identify bottlenecks across interconnected assets, and uncover opportunities to improve maintenance, scheduling, and operations. It also allows organizations to standardize performance metrics and benchmark results consistently across assets and business units.
To lead in this area, companies should use enterprise tools to shift from managing performance at the asset or business-unit level to driving performance across the entire organization. Higher levels of transparency and operating discipline are within reach for companies that make the shift.
2. Scale digital and AI transformation for core operations
The situation
Almost every operator has embarked on some form of digital transformation and the availability of operational data has grown exponentially due in part to lower-cost sensors. Now, with the rapid evolution of AI, companies can leverage this data in radically new ways. Despite the promise these developments hold, many companies have not yet seen results. In our annual global CEO survey, only 30% reported real results from their AI initiatives in the past year. For energy companies, this represents an untapped opportunity.
Real value comes from a shift away from experimentation to scaling AI across core operations.
The solution
After years of pilots, AI-enabled technologies are becoming front-line tools. The ability to combine and contextualize data has accelerated this process. Time series data from equipment sensors, transactional data that describes maintenance history, and geospatial data that pinpoints equipment and crew locations can now be used together to improve the speed and quality of decisions.
This means embedding analytics in your day-to-day decision processes and workflows. Consider that control room operators can use optimization signals to drive down energy consumption. Large-language models can assist with planning maintenance work. Agentic AI can improve the efficiency and control of procurement processes. Establishing sound data governance is foundational to making the most of these advances. To take the lead, you’ll want to shift from focusing solely on technology investments to designing operating models that squeeze the most value from these investments.
3. Reimagine the operations workforce
The situation
The industry faces a critical workforce shortage. Nearly half—or 48% of the workforce—is 45 or older, and many will likely retire during the next five to 10 years, creating not only a capacity gap but a risk of losing decades of institutional and operational knowledge as well. Much of this expertise remains undocumented, embedded in day-to-day decisions and frontline experience. Meanwhile, sourcing talent for the newest positions in digital and AI-related fields is further adding to the staffing crunch. The International Energy Agency (IEA) reported in its World Energy Employment series that more than 60% of energy companies globally cite a “lack of candidates with the required skills” as their primary barrier to growth. Further, training existing employees presents its own challenges.
Leaders are driving a shift from reactive hiring to deliberate capability building.
The solution
Today’s industry needs to unlock a new era of workforce capability—one that’s as comfortable with traditional operations and maintenance as it is well-versed in modern digital tools. This requires redefining roles to reflect the evolution of how work gets done.
As you build the new digital toolkit, recognize the opportunity to capture the enormous institutional knowledge of their workforce. This means involving late-career members of your operations team in these initiatives, before the retirement waves accelerate and their know-how is gone for good.
Functional teams may need to be restructured. This may result in hybrid teams or pods that combine engineering, data, and field expertise. Leading companies will likely make the shift from reactive workforce planning to a deliberate capability-building strategy.
4. Manage risk dynamically to mitigate volatility
The situation
Geopolitical instability—particularly in the Persian Gulf—is a major driver of recent volatility in crude and natural gas markets. The rapid expansion of the global LNG market is also causing market turbulence. By 2030, the world is expected to grow natural gas liquefaction capacity by nearly 50%, most of it in the US and Qatar, according to the IEA. This is an unprecedented rate of growth relative to historical levels and could shift the market toward greater supply abundance. At the same time, this growth is placing increased pressure on operators to execute large-scale infrastructure and capital projects efficiently—requiring disciplined investment decisions, resilient supply chains, and the ability to deliver capacity on time and on budget to meet rising demand.
The rapid evolution of the regulatory environment is also creating instability. Some changes are favorable to the industry—permitting reform, extension of methane rule compliance deadlines, and recission of the endangerment finding. However, some new compliance requirements—such as updates to Pipeline and Hazardous Materials Safety Administration (PHMSA) rules for midstream operators—will require attention. Companies should also prepare for executive action that could add to flux.
Uncertainty favors those who shift to predictive, analytics-led risk management.
The solution
Leading operators manage risk dynamically, particularly when it comes to market risk exposure. It starts with visibility across geographies and asset classes. By aggregating supply, demand, and logistics data—and then using it to measure risk and build predictive models—your company will have a significant competitive advantage.
The energy industry has not escaped the impact of supply chain disruptions this decade. However, companies can use data and analytics to model and predict how external pressures—such as tariffs or inflation—may affect the cost and risk of projects. With this information, you and your teams can make better, quicker decisions. This applies up and down the supply chain, and it requires an understanding of suppliers’ and contractors’ exposure as well as your own.
Companies that can make data-informed decisions are better positioned to lead. Doing so will require a shift in thinking from reactive response to designing for risk resilience.
Shifting gears in tandem
These four priorities for evolving energy operations are not independent workstreams to be pursued in parallel. They’re deeply interconnected. The companies that treat them as such will pull ahead. Cost discipline is enabled by digital tools. Digital tools are only as effective as the people who use them. And both operational efficiency and workforce capability determine how well an organization can absorb and respond to external shocks. The operators that thrive in this more demanding era won’t be the ones that simply react faster—they’ll be the ones that build integrated, resilient operating models designed for continuous adaptation. The edge doesn’t go to those who wait for conditions to stabilize. It goes to those who operate with discipline while everything around them shifts.
{{filterContent.facetedTitle}}
{{contentList.loadingText}}
{{contentList.loadingText}}
Follow us
