Maximize operations across the front and back office
The influx of oil and gas M&A also creates a case for companies to improve business fundamentals, such as driving down operating costs, leveraging scale, jumping the curve on differentiated capabilities and strategically thinking about talent management.
Maximizing operations is not a new description for simply doing “more with less.” Rather, it is operating by exception and problem-solving using technology at speed, innovation at scale with humans at the center. “To drive immediate results and limited disruption, we are collaborating with teams responsible for performance in the field, subsurface, production-operations, facilities, maintenance and supply chain,” says Swapnil Bhadauria, EY US Oil & Gas Digital Operations Leader. “We take a people-led approach in our business or technology transformation implementations. In every project, people are critical and the change champions that ultimately drive success.”
Real-time data and emerging technology are essential to enable better, faster, and more strategic decisions. This is true holistically across the entire value chain – in both the front office and back office, but also specifically in subsurface prediction, drilling and completions, asset surveillance and optimization, maintenance, and materials management.
Considering different operating models, such as managed services, is particularly important when companies develop new business areas. For example, the front- and back-office functions for low carbon will be different from traditional oil and gas. As low-carbon business areas begin to scale, companies should consider multiple operating models before committing to specific processes and technologies. This will allow them to find synergies by integrating traditional business areas or pivot to innovative and emerging ecosystem models.
Lastly, oil and gas companies that are able to integrate artificial intelligence (AI) and generative AI (GenAI) capabilities in their everyday decision-making will jump the curve on business value. This shift will require companies to establish a strong foundation of trusted data while also implementing AI and GenAI engineering best practices, robust governance and risk management. The adoption curve for AI is faster than for any other technology so far, so companies must act quickly.
By 2025, the 10% of enterprises that establish AI engineering best practices will generate at least three times more value from their AI efforts than the 90% of enterprises that do not.¹
“With confident and responsible adoption of AI, oil and gas companies will unlock the full potential of their workforce, have a greater impact on daily operations, accelerate real-time decision-making, and positively impact the bottom line,” Bhadauria explains.