This article is part of Kongsberg Digital’s Executive Series on why and how senior energy leaders are moving towards the operating model of the future, a digital performance model (DPM). Discover why ensuring decision quality through decision intelligence and AI is at the core of driving digital performance. To learn more, visit the DPM webpage: DPM
In today's rapidly evolving energy landscape, the ability to make fast, high-quality decisions has become a critical differentiator for oil & gas companies. As technology advances at an unprecedented pace, strategic integrated digitalisation has emerged as a vital enabler of effective decision-making. By embracing a powerful combination of artificial intelligence (AI), automation and human expertise, industry leaders can unlock a new level of performance, resilience and value creation.
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At its core, a company's value is the sum of its decisions. A study by Bain & Company found a 95% correlation between decision effectiveness and financial performance across industries and geographies. However, traditional decision-making processes often need help to keep pace with the complexity and velocity of today's business environment. Siloed data, cognitive biases and a lack of real-time insights can lead to substandard outcomes and missed opportunities. Companies that have invested in improving their decision-making processes by leveraging data, technology and human expertise have consistently outperformed their peers.
Unfortunately, decision-making processes in many businesses are far from optimal. Managers often make decisions under pressure, with limited information, or amidst information overload and are influenced by biases, emotions and subjectivity. A study by the University of Minnesota found that 89% of managers rely on intuition and rules of thumb, rather than data-driven insights, to make decisions.
Moreover, decision-making is frequently siloed, with individuals relying on their limited experience and isolated data, missing out on the benefits of collective wisdom and shared information. According to a survey by Signal, the main obstacles to effective decision-making include an overwhelming amount of data (44%), insufficient time (21%), lack of stakeholder alignment (16%) and difficulties in implementing solutions (19%). This lack of systematic assessment and feedback hinders continuous improvement in decision-making processes.
In this context, technology has a pivotal role to play. However, over the past decades, companies have adopted a fragmented mix of tools, including spreadsheets, reporting systems and machine learning platforms, often lacking holistic, strategic integration and domain-specific readiness. This piecemeal approach must catch up with the increasing complexity and speed required for modern decision-making. As a result, decisions are either expedited poorly or not made at all, highlighting the gap between the need for faster decisions and the capacity to make them.
There is no doubt that decision-making has become more complex, as have the methods of informing decisions. Traditional decision-making tools lack integration and are not ready to perform domain-specific decision-making in real time, resulting in a significant portion of the decision-making process being manual.
An emerging field that uses technology to support, augment and automate business decisions is Decision Intelligence (DI). DI leverages AI, machine learning and automation to analyse vast amounts of data and generate predictive insights and recommendations. Digital technologies, particularly those fueled by AI, large language models (LLMs) and automation, can significantly enhance the quality and speed of decision-making. DI represents a powerful convergence of these technologies, augmenting human expertise to unlock new levels of performance and resilience.
The appropriate approach depends on the complexity and frequency of decisions. Simpler, repetitive decisions are more easily automated, freeing human resources for high-value activities like strategic planning and innovation. As users develop confidence, they can evolve from decision support to augmentation and automation, scaling back to more manual approaches when needed, such as during unpredictable events.
DI enables strategic digitalisation and significantly benefits oil & gas companies by enhancing efficiency, productivity and profitability across various key areas, including exploration and production, supply chain management, asset optimisation and safety compliance. DI can optimise drilling locations, reduce non-productive time and improve recovery rates through AI-driven seismic data analysis and production history. At the same time, real-time optimisation of inventory and logistics can lower costs and improve market responsiveness. Continuous equipment monitoring and predictive maintenance extend asset lifetimes, reduce downtime and enhance safety and environmental performance. DI also supports sustainability by reducing carbon footprints and optimising energy use.
The advantages of a DI approach as an enabler of strategic digitalisation are countless and invaluable, and the first step is to understand and believe.
Realising digital and DI's full potential requires more than technology investments. It demands a fundamental shift in mindset and culture, embracing data-driven decision-making, continuous learning and cross-functional collaboration. Energy leaders must foster an environment where experimentation is encouraged, insights are shared freely, and decisions are made based on evidence rather than intuition alone.
Investing in digital literacy and up skilling programs to empower the C-suite in this journey is crucial. Executives need to understand the capabilities and limitations of DI technologies and the critical role of human judgment in the decision-making process. By cultivating a workforce proficient in digital and human skills, energy companies can create a culture of continuous improvement and innovation.
Moreover, energy leaders must prioritise the responsible and ethical use of DI. This means ensuring that DI systems are transparent, unbiased and aligned with human values. It also involves considering DI-driven decisions' societal and environmental implications and engaging with stakeholders to build trust and accountability.
As the energy transition gathers pace and the demands on oil & gas companies continue to evolve, the ability to make fast, high-quality decisions will only become more critical. Companies that fail to embrace a holistic, strategic approach to digitalisation fueled by decision intelligence and AI risk falling behind their more agile, data-driven competitors. In contrast, those who successfully harness the synergies between human and machine intelligence will be well-positioned to navigate the challenges and opportunities of the future.
By combining the speed and scale of AI and automation with human experts' contextual understanding and judgment, DI enables oil & gas companies to make better, higher-quality decisions faster, driving operational excellence, financial performance and sustainable value creation. Companies become equipped to respond more effectively to market dynamics, customer needs and stakeholder expectations while fostering a culture of innovation and continuous improvement.
Ultimately, the future of the oil & gas industry will be shaped by the decisions that companies make today. Industry leaders can survive and thrive in unprecedented change by embracing intelligent decision-making as a strategic imperative and putting people at the center of digital transformation. The path forward requires vision, courage and a willingness to challenge the status quo, but the rewards — in terms of performance, resilience and competitiveness — are well worth the journey.
About the Digital Operating Model of The Future Executive Series:
This article is part of Kongsberg Digital’s educational executive series to showcase different perspectives on why and how leaders are rethinking digital transformation and advancing toward the operating model of the future, a digital performance model. Learn more here.
