Sustaining Digital Oilfield Value Beyond the Pilot Phase
Pilot programs can demonstrate what a digital solution is capable of achieving. Sustaining that value across an enterprise requires organizations to address ownership, governance, accountability, operational workflows, and decision-making long after deployment begins. Drawing on nearly 25 years in digital production and energy-sector leadership, Vikas Agrawal explores the organizational factors that help transform successful pilots into lasting operational capabilities.
About twenty years ago, I worked on a production-optimization initiative for a large offshore asset. The technical work was sound, the recommendations identified measurable production opportunities, and implementation on selected wells delivered the expected results. At the time, it felt like the project had accomplished what it was designed to do.
Years later, I found myself looking at the same asset from a very different vantage point. New digital initiatives were underway, new technologies had been introduced, and additional value opportunities had been identified. Some of these delivered meaningful results within specific teams or operating groups, while others struggled to gain broader adoption. What struck me was how familiar many of the underlying challenges felt. The technology had evolved considerably, but sustaining value across a large organization remained every bit as difficult as identifying it in the first place.
Over the last two decades, the energy industry has invested heavily in digital technologies, advanced analytics, cloud platforms, and more recently, artificial intelligence. These investments have created new ways to monitor operations, identify opportunities, and support decision-making across increasingly complex assets. Demonstrating value through a pilot or targeted deployment is often achievable, but I’ve found that extending that value across an organization and sustaining it through changing priorities, operating conditions, and leadership transitions is where the work becomes significantly more complex.
Throughout my career, I have seen organizations achieve impressive results from digital initiatives when technology deployment was accompanied by equal attention to operating models, governance structures, ownership, and value realization. Digital solutions do not operate independently of the organizations that use them. Adoption, accountability, decision-making processes, and clear definitions of success all influence whether a promising initiative becomes part of everyday operations or remains confined to a successful pilot. Organizations often improve their chances of sustaining value when those questions are addressed early and revisited as the initiative matures.
From Pilot Success to Enterprise Implementation
Generating value through a pilot is often a very different undertaking from sustaining that value across an enterprise. Pilot programs are typically designed around a defined objective, a focused group of stakeholders, and a relatively short timeframe. Success can be measured against a specific operational challenge, allowing teams to move quickly and demonstrate results without needing to account for every process, function, or business priority across the organization.
Enterprise integration brings a different set of challenges because the solution is no longer operating within the boundaries of a pilot team. As more parts of the organization begin using the technology, it becomes intertwined with existing workflows, operating practices, data environments, and decision-making processes. The conversation gradually shifts from proving that the technology works to ensuring it can support a broader range of users, operating conditions, and business objectives over time.
Long-term adoption is often shaped by decisions made well before deployment begins. Stakeholders often focus considerable attention on technology capabilities, which is understandable given the pace of innovation across the industry. At the same time, questions surrounding ownership, governance, operating processes, and value realization deserve equal consideration because they shape how the organization will engage with the solution once it becomes part of day-to-day operations.
One of the most valuable conversations an organization can have early in a digital initiative involves creating a shared understanding of the journey ahead. Technology roadmaps are often discussed from a product-development perspective, yet they also play an important role in aligning expectations across the business. Stakeholders who understand how a solution is expected to mature, what capabilities will be available at different stages, and how value will be realized over time are generally better positioned to support adoption through the inevitable adjustments that accompany any large-scale transformation effort.
Aligning Expectations Before Deployment Begins
A lesson that has remained consistent across digital initiatives is the importance of defining a shared understanding of the journey before deployment begins. Much of the industry’s attention naturally focuses on technology capabilities, but long-term adoption is often influenced just as much by how expectations are established during the early stages of a program.
Technology demonstrations play an important role in helping organizations understand what a solution may ultimately be capable of delivering. A compelling demonstration can create a shared vision of future possibilities and help build the organizational support needed to move an initiative forward. Sustaining adoption depends on an equally clear understanding of how the solution will mature over time, what capabilities will be available at different stages of deployment, and what organizational changes may be required to realize value from those capabilities.
In my experience, organizations benefit when roadmap discussions extend beyond technical features and implementation timelines. Stakeholders across operations, engineering, production, and management often view success through different lenses, and those perspectives need to be aligned early. A production engineer may focus on operational improvements, a business leader may be evaluating financial impact, and an asset manager may be considering how a solution fits within broader organizational objectives. Bringing those perspectives together helps establish realistic expectations while creating a common framework for measuring progress.
This alignment becomes particularly important as initiatives move beyond pilot environments. A pilot may demonstrate the potential value of a solution, but broader adoption introduces new operational, organizational, and business considerations. As more teams begin using the technology, questions arise about ownership, workflows, accountability, and how success will be measured across different parts of the organization. Addressing those questions early helps sustain momentum as adoption expands, and the initiative becomes more deeply integrated into day-to-day operations.
Turning Insight Into Action
Sustaining value also depends on what happens after an insight is generated. Most digital platforms are highly effective at organizing information, recognizing patterns, and bringing operational issues to the attention of the people responsible for managing them. The real work begins after an opportunity has been identified. In many cases, the next challenge is determining how that opportunity moves from observation to action within the organization.
Significant progress has been made across the energy industry in collecting, integrating, and visualizing operational data. Teams now have access to more information than ever before, but value is created only when that information influences decisions, operating practices, and business outcomes. Reaching that point requires clarity around ownership, accountability, and the processes used to evaluate and act on recommendations.
A recurring theme across digital initiatives is the importance of defining who is responsible for acting on the insights being generated. Production engineers, operations teams, reliability specialists, and asset managers may all interact with the same platform, yet each group contributes to a different part of the decision-making process. Having a clear process for reviewing, prioritizing, implementing, and measuring recommendations helps ensure that valuable insights become part of day-to-day operations rather than remaining confined to a dashboard or report.
Interest in artificial intelligence continues to grow as organizations look for new ways to accelerate analysis and support operational decision-making. Sustained value is ultimately created through decisions, actions, and outcomes that improve operational performance. As digital capabilities become more closely integrated into operational workflows, they increasingly contribute directly to the decision-making process while helping people evaluate information more efficiently.
Although the specific organizational structure varies from one company to another, I have found that successful implementations consistently address the same underlying questions:
- Who owns the outcome?
- Who reviews and acts on the insights being generated?
- How are those decisions incorporated into existing operational workflows?
- How will value be measured over time?
- How will governance evolve to support broader deployment as adoption expands?
The answers will differ from one organization to another, but those five considerations provide a practical framework for planning technology adoption and sustaining value beyond the pilot phase.
Expanding the Role of Digital Intelligence
Recent advances in artificial intelligence are creating new opportunities to support operational decision-making across the energy industry. Large language models, agentic systems, and increasingly sophisticated analytics platforms can help users navigate large volumes of information, identify emerging issues, and prioritize areas that may require attention. These capabilities have the potential to improve efficiency and reduce the time required to move from observation to evaluation.
The growing interest in AI reflects a broader shift in how organizations interact with operational data. Historically, engineers and operations teams were responsible for navigating multiple systems, reviewing reports, and manually connecting information from different sources before arriving at a decision. New digital tools are making that process more accessible by helping users surface relevant information more quickly and focus attention on the issues most likely to influence operational performance.
The long-term value of these capabilities, however, will depend on how effectively they are integrated into existing operating models. Recommendations still require evaluation, decisions still require accountability, and organizations still need clear processes for determining how actions will be prioritized and executed. AI can accelerate many aspects of the workflow, but sustained value ultimately depends on how those capabilities support the people responsible for managing the asset.
Organizations are likely to derive the greatest benefit when AI is viewed as one component of a broader operational strategy. Technology can help improve visibility, accelerate analysis, and support decision-making, but lasting business value depends on the way those capabilities are incorporated into day-to-day operations. Whether the technology is an AI platform, a digital production system, or the integration of newly acquired capabilities, successful implementation still requires clear ownership, defined accountability, workflow integration, meaningful measures of success, and governance that supports long-term adoption.
Sustaining Value Requires an Operating Model
When I think back to that production-optimization project from the beginning of my career, what stands out today is not the technology that was available at the time or the specific recommendations that were implemented. The more lasting observation is that sustaining value has always required a broader organizational commitment than any individual project can provide on its own.
The industry’s digital capabilities have advanced dramatically. Organizations now have access to levels of connectivity, computing power, analytics, and artificial intelligence that were difficult to imagine when many early digital-oilfield initiatives began. Those advances have created new opportunities to improve operational performance and support better decision-making across increasingly complex assets.
My current responsibility for integrating an acquired technology company has given me an opportunity to view many of these same challenges from a different perspective. Bringing together technologies is only one part of the work. Integrating teams, defining operating responsibilities, aligning stakeholders, and establishing shared measures of success ultimately determine whether those new ways of working become part of the business or remain separate from it.
This experience has reinforced something I’ve come to appreciate throughout my career: technology changes much faster than the organizational work required to sustain it. The tools available to the industry will continue to advance, but every successful implementation still depends on people making decisions, taking ownership, and embedding those technologies into everyday operations.
Vikas Agrawal is an Integration Manager at one of the world’s leading energy technology companies, where he leads the integration of people, technologies, and business operations following a strategic acquisition in the digital energy sector. Over nearly 25 years in the oil and gas industry, he has held technical, operational, commercial, and executive leadership roles across North America, Europe, Africa, the Middle East, and Asia. His work has focused on production optimization, digital transformation, and helping energy companies translate technology investments into sustained operational and business value.
