In oil and gas, performance depends on what happens in the field, not only what is written in the plan. A maintenance program, inspection process or safety procedure may be well designed, but risk begins to build when day-to-day execution starts to move away from the approved process.
That movement is known in the industry as “operational drift.” It can start with a field adjustment, a missed procedural step or a task completed differently than intended. Sometimes the worker has a sound reason for making that choice. The problem is that when the reason is not captured or reviewed, the organization loses the chance to learn from it, correct the process or prevent the same issue from spreading across crews, contractors and assets.
Operational drift can be hard to see because it happens in small moments during routine work. In oil, gas and energy environments, those moments can accumulate long before they show up as downtime, an audit issue or a safety incident.
The topic is becoming a broader industry conversation because operators have more systems than ever, but those systems do not always show how work is performed at the point of execution. A recent Forrester study found that while 76% of leaders believe process improvement is embedded in daily operations, only 39% of front-line supervisors say the same. For upstream operators, that disconnect can affect inspection quality, maintenance consistency, and the ability to respond before risk reaches the incident report. The consequences of that lack of visibility are well documented. Investigations into incidents ranging from the 2018 Superior refinery explosion to the CSB’s findings following a fatal 2024 PEMEX refinery accident have pointed to the breakdowns in maintenance execution, procedural compliance, and safety controls that were not addressed before they escalated.
Planning systems, maintenance systems and digital permits play important roles. They help assign work, manage approvals and track completion. What they may not show is whether the worker had the right instruction during the job, whether the approved process matched field conditions or whether a deviation points to a larger issue elsewhere in the operation.
With the advent and uptake of AI, operators can more easily identify drift earlier by using field execution data as a source of operational intelligence. Patterns in daily work can show where procedures are unclear, where teams need support or where the same deviation is appearing across multiple assets. That gives leaders a chance to act before drift affects safety, reliability or production performance.
OGE work will always require human judgment. Operators need to know that workers have the right guidance in the moment and that critical decisions are captured when conditions change in the field.
For operators, operational drift is not a minor process issue. Left unseen, it becomes downtime, lost production, compliance exposure or a preventable safety event. The operators best positioned to avoid those outcomes will be the ones that can see how work is being performed, learn from deviations as they happen and intervene before small gaps become costly failures.
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