THE OPPORTUNITY
A global energy firm faced challenges in optimizing the selection process for its energy extraction platforms. The existing process was manual, time-consuming, and prone to errors, leading to suboptimal decision-making, bloated development costs, and lost extraction volume.
Utilizing novel AI/ML models, the goal was to reduce the time required for selection, improve decision-making accuracy, lower operational costs, and maximize profit.
THE RESULTS
Efficiency Gains: The time required for platform design was reduced by 40%, allowing quicker decision-making and project initiation.
Cost Reduction: The optimized selection process contributed to a projected 15% reduction in development costs by ensuring the right platforms were chosen for each project.
Accuracy and Confidence: Stakeholders expressed increased confidence in the data-driven recommendations provided by the AI/ML system.