Operational Excellence Starts with Asset Intelligence

Traditional asset management in oil and gas relies heavily on reactive maintenance, disconnected systems, and manual tracking. As operations scale, these limitations lead to increased downtime, safety risks, and rising operational costs.

Organizations today require intelligent systems that can predict failures, optimize performance, and provide real-time visibility across asset-intensive environments.

• Reactive maintenance with no predictive intelligence
• High operational costs due to unplanned downtime
• Excess inventory and inefficient resource utilization
• Limited visibility across distributed assets
• Increased HSE and compliance risks

Traditional systems were never designed for predictive, intelligent operations.

What You Can Achieve with Asset Intelligence:

• AI-powered failure prediction using IBM Maximo
• Real-time monitoring and asset performance visibility
• Optimized inventory and maintenance planning
• Improved safety and regulatory compliance
• Reduced downtime and operational costs
• Scalable architecture for enterprise-wide deployment

Asset Intelligence enables oil and gas enterprises to move from reactive maintenance to predictive, optimized operations.

Book a Meeting

Use an inspection finding on a critical oil-and-gas asset to test the maintenance decision process. Review asset criticality, work history, operating constraints and the approval required before intervention.

Start with the asset hierarchy, work-management process and information needed by planners, technicians and operating teams. Review how inspection findings, condition signals, maintenance history and work orders are connected in the selected Maximo environment. Define the application scope and integrations before choosing configuration or customization changes.

Validate the complete path from an observed condition to an authorized work action. Include incomplete asset data, duplicate notifications, material availability, mobile connectivity and supervisory review. Predictive or AI-assisted recommendations should provide evidence for the responsible person; their use does not remove operational approval or maintenance accountability.

Bring the asset register, representative work orders, current Maximo deployment details, integration list and maintenance priorities. Agree the pilot population, data-quality checks and acceptance scenarios. Deliverables can include the process design, configuration scope, integration requirements and support handover, with responsibility assigned for ongoing asset-data quality.