
Asset Information Management (AIM) is the discipline of ensuring that all data and documentation describing physical assets — what they are, where they are located, how they were designed and built, their current condition, and their operational history — is accurate, complete, accessible, and governed throughout the asset lifecycle. AIM connects engineering and project delivery on one side to operational systems (CMMS, ERP, EAM) on the other.
In oil and gas, energy, chemicals, and utilities, the quality of asset information directly determines operational safety, maintenance efficiency, regulatory compliance, and the cost of running the facility over its operational life. Poor AIM is not a data problem — it is a business risk.
These two disciplines share the acronym AIM and are frequently confused, even by industry professionals. Understanding the distinction is important:
The two disciplines are interdependent. Effective Asset Integrity Management is impossible without high-quality Asset Information Management — you cannot maintain what you cannot accurately identify, locate, and document. Maintenance teams working from incorrect or incomplete asset information consistently make errors that compromise both safety and efficiency.
Asset Information Management is important because every decision made about a physical asset depends on the quality of the information behind it. Engineering, maintenance, inspection, procurement, and operations teams need accurate and accessible information to understand what equipment is installed, how it is configured, which documents apply, and what has changed over time.
When asset information is incomplete, inconsistent, or stored across disconnected systems, the impact extends far beyond data quality. Teams spend time searching for and verifying information, engineering decisions may be based on outdated documentation, maintenance activities can be delayed, and errors introduced during projects can follow the asset into operations for years.
Effective AIM creates a trusted information foundation by connecting asset identifiers, technical attributes, engineering documents, supplier data, and lifecycle records in a governed structure. This enables organisations to:
For asset-intensive organisations, AIM therefore is not simply about managing data. It is about ensuring that trusted engineering and asset information remains usable from project development and handover through decades of operation, maintenance, modification, and eventual decommissioning.
Asset Information Management spans several interconnected data domains:
Asset information management is not a one-time activity — it is a discipline that must be maintained across every phase of an asset's life:
The transition from project execution to operational ownership is the most critical — and most frequently underestimated — challenge in Asset Information Management. This handover requires transferring millions of data points across documents, drawings, tags, and systems from EPCs and suppliers to the owner-operator, in a format that can be imported into CMMS and ERP systems and used from day one of operations.
Common causes of handover failure include:
Research consistently shows that correcting poor-quality asset data in operational systems costs significantly more than preventing it during the project — and that the correction cost increases with every year the incorrect data remains in use. Treating data quality as a project deliverable from FEED through to handover is the correct approach.
When evaluating Asset Information Management software for oil and gas, energy, or process industry operations, the key capabilities to assess are:
Sharecat is a purpose-built AIM platform for asset-intensive industries that connects engineering documents to tagged asset data from the earliest project stage. By aligning with CFIHOS and ISO 15926, Sharecat ensures asset information is captured consistently and can be transferred reliably to CMMS and ERP systems at handover, reducing the cost and risk of data migration.
Sharecat's data quality management capabilities enable continuous validation of completeness and accuracy throughout the project, so the handover package is a trusted foundation for operations — not a starting point for corrective work. Supplier documentation is linked directly to the tag register through governed submission workflows, eliminating the most common source of handover failures.
Is AIM the same as an asset management system?
No. An asset management system (typically a CMMS or EAM like SAP PM or IBM Maximo) manages the maintenance and operational activities performed on assets. AIM is the discipline of ensuring the underlying asset data that these systems depend on is accurate, complete, and governed. AIM provides the data foundation that makes asset management systems reliable.
Who is responsible for AIM in an oil and gas company?
AIM responsibility typically sits across multiple functions: engineering (for design data and documentation), operations (for as-operated data), IT/digital (for systems and integration), and often a dedicated asset data or information management function. Owner-operators increasingly appoint dedicated AIM leads on major capital projects to ensure data quality is maintained from FEED through handover.
When should AIM be started on a capital project?
AIM should start at FEED — or even earlier during concept selection. Decisions made in early project phases about tag numbering systems, data requirements, and document coding conventions determine the quality of asset data available at handover. Retrofitting good data governance onto a project that is already in detailed engineering is significantly more expensive than establishing it at the outset.
What is the cost of poor AIM?
The cost of poor asset information management is primarily felt in operations: maintenance teams spending time locating correct information instead of performing maintenance, procurement errors due to incorrect equipment specifications, extended turnarounds due to poor work preparation, and regulatory exposure from incomplete inspection records. Studies of major capital projects consistently show that handover data deficiencies cost owner-operators millions of dollars per year in operational inefficiency.