Book a demo
Login
Supplier data management is the discipline of defining, collecting, validating, and integrating the technical data and documentation delivered by equipment suppliers, manufacturers, and subcontractors throughout the lifecycle of industrial assets. In heavy industries — oil and gas, energy, chemicals, utilities, and renewables — supplier data is the raw material from which the asset record is constructed: equipment attributes, inspection certificates, as-built drawings, operation and maintenance manuals, test records, and structured technical data that owner-operators depend on throughout the operational life of their facilities.
The scope of supplier data management spans two distinct phases of the asset lifecycle that have different objectives, different actors, and different quality requirements.
In capital projects, supplier data management is the process by which EPCs define what data equipment manufacturers and subcontractors must deliver, manage the submission and validation workflow during project execution, and ensure that complete, accurate supplier data is available for handover to the owner-operator at project completion. The quality of supplier data delivery is the single largest determinant of handover completeness and is one of the most consistently underestimated risks in capital project information management.
In operations, supplier data management encompasses the governance of supplier and vendor master data in CMMS and ERP systems: who is authorized to supply goods and services, what their qualification and performance status is, how MRO (Maintenance, Repair, and Operations) supplier data is structured and maintained, and how supplier-provided technical data is kept current as equipment configurations change and as replacement parts are sourced from alternative vendors.
In both contexts, the fundamental challenge is the same: a large number of organizations — dozens or hundreds of suppliers on a major capital project; hundreds or thousands of vendors in a mature operational MRO catalog — must deliver data that meets the receiving organization’s quality standards, in formats that can be integrated into the receiving organization’s systems, on schedules that align with the receiving organization’s operational requirements. Achieving this at scale requires governed processes, defined standards, and tooling that makes it tractable.
The foundation of capital project supplier data management is the Supplier Document Requirements List (SDRL) — the contract document that specifies which documents and data each supplier must deliver, in what format, at which project milestones, and to what quality standard. A well-written SDRL removes ambiguity about expectations, creates the contractual basis for rejecting non-compliant submissions, and provides the measurement framework against which handover completeness is assessed.
Effective SDRLs for modern digitally-managed projects specify more than document types and formats. They define structured data requirements: the equipment attribute data template (often CFIHOS or owner-operator-defined) that the supplier must populate for each equipment class, the tag numbering convention to which all documentation must be referenced, the file naming convention, the revision management protocol, and the submission system through which documents must be delivered. SDRLs that address only document types and leave format and structure to supplier discretion produce handover packages that are nominally complete by document count but practically difficult to integrate into owner-operator systems.
The submission and validation workflow is where SDRLs become operational. On a large EPC project involving hundreds of equipment packages, managing supplier data submissions is a significant project management activity: tracking submission status by supplier, purchase order, and document type; reviewing submissions against SDRL requirements; managing the review and comment cycle; accepting conformant submissions and returning non-conformant ones; and linking accepted documents to the correct equipment tag numbers. This workflow, managed informally through spreadsheets and email, is a persistent source of handover quality problems on capital projects. Managed through a structured supplier portal or document management system with integrated SDRL tracking, it is substantially more controllable.
A Vendor Data Book (VDB) — also known as a Manufacturing Record Book (MRB), Quality Dossier, or Supplier Documentation Package — is the documentation package an individual equipment supplier delivers at the end of a purchase order. It is the supplier’s delivery against the SDRL: typically containing material test reports, factory acceptance test (FAT) certificates, as-built drawings, datasheet revisions, inspection records, weld maps and non-destructive testing records, declarations of conformity, spare parts lists, and operation and maintenance manuals for that specific piece of equipment or package.
The VDB is a supplier-to-EPC deliverable: one per vendor scope, representing the complete technical and quality record for the supplied equipment. On large capital projects, the combined VDB packages from all suppliers form the raw material of the project’s handover documentation. Validating VDB completeness against the SDRL for every purchase order — before the project reaches mechanical completion — is the critical quality gate that determines whether the handover package will be complete and usable at project closeout.
The most common VDB quality failures are: missing documents (sections required by the SDRL not submitted); incorrect tag references (supplier uses their own internal references rather than the project’s tag numbers, making document-to-equipment linkage impossible without manual rework); incorrect revision management (updated documents submitted without revision identifiers); and non-conformant formats (data submitted as unstructured PDFs when structured templates were required, or drawings in formats that the owner-operator’s EDMS cannot process).
The most significant advance in capital project supplier data management over the past decade has been the development and adoption of industry standards that define common data formats and requirements across the supply chain — reducing the bespoke data management overhead that arises when every owner-operator defines its own supplier data requirements independently.
CFIHOS (Capital Facilities Information Handover Specification), now governed by IOGP as Joint Industry Project 36 (JIP36), is the leading standard for asset information handover in the oil and gas and energy industries. CFIHOS defines a data model and Reference Data Library (RDL) that specifies what attribute data must be provided for each equipment class, using a common vocabulary that is understood by owner-operators, EPCs, and equipment manufacturers worldwide. Suppliers that have implemented CFIHOS-aligned data delivery can provide structured, importable equipment attribute data to any owner-operator that uses the standard, without bespoke reformatting. CFIHOS Version 1.5 integrates with JIP33, enabling supplier data requirements from JIP33 procurement specifications to flow directly into the CFIHOS data delivery framework.
JIP33 (IOGP Joint Industry Practice 33) standardizes procurement specifications for equipment categories commonly used in oil and gas capital projects — pumps, compressors, valves, heat exchangers, and more than thirty other equipment types. JIP33 specifications include Information Requirement Specifications (IRS) that define what supplier data and documentation must be delivered for each equipment type, aligned with CFIHOS. The combined CFIHOS/JIP33 framework enables owner-operators to specify consistent, machine-readable supplier data requirements and receive structured, importable data from suppliers who have adopted the standards.
VDI 2770 is the German standard for digital documentation of industrial equipment, defining requirements for the structure, format, and metadata of equipment-related documents. Increasingly adopted in the European process industry as the standard format for digital documentation packages, VDI 2770 specifies that equipment documentation be delivered as structured document containers with defined metadata, enabling automated import into EDMS and asset management systems. For projects with European owner-operators or equipment suppliers, VDI 2770 compliance is increasingly a procurement requirement.
In operational facilities, supplier data management shifts from project execution to the ongoing governance of the vendor and material master data that drives procurement, maintenance, and spare parts management.
The vendor master — the authoritative list of approved suppliers with their names, addresses, bank details, tax identifiers, qualification status, and performance records — is a critical master data asset in any asset-intensive organization. In the ERP system, it governs purchase order routing, payment processing, and financial reporting. In the CMMS, it links maintenance activities and spare parts to the suppliers that can fulfil them. Across procurement and finance systems, it provides the single source of truth for supplier identity.
Vendor master quality problems in operational organizations are endemic. Duplicate vendor records — the same supplier entered under multiple names or addresses — generate split purchase histories, complicate spend analysis, and create payment processing errors. Stale qualification data — vendors whose approved status has not been validated against current qualification records — creates regulatory exposure when procurement proceeds with suppliers who are no longer properly qualified. Mismatched vendor identity across systems — the same supplier identified by different codes or names in the ERP, the CMMS, and the procurement system — prevents cross-system spend analysis and complicates supplier performance management.
The MRO materials catalog is the corresponding master data challenge on the materials side: the structured catalog of spare parts, consumables, and materials used in maintenance and operations, linked to the equipment items they support. MRO catalogs in mature industrial operations commonly contain millions of line items, and duplicate and inconsistently described materials are endemic at that scale. A mechanical seal described under three different descriptions in the same CMMS appears as three separate stock items, generating overstated inventory values and obscuring true consumption. Effective MRO supplier data management requires deduplication, standardized description formatting (commonly using ECCMA, UNSPSC, or owner-defined classification), and explicit equipment-to-material linkage through the tag register.
Several quality problems recur consistently in supplier data management programs, at both project and operational level, and their downstream consequences are frequently more severe than they appear at the time of submission.
Wrong equipment tag references are the most common and most damaging project-level quality problem. When a supplier submits documentation against their own internal part numbers rather than the project’s tag numbers, the documents cannot be automatically linked to the correct equipment items in the owner-operator’s systems. Every affected document requires manual matching and re-tagging — at a cost that typically exceeds the cost of preventing the problem through clear SDRL requirements and early supplier engagement.
Missing and incomplete O&M manuals are a persistent handover quality problem. Manuals that arrive without required content — missing spare parts lists, maintenance procedures that do not reflect the installed configuration, or content that covers a product family rather than the specific equipment variant supplied — force maintenance and operations teams to work from incomplete information during commissioning and early operations, when the risk of equipment problems is highest.
Unstructured data delivery — equipment attribute data provided as unstructured PDFs when structured templates were required — forces manual data extraction by the EPC or owner-operator, at costs that are highly variable and frequently underestimated. A single supplier delivering attribute data for fifty equipment items in PDF format rather than the required structured template can generate days of manual rework that could have been avoided through earlier supplier engagement and clearer SDRL requirements.
Late submission is a structural risk in capital project information management. Supplier documentation that is not available at mechanical completion forces the project to track outstanding items through a punch list, often across the most compressed and resource-constrained phase of the project. Outstanding supplier data at handover is one of the most common reasons for handover milestone delays and associated payment disputes.
On large capital projects — offshore platforms, LNG facilities, refineries, and major industrial plants — the supplier data management challenge is significant in scale. Hundreds of equipment suppliers, tens of thousands of individual documents, millions of equipment attribute values, and complex dependency relationships between engineering, procurement, and information management all converge in the handover period. Managing this at scale requires both robust processes and fit-for-purpose technology.
The process requirements for effective supplier data management at scale include: defining SDRL requirements at contract award, not during detailed engineering; providing suppliers with standard templates, clear submission instructions, and a defined submission portal before their data delivery window opens; implementing early validation — reviewing and returning non-conformant submissions at the start of delivery, not at mechanical completion; tracking submission and acceptance status by supplier, document type, and tag number in a centralized system; and linking accepted documentation to the correct tag numbers as part of the acceptance process, not as a separate post-handover activity.
The technology requirements include a supplier portal or document management system that can manage the SDRL, track submission status, route documents through the review and comment cycle, record acceptance decisions, and link accepted documents to the tag register. Systems that manage these workflows through spreadsheets and shared drives create the conditions for the most common supplier data quality failures: submissions that are received but not validated, documents that are accepted but not linked to tags, and status information that is out of date or inconsistent.
Sharecat is built around the supplier data management challenge at the center of capital project information management, providing the platform through which supplier submissions are received, validated, managed, and integrated into the project and owner-operator asset record.
For capital projects, Sharecat provides a structured supplier portal through which equipment suppliers submit their documentation and data against defined SDRL requirements. Submissions are validated against completeness and format requirements at the point of submission — non-conformant documents are flagged and returned to the supplier for correction before they enter the project record, rather than being accepted and remediated later at higher cost. Document-to-tag linkage is enforced as part of the acceptance process: documents that cannot be linked to a valid project tag number are not accepted, eliminating the manual post-handover matching work that consumes significant effort on projects with uncontrolled supplier data submission processes.
CFIHOS-aligned structured data delivery is natively supported: suppliers can submit equipment attribute data in CFIHOS-compatible structured formats, with validation against the applicable CFIHOS data model at the point of submission. For owner-operators who have defined their own data templates, Sharecat supports template-based structured data collection with equivalent validation and completeness checking. The result is a project data environment where structured, tag-linked equipment attribute data is available in importable form at handover, rather than requiring post-handover data extraction and transformation work.
For owner-operators managing operational supplier data, Sharecat provides the integration framework that connects capital project supplier data — collected and validated during project execution — to the operational asset record and CMMS. Engineering data produced and validated in Sharecat during the project flows to the operational systems that will use it through governed, auditable integration, maintaining the data quality achieved during the project through handover into operations rather than allowing it to degrade in a manual handover process.
The Sharecat platform has demonstrated this capability at significant scale. On the BP Tangguh LNG Expansion, Sharecat managed 170,812 tagged equipment items and 7,650,321 data attributes from 391 suppliers — connecting tag data from engineering through to owner-operator handover across one of the most complex capital project information management programs in the energy industry.
The Supplier Document Requirements List (SDRL) is the contract document that defines what documentation and data each supplier must deliver, in what format, at what milestones, and to what quality standard. It is the foundation of capital project supplier data management because it converts vague expectations into specific, measurable, contractually enforceable requirements. Projects with well-written SDRLs, provided to suppliers at contract award, consistently achieve better supplier data quality than projects where requirements are communicated informally or late. An effective SDRL specifies not only document types but format requirements, tag referencing conventions, and structured data templates — the details that determine whether submitted data is directly usable or requires significant rework.
Formally, the EPC contractor is responsible for defining supplier data requirements, managing the submission and validation workflow, and delivering a complete supplier data package to the owner-operator at handover. In practice, a dedicated information management or document control function within the EPC manages the day-to-day SDRL tracking and validation work. Owner-operators who actively participate in SDRL definition at contract award and in data validation during the project — rather than reviewing results only at handover — consistently achieve better handover quality. The most effective arrangements involve the owner-operator defining their data requirements clearly at the outset and the EPC implementing the workflow to meet them, with regular quality reporting during execution.
Missing supplier data at handover is managed through a handover punch list: outstanding items are tracked, and milestone payments or final acceptance may be withheld until outstanding data is received and accepted. However, in practice, the resolution of punch list items after handover is consistently slower and more expensive than preventing them: suppliers have reduced commercial incentive to respond after payment milestones have been reached, the EPC project team is demobilizing, and the owner-operator is attempting to start operations with incomplete information. The most effective approach is to identify and resolve supplier data gaps during execution, before mechanical completion, when the project still has the commercial leverage and organizational capacity to obtain corrections.
CFIHOS reduces the bespoke data management overhead that arises when every owner-operator defines its own supplier data requirements. By providing a common data model and Reference Data Library that specifies what attribute data must be provided for each equipment class, CFIHOS enables equipment manufacturers to build reusable data delivery capability that works across multiple clients and projects. An equipment manufacturer that has implemented CFIHOS-aligned data delivery can provide structured, importable equipment attribute data to any CFIHOS-adopting owner-operator without project-specific reformatting, reducing the cost and effort of compliant data delivery for both the supplier and the receiving party. CFIHOS alignment also enables automated import of supplier attribute data into owner-operator systems, eliminating the manual data entry that is otherwise required at handover.
Predictive maintenance AI models depend on complete, accurate equipment attribute data and structured maintenance history linked to the correct equipment tag numbers — precisely the data that effective supplier data management delivers at project handover. A predictive maintenance program built on asset records where equipment attributes are incomplete, where vendor documentation is not linked to tags, and where maintenance history is associated with incorrectly described equipment will produce unreliable outputs. Organizations that invest in supplier data quality during capital projects — ensuring that complete, accurate, tag-linked equipment data is delivered at handover — create the foundation for effective predictive maintenance during operations. Organizations that accept poor-quality supplier data at handover spend the early operational years remedying the gap, typically at higher cost and with lower quality outcomes than would have resulted from controlling quality during the project.
Supplier documentation data refers to the technical documents and equipment attribute data that suppliers provide about the physical equipment and systems they supply: datasheets, certificates, manuals, as-built drawings, and structured attribute records. This is the primary focus of capital project supplier data management. Supplier master data refers to the record of the supplier organization itself in ERP, CMMS, and procurement systems: legal name, address, tax identifiers, bank details, approved status, qualification records, and performance history. In operational environments, both types require governance: documentation data must be kept current as equipment configurations change and as-built records are updated; supplier master data must be maintained with current qualification status, deduplicated across systems, and synchronized between ERP and CMMS to support integrated procurement and maintenance management.
Document Handover Package — the complete set of engineering documentation transferred from EPC contractor to owner-operator at project completion; the destination into which validated supplier documentation data is assembled.
CFIHOS — the Capital Facilities Information Handover Specification; the leading industry standard for structured equipment data delivery in oil and gas and energy capital projects.
Master Tag Register — the authoritative list of equipment tag numbers in the project or facility; the reference to which all supplier documentation must be linked for effective retrieval and use.
Data Quality Management — the discipline of profiling, cleansing, validating, and monitoring data quality; directly applicable to both project supplier data and operational MRO and vendor master data.
Asset Data Migration — the movement of asset data between systems; supplier data quality at handover directly determines the quality of data available for migration into operational CMMS and ERP systems.
Master Data Governance — the organizational framework for maintaining master data quality over time; applicable to vendor master data and MRO materials data in operational environments.
ISO
27001
Certified
