A CMMS (Computerised Maintenance Management System) is software used to manage and track maintenance activities, work orders, asset records, and spare parts across industrial facilities. Core functions include:
Scheduling and tracking work orders — from creation through completion, including labour, materials, and downtime tracking.
Managing preventive maintenance programmes — automating recurring maintenance tasks based on time intervals, usage, or condition triggers.
Recording equipment history and failure data — building a maintenance record for each asset that supports reliability analysis and lifecycle planning.
Controlling spare parts inventory — managing stock levels, reorder points, and consumption against work orders.
Supporting procurement of maintenance materials — linking item master records to purchase orders and supplier data to enable direct OEM ordering.
In asset-intensive industries such as oil & gas, energy, utilities, and pharmaceutical manufacturing, a CMMS is one of the most operationally critical systems in the business — and one of the most dependent on high-quality masterdata. A CMMS populated with incomplete or incorrect data cannot deliver reliable maintenance scheduling, procurement support, or operational reporting.
A CMMS focuses primarily on maintenance execution — work orders, preventive maintenance scheduling, and technician management. An EAM (Enterprise Asset Management) system extends this to cover the full asset lifecycle, including procurement, commissioning, depreciation tracking, total cost of ownership, anddisposal planning.
In practice,the terms are often used interchangeably, and many modern systems combine bothfunctions. In the SAP ecosystem, the equivalent function is the SAP PM (PlantMaintenance) module. Standalone CMMS products such as IBM Maximo and IFS mayintegrate with any ERP system.
The keydifference for data management purposes is scope: a CMMS manages maintenancedata, while an EAM manages data across the entire asset lifecycle. In bothcases, the quality of the underlying master data — equipment records,functional locations, spare parts, and manufacturer information — determineswhether the system delivers value.
Why CMMS Data Quality Is Critical for Industrial Operations
A CMMS isonly as reliable as the data it contains. The most common data quality problems found in industrial CMMS systems include:
Incompleteequipment records — missing attributes, functional locations, and spare parts links that prevent maintenance scheduling and procurement from operatingcorrectly.
Incorrect part numbers — model numbers entered in part number fields that block automatedordering and force procurement teams into manual workarounds.
Unverified manufacturer names — inconsistent or abbreviated manufacturer names that fragment spend analysis and prevent preferred supplier routing.
Brokenr eferences — documents, functional locations, and tags that reference itemsthat do not exist or point to the wrong equipment.
Each ofthese problems has a direct operational cost. Maintenance teams spend time searching for information that should already be in the system. Procurementteams order from intermediaries at premium prices because the correct OEMcannot be identified. Inventory accumulates duplicates because the same partexists under multiple descriptions. Regulatory audits surface inconsistenciesthat require emergency remediation.
According to Gartner, poor data quality costs organisations an average of $12.9 million peryear. In asset-intensive industries with large equipment inventories, theimpact on CMMS-dependent operations is typically far higher.
Sharecat Data Services specialises in improving the quality of data held in CMMS systemsacross heavy and complex industries — oil & gas, energy, utilities,pharmaceutical, and manufacturing. The company's services address the fullrange of CMMS data quality problems: data cleansing to correct errors and inconsistencies in existing records, data enrichment to add missing informationfrom verified external sources, and data cataloging to ensure that new dataentering the system is correct from day one.
What setsSharecat Data Services apart from general data providers is industry expertise.The team understands industrial equipment, OEM naming conventions, and the data standards that apply in heavy industries — including CFIHOS, UNSPSC, eClass, ISO 15926, and NORSOK. This means data quality issues that a general providerwould miss — a model number filed as a part number, a manufacturer name entered as a trading name rather than the OEM name — are identified and corrected.
Sharecat Data Services' approach combines proprietary tools with subject matter experts,and every project includes a before-and-after statistical comparison so the improvement in CMMS data quality is measurable. Clients report saving up to 90%of the time and cost previously spent in procurement processes once their CMMS systems have the correct data to operate as intended.
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