Optimal› What We Do› Asset Data Cleansing & Enrichment
04.04 · Advisory & Optimisation

The plant stopped.
The spare was in the system.
Just not visible.

Duplicate records, missing OEM references, inconsistent naming conventions, obsolete part numbers still active in the register. Poor asset master data does not announce itself — it surfaces as a production outage, an emergency purchase order, or an inventory write-off. Optimal's Asset Data Cleansing & Enrichment service eliminates the root cause, not the symptom.

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Supply Chain & Procurement
Inflated inventory. Duplicate orders. Wrong parts arriving on site.
When material master data is inconsistent, the same component exists under twelve different descriptions. Procurement orders against the wrong record. Stock is held in multiple locations under different names. Working capital is tied up in inventory that cannot be found — while the right part is on emergency purchase order.
Plant & Operations Leadership
Production down. Right spare not found. Wrong spare fitted.
A maintenance team searching for a bearing in a poorly maintained CMMS can spend more time locating the part than fitting it. When the search fails and the system cannot be trusted, the outage extends. When the wrong part is fitted because the record was inaccurate, the outage returns. Data quality is a production performance problem, not a data problem.
When Clients Come to Us

Four situations we
recognise immediately

Every asset data engagement Optimal takes on starts from one of four recognisable situations. The data problem is usually not new — it has been accumulating for years. What changes is the point at which the cost of leaving it unresolved exceeds the cost of fixing it.

01
Inflated & duplicated inventory
The same component held under multiple item codes, in multiple stores locations, under inconsistent descriptions. Duplicate stock is a direct working capital cost — typically 10–30% of total stock value is recoverable through systematic deduplication. The inventory looks large. The right parts are frequently unavailable.
02
Spares shortages causing production outages
Assets are failing and the required spare cannot be located — not because it is not held, but because the data linking the equipment to its critical spares is incomplete, misclassified or missing OEM references entirely. The outage is the visible cost. The data deficiency is the cause.
03
New EAM / CMMS implementation
A new system is being implemented and the data that will be migrated into it is the same data that has been causing problems in the outgoing system. Migrating without cleansing perpetuates every existing problem in a new environment. Clean data is the prerequisite for a successful go-live — not an optional step after implementation.
04
Post-acquisition asset register consolidation
An acquisition has brought additional assets, stores and ERP or CMMS systems into the portfolio. Two naming conventions, two classification taxonomies, multiple stores locations holding overlapping inventory. Consolidation without data harmonisation produces a larger version of the same problem — not a single source of truth.
The Financial Case
What poor asset master data
is costing your organisation
10–30%
of total stock value is typically recoverable through systematic duplicate detection and inventory rationalisation — direct working capital release without additional procurement spend.
5–20%
of MRO items in a typical asset register are duplicates — the same component held under multiple descriptions, codes or stores locations. Each duplicate represents both cost and risk.
2–10%
of annual procurement spend is attributable to maverick buying, duplicate orders and poor spend visibility — all driven directly by incomplete or inconsistent material master data.
50–70%
improvement in manufacturer name and OEM code coverage — the data that links a work order to the correct spare and enables maintenance technicians to find what they need without a phone call to procurement.
30–50%
improvement in categorisation precision following systematic enrichment — enabling meaningful spend analysis, supplier rationalisation and inventory benchmarking for the first time.
"

"Without an appropriate data foundation it is almost impossible to achieve business goals. Working with data is the first step towards success. The paradigm is simple: Get Clean. Stay Clean."

Optimal — Asset Data Management Practice
What Optimal Delivers

Three services.
One data standard.

Optimal delivers asset data improvement as a project, a programme, or a fully managed ongoing service embedded within ARaaS®. Every engagement is led by Optimal engineers — not data entry contractors — because understanding what an asset record should contain requires knowing how the asset operates.

01
Project — one-time or phased
Master Data Cleansing
A structured, systematic programme to identify and correct the data defects in your existing asset register and MRO inventory catalogue. Duplicates identified and resolved. Incorrect classifications corrected. Missing OEM references sourced and added. Obsolete records flagged and retired. The register that emerges is accurate, non-duplicated and ready for migration or ongoing use.
Duplicate item identification and resolution — single source of truth per component
Standardised material descriptions — noun–modifier format aligned to your taxonomy
OEM manufacturer name and code coverage — linking inventory to equipment BOMs
Obsolete item identification — flagged for retirement or review
Data quality report — completeness scorecard with gap analysis before and after
02
Project — with EAM implementation
Asset Data Enrichment
Enrichment goes beyond correcting what exists — it adds what is missing. Nameplate data, technical specifications, criticality classifications, maintenance-relevant attributes and UNSPSC commodity codes are applied systematically to each asset record. The enriched register supports reliability analysis, spare parts strategy, spend analytics and ERP integration in ways that a raw, unenriched register cannot.
Technical attribute enrichment — specifications, dimensions, ratings, materials of construction
UNSPSC classification — four-level hierarchy applied to every item for spend analytics and procurement
Criticality linkage — inventory items linked to asset criticality register to prioritise stocking decisions
BOM alignment — inventory records linked to equipment bills of materials and functional locations
ERP / EAM load-ready output — structured for direct import to SAP, Maximo, eMaint or equivalent
03
Managed service — under ARaaS®
Ongoing Data Governance
Data quality is not a project outcome — it is a continuous operational requirement. New items are created, equipment is modified, suppliers change, and obsolescence accumulates. Without a governance process, a cleansed register degrades back to its previous state within 12–24 months. Optimal's managed ongoing enrichment service — embedded within the ARaaS® programme — prevents re-contamination and maintains data quality as a living standard, not a historical achievement.
Real-time duplicate detection — new material requests checked against existing records before creation
New item classification — incoming parts classified and enriched to standard before entering the register
Periodic quality audits — scheduled reviews with completeness and accuracy scoring
Obsolescence management — end-of-life items flagged and alternatives identified proactively
Multi-ERP harmonisation — data governance spanning multiple systems and plant locations
How We Work

From data audit
to governed register

Every engagement follows a four-phase structured process. No data is modified without understanding what it should contain. No enrichment is completed without validation. No output is delivered without a completeness scorecard confirming the improvement achieved.

01
Data Profiling & Audit
Extraction and analysis of your existing asset register and MRO inventory catalogue. Volume, structure, completeness and quality assessed at field level. Duplicates quantified. Classification gaps identified. OEM reference coverage measured. Obsolescence risk scored. The audit produces a Data Quality Scorecard — the before picture that every subsequent metric is measured against.
Output: Data Quality Scorecard — completeness, duplicate rate, classification coverage, OEM reference gap
02
Taxonomy & Standards Alignment
Agreement on the data standards the register will be aligned to — naming convention, noun–modifier structure, UNSPSC classification level, attribute schema and criticality linkage rules. Where a client has an existing taxonomy, Optimal works within it. Where none exists, Optimal defines a fit-for-purpose standard aligned to ISO 14224, UNSPSC and the target EAM system requirements. This step is completed before any cleansing begins.
Output: Data standard definition — naming convention, classification schema, attribute framework, governance rules
03
Cleansing, Deduplication & Enrichment
Systematic processing of the asset register using Optimal's AI-assisted data management toolset — cross-referencing against industry dictionaries (ECCMA, ANGLO, DLIS, NRICSC, PIDX) and manufacturer databases to resolve duplicates, correct descriptions, add OEM references and apply UNSPSC classification. Each record is processed to the agreed standard. Items that cannot be resolved from available data are flagged for physical verification or client input — not estimated.
Output: Cleansed and enriched data set — validated, classified, OEM-referenced, duplication-free
04
Validation, Load & Governance Setup
Final quality validation against the agreed standard — completeness scoring across all fields, cross-reference checks and client review before load. Data formatted for direct import to the target EAM, CMMS or ERP system. For managed service clients, the governance framework is established at this stage — the rules, workflows and periodic review process that prevent data quality from degrading after handover.
Output: Load-ready data set + post-project Quality Scorecard + governance framework (managed service)
Platform Capabilities

AI-assisted processing.
Engineer-validated output.

Optimal's asset data work is supported by an AI-powered material master data management platform — enabling large-scale processing that would be impractical manually, while maintaining the engineering validation that distinguishes a trusted output from an automated one. The platform is the engine. Optimal's engineers are the quality gate.

AI-Powered Duplicate Detection
Automated identification of identical, similar and equivalent materials across the full register — including items described in different languages, different abbreviation conventions and different unit-of-measure formats. Detects duplicates that text-matching alone cannot find. Typically identifies 5–20% of the register as duplicatable — each a working capital and procurement risk.
Multi-ERP & Multi-Language Harmonisation
Data consolidated from multiple ERPs, CMMS systems and legacy stores databases — regardless of language, naming convention or data structure. Particularly relevant for post-acquisition consolidations where multiple systems must be harmonised into a single asset register. The platform overcomes geographical and linguistic barriers that manual reconciliation cannot manage at scale.
Automatic UNSPSC Classification
Every item classified to the UNSPSC four-level hierarchy — Segment, Family, Class, Commodity — enabling spend analytics, supplier rationalisation and procurement benchmarking for the first time. UNSPSC codes cross-referenced to eCl@ss and other industry taxonomies on request. Classification applied at the scale of tens of thousands of records without sacrificing accuracy at item level.
Real-Time New Material Checking
For ongoing managed service clients, the platform checks every new material creation request against the existing register in real time — identifying potential duplicates before they are created. The single most effective control against data quality degradation. Without it, a cleansed register accumulates new duplicates from the moment the project ends. With it, deduplication becomes a continuous operational function.
OEM & Manufacturer Reference Enrichment
Manufacturer names standardised against global manufacturer databases. OEM part numbers sourced and validated. OEM-to-MRO conversion opportunities identified — where a generic consumable can replace a proprietary part at lower cost without compromising specification. Typically 50–70% improvement in manufacturer code coverage — the data that enables fast, accurate part identification during a maintenance event.
Spend Analytics & Inventory Optimisation Reporting
Once the register is clean and classified, the platform generates spend analytics dashboards — procurement spend by UNSPSC category, supplier concentration, non-moving inventory by value and location, and duplicate stock holdings. For the first time, Supply Chain and Finance have reliable data to make inventory rationalisation and sourcing decisions from, rather than managing against an unreliable baseline.
Standards & Dictionaries

Classification frameworks
used in every engagement

Asset data enrichment without reference to recognised standards produces a taxonomy that is internally consistent but externally incompatible. Optimal aligns every engagement to the applicable frameworks — enabling interoperability, procurement benchmarking and regulatory compliance.

UNSPSC
United Nations Standard Products & Services Code — the primary global commodity classification used for MRO spend analytics and supplier management. Applied at four-level hierarchy to every classified item.
ISO 14224
Equipment taxonomy and failure mode classification — provides the technical asset hierarchy that links inventory records to equipment type, criticality and maintenance strategy across asset-intensive industries.
eCl@ss
International classification and product description standard — used as an alternative or complement to UNSPSC, particularly in European manufacturing and process industry contexts. Cross-mapping between eCl@ss and UNSPSC available.
ECCMA / ANGLO / PIDX
Industry dictionaries used for manufacturer name standardisation, technical attribute definition and OEM reference validation — providing the reference data that enrichment is cross-checked against at item level.
ISO 8000
International standard for data quality — defines the characteristics of quality data including syntax, semantic encoding, provenance and accuracy. The overarching quality framework within which all data produced by Optimal is assessed.
Engagement Models

How Optimal delivers
this service

Asset data cleansing and enrichment is delivered either as a defined project with a clear scope and deliverable — or as a managed ongoing service embedded within the ARaaS® programme. The right model depends on your current situation and long-term governance appetite.

Project Engagement
One-time or phased cleansing & enrichment programme
A scoped, time-bounded engagement to clean and enrich a defined asset register or MRO catalogue. Typically triggered by a CMMS migration, an acquisition consolidation, or the decision to finally resolve an inventory problem that has been deferred too long. Optimal delivers a defined output — cleansed, enriched, validated, load-ready data — against an agreed specification and timeline. The project ends with a Data Quality Scorecard confirming the improvement achieved and a recommendations report for ongoing governance.
Fixed scope, timeline and deliverable — no open-ended engagement
Phased approach available — tackle the highest-priority assets first
Migration-ready output for SAP, Maximo, eMaint and equivalent systems
Data Quality Scorecard — before and after — confirming the commercial value delivered
Governance framework recommendations included — to prevent re-contamination after handover
Managed Service · Embedded in ARaaS®
Ongoing data governance as a continuous operational function
A project that cleanses the register once is necessary. A managed service that keeps it clean indefinitely is transformative. Optimal's ongoing data enrichment service — delivered as part of the ARaaS® programme — provides continuous governance: new material requests checked against existing records in real time, periodic quality audits, proactive obsolescence management and multi-site harmonisation. The asset register becomes a living, governed data asset rather than a one-time project output that degrades the moment the project team leaves.
Real-time duplicate prevention — every new item creation checked before it enters the register
Scheduled quality audits — completeness and accuracy scoring on a defined cadence
Proactive obsolescence management — end-of-life items identified and alternatives sourced
Multi-plant, multi-ERP harmonisation — single standard maintained across all locations
Embedded in the ARaaS® cycle — data quality improvement feeds directly into reliability engineering and maintenance strategy
Why Optimal for This

Three things that distinguish
this from a data services firm

Asset engineers validate what the AI produces
Generic data services firms process your records algorithmically and return a file. Optimal's engineers validate the output against their knowledge of how the equipment operates and what the maintenance record should contain. A pump bearing that appears twice in the catalogue under different descriptions is not just a data duplicate — it is a decision about criticality, lead time and stocking level. That decision requires an engineer, not an algorithm.
Data cleansing connected to reliability engineering
Optimal does not deliver clean data and stop. Within the ARaaS® programme, cleansed and enriched asset data feeds directly into criticality assessment, spare parts strategy, maintenance planning and defect elimination. The data project is not an administrative exercise — it is the foundation of every reliability decision that follows. The improvement in data quality is measured in production availability and maintenance cost, not just in field completeness scores.
Global capability — Europe and Africa — single standard
Optimal operates across the UK, continental Europe, South Africa, Namibia and the broader African continent. For organisations with multi-site, multi-country asset registers — including post-acquisition consolidations across languages and ERP systems — Optimal maintains a single data standard regardless of geography. The harmonised register that emerges reflects one organisation, not a collection of independent data silos.

Ready to see what is
actually in your register?

Every engagement starts with a data profile — a structured assessment of your existing asset register or MRO catalogue that quantifies the duplicates, gaps and misclassifications before any commitment is made. You will know exactly what the problem is, what it is costing you, and what a clean register would look like. No obligation and no proposal before the conversation.

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Related Capabilities

Often delivered
alongside this service

03.04 · Digital Engineering
Enterprise Asset Management Platform
A CMMS migration without data cleansing perpetuates every existing data problem in a new system. Optimal's EAM Platform implementation and data cleansing services are designed to be delivered together — clean data migrated into a correctly configured system from day one.
Learn more →
02 · Operations & Maintenance
Spares & Inventory Optimisation
Clean, enriched, criticality-linked inventory data is the prerequisite for meaningful spares optimisation. Once the register is accurate, Optimal's spares optimisation methodology can determine correct min/max levels, identify excess stock and eliminate the critical spares gaps that cause production outages.
Learn more →
ARaaS® Framework
Asset Reliability as a Service
Asset data quality is the foundation of every ARaaS® programme. Criticality assessment, maintenance strategy, defect elimination and EAM implementation all depend on a register that accurately reflects the plant. Data cleansing is where every ARaaS® engagement should begin.
Understand ARaaS® →
GARPI™ 2026

Not sure where to start? Benchmark your asset management maturity first.

The Global Asset Reliability & Performance Index is Optimal's free industry benchmarking survey — giving you a structured view of where your organisation stands against global peers before committing to any programme.

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