MRO Data Classification and Cleansing for a Global Shipping Contractor: 198,000 Items, 100% Accuracy, 26% Faster Procurement

Client Profile

Renowned Contractor Delivering Engineering & Construction Services to the Shipping Sector

The client is a Switzerland-headquartered engineering and construction contractor serving the global shipping industry. Founded in 1985, the company provides repair, retrofit, and maintenance services for ships and marine equipment. Its operations span commercial shipping, fleet management, and port infrastructure across multiple international markets.

Project Scope

MRO Data Classification and Cleansing for 198,000 Shipping Items

The client required classification and cleansing of MRO data for 198,000 items, including ship repair equipment, mechanical parts, communication equipment, navigation tools, and small parts. The core objectives of the engagement were defined by three key requirements:

  • MRO Data Classification: Accurately mapping complex industrial components to UNSPSC standards at the commodity level.
  • Data Cleansing: Standardizing formatting, resolving inconsistencies, and correcting legacy errors to ensure database integrity.
  • Data Enrichment: Filling the missing attribute values and updating critical product specifications to improve inventory visibility.

To maintain strict quality control across the high-volume dataset, the project was executed in two strategic phases:

  • Phase 1: Processing the initial 100,000 items, which included establishing the baseline classification workflows, cleansing protocols, and validation standards.
  • Phase 2: Processing the remaining 98,000 items utilizing the optimized workflows and established data matching procedures.

To address the technical complexity of the taxonomy, the client required a specialized team of domain experts with demonstrated proficiency in MRO operations, UNSPSC standards, and advanced Excel skills.

Key Challenges

Strict Deadlines, Commodity-Level Precision, and Domain-Specific Complexity

Three factors defined the difficulty of this engagement:

  • Short Delivery Window: The entire 198,000 items had to be classified within 45 days, leaving no margin for rework cycles or delays in ramping up resources.
  • Extensive classification hierarchy: The client required commodity-level UNSPSC codes, not segment, family, or class-level codes. Every item needed to be resolved to its most specific applicable category within the shipping and marine context.
  • Immediate Team Alignment: Resources had to be trained on the specific product landscape — covering mechanical parts, marine hardware, navigation equipment, and accessories — before deployment, without affecting the project timeline.

The Solution

Structured MRO Data Classification & Cleansing for Faster Procurement and Streamlined Inventory Management

Data Cleansing and Enrichment

Before classifying MRO and shipping data, we audited all 198,000 item records for data quality. Our team identified and rectified missing part numbers, incorrect descriptions, and product attributes to reflect current specifications.

This step ensured classification decisions were based on accurate, complete, and standardized data inputs.

Item Description Review

Each item description was reviewed individually to determine product type, application, and relevant characteristics within the MRO and shipping context. This step was critical for separating similar items, as it improved the classification reliability and reduced the risk of generic mapping.

Step 3 — UNSPSC Code Assignment

Based on the description analysis, a UNSPSC code was assigned to each item.

Code selection was guided by the item's function and product type — e.g., mechanical parts, navigation systems, ship repair equipment, communication devices — and aligned with UNSPSC hierarchy standards applicable to the marine and industrial sectors.

Step 4 — Unit of Measure (UOM) Assignment

Each item was assigned an appropriate UOM alongside its UNSPSC code.

Smaller components, such as fasteners and seals, were classified as “pieces”; larger systems, such as propellers, navigation systems, and ship engines, were classified as “units” or “sets”. Accurate UOM assignment was a prerequisite for correct commodity-level placement within the UNSPSC hierarchy.

Step 5 — Commodity-Level Data Classification

All items were classified at the commodity level, i.e., the most detailed tier of the UNSPSC framework. For example, insted of categorizing items broadly as "marine equipment" or "mechanical parts," each part was mapped to a specific subcategory such as hull fittings, engine components, marine pumps, or mooring equipment. This level of specificity was applied uniformly across all 198,000 records.

Step 6 — Quality Control

A three-tier QC process was applied throughout:

  • Tier 1 (Self-check): Each classifier reviewed their own work before submission.
  • Tier 2 (Team lead review): The group head or assistant team lead reviewed completed batches for consistency and accuracy.
  • Tier 3 (Account manager spot checks): Random audits were conducted by the account manager to verify classification accuracy against client standards and internal benchmarks.
Measurable Impact

High-Accuracy Classification Delivered Within Agreed Timelines

100%

data accuracy

All items were correctly classified into their UNSPSC categories.

198,000

items classified on the schedule

Both phases were completed within the stipulated 45-day window.

26%

drop in order turnaround time

Reduction in procurement lead time improved order management.

17%

improvement in inventory visibility

Client’s asset tracking and retrieval improved across the MRO inventory.

Contact US

Looking for MRO Data Classification or Master Data Management Support?

Data4eCom delivers UNSPSC classification, data cleansing, and MRO master data management to help enterprises organize complex product data for higher inventory accuracy and more efficient procurement. With domain specialists who understand your industry, we deliver accurate, procurement-ready data at scale.

Write to us at info@data4ecom.com.

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