The Hidden Cost of MRO Duplicate Parts: A $4.2M Case Study

By Raghu Vishwanath, Managing Partner | September 2025 | 12 min read

“We thought we had an inventory problem. Turns out we had a data problem.”

The VP of Operations at a major industrial manufacturer was reviewing the findings from our data quality assessment. His team had just discovered something shocking: 50,000+ duplicate parts sitting in their EAM system.

Not 50. Not 500. Fifty thousand.

Same parts. Different descriptions. Different part numbers. Different storage locations. All treated as unique items by their system.

Using industry-standard cost calculation methodologies, we estimated the annual impact at $3-5 million across wasted procurement spend, excess inventory carrying costs, and operational inefficiencies.

And they had no idea—until they looked.

The Invisible Problem

Duplicate parts are the silent killer of MRO efficiency. Unlike equipment failures or supply chain disruptions, duplicates don’t announce themselves. They hide in plain sight, quietly destroying value:

Procurement buys a “new” part that already exists in inventory
Warehouse stocks multiples of the same item under different SKUs
Technicians can’t find parts even though they’re in the storeroom
Emergency purchases happen because the system says “out of stock”
Annual physical inventory reveals hundreds of obsolete “unique” parts that are actually duplicates

Every organization with an EAM system has duplicates. The question isn’t whether you have them—it’s how many, and what they’re costing you.

How Duplicates Multiply (The Anatomy of Data Pollution)

Let’s follow the life cycle of a simple bearing to understand how one part becomes five in your system.

Year 1: The Original Entry

A maintenance technician needs to replace a bearing on a critical pump. He creates a part requisition:

Part Number: BRG-6205
Description: BEARING
Manufacturer: SKF
MPN: 6205-2RS

Simple. Clean. One part in the system.

Year 2: The Night Shift Emergency

Equipment fails at 2 AM. Different technician, urgent situation, can’t find the bearing in the system (searching for “6205” doesn’t match “BRG-6205”).

Emergency purchase from local supplier. New part number created:

Part Number: 6205-BEARING
Description: 6205 2RS BEARING
Manufacturer: [blank]
MPN: [blank]

Now you have two parts. Same bearing. Different records.

Year 3: The Facility Expansion

New facility comes online. Different naming convention in their legacy system. Migration creates:

Part Number: BEAR-6205-RS
Description: Bearing, 6205, Rubber Sealed
Manufacturer: SKF
MPN: 6205 2RS

Three parts. Same bearing.

Year 4: The Vendor Catalog Import

Procurement implements new vendor catalog integration. Automatic import creates:

Part Number: SKF-6205-2RS
Description: SKF Deep Groove Ball Bearing 6205-2RS1
Manufacturer: SKF
MPN: 6205-2RS1

Four parts. (Note the subtle difference: 6205-2RS vs 6205-2RS1—technically different, functionally identical for most applications.)

Year 5: The Merger

Company acquires another operation. Their EAM data gets migrated:

Part Number: 52050012
Description: BALL BEARING 25X52X15MM
Manufacturer: [blank]
MPN: [blank]

Five “different” parts in your system. All the same bearing.

Multiply this scenario by thousands of parts across decades of operations, and you understand how organizations end up with 30-40% duplicate records in their MRO catalogs.

The True Cost: More Than Just Wasted Purchases

When we presented the findings to the conglomerate’s leadership, the initial reaction was: “Okay, so we’ve got duplicates. We’ll stop buying extras. Problem solved.”

If only it were that simple.

Duplicates create a cascade of costs across your entire operation. Based on industry research and standard cost calculation methodologies, here’s how duplicate parts destroy value:

Direct Procurement Costs

Unnecessary Duplicate Purchases When parts can’t be found in the system (because they’re listed under different descriptions), procurement buys “new” parts that already exist in inventory. Industry studies show this happens in 15-25% of MRO purchases in organizations with high duplicate rates.

Additional direct costs include:

Emergency purchases at premium prices (because “regular” part couldn’t be found)
Rush delivery and expedited shipping fees
Small-lot purchasing penalties (lost volume discounts from fragmented spend)
Transaction costs from incorrect parts ordered and returned

For an organization with 50,000 duplicate records and typical MRO spend patterns, direct procurement waste alone can reach $1-2 million annually.

Inventory Carrying Costs

Excess Stock from Duplicates Every duplicate part record typically represents physical inventory sitting somewhere in your facilities. The financial impact includes:

Capital tied up: Using the industry-standard 15-20% annual carrying cost, excess inventory from duplicates represents significant locked capital
Warehouse space: In premium facilities, storage costs add up quickly
Handling and management overhead: Staff time managing redundant stock
Obsolescence write-offs: Duplicate parts that age out before being used

Research shows that organizations with 25-40% duplicate rates typically carry 20-35% excess inventory. For large industrial operations, inventory carrying costs from duplicates commonly range from $800K-1.5M annually.

Operational Inefficiency Costs

Lost Maintenance Productivity Research consistently shows maintenance technicians are productive only 25% of their time, with 75% lost to searching for information, clarifying work orders, and dealing with data problems.

The operational waste from duplicates includes:

Technician time searching for parts that “don’t exist” in the system
Work order delays while “sourcing” parts already on hand
Incorrect parts issued and subsequent rework
Storeroom time reconciling physical inventory versus system records

For a maintenance organization with 40-50 technicians, productivity losses from duplicate-driven data issues typically cost $600K-1M annually in wasted labor.

Strategic Disadvantages

Lost Negotiating Power Duplicates fragment your spend across multiple part numbers, preventing you from:

Qualifying for volume discounts (each “unique” part has low volume)
Negotiating preferred supplier agreements (can’t prove total spend)
Conducting effective competitive bidding (unclear requirements)
Making data-driven sourcing decisions (unreliable spend analysis)

For organizations with substantial MRO spend, lost strategic leverage from fragmented data typically represents $200-400K annually in missed savings opportunities.

Combined Annual Impact

For the manufacturer we worked with—operating multiple facilities with 100,000+ parts before deduplication—the estimated total annual impact fell in the $3-5 million range, based on:

Confirmed duplicate rate (26% of catalog)
Typical MRO spend patterns for their industry
Standard cost calculation methodologies
Industry benchmarks for similar-scale operations

This doesn’t include:

Lost productivity from using wrong parts
Safety risks from incorrect substitutions
Compliance issues from uncontrolled inventory
Inability to implement predictive maintenance (requires clean data)
Leadership time wasted on data firefighting instead of strategic initiatives

Why This Happens to Everyone (Even Good Organizations)

Before you judge this organization too harshly, understand: this is normal.

We’ve conducted data quality assessments for dozens of asset-intensive organizations. The duplicate rate typically ranges from 25-45% of total MRO parts records.

Why is this so universal?

1. EAM Systems Weren’t Designed to Prevent Duplicates

Your EAM platform (SAP, Oracle, Maximo, etc.) is built for transactions, not data quality. It will happily accept:

“BEARING” and “BEAR” as different parts
“6205” and “6205-2RS” as unrelated items
Blank manufacturer fields (no validation)
Any description you type (no standardization)

The system doesn’t know these are duplicates. It just stores whatever you tell it.

2. Multiple Entry Points = Multiple Standards

Parts get created by:

Maintenance technicians (focused on fixing equipment, not data quality)
Procurement staff (vendor descriptions copied inconsistently)
Storeroom personnel (inventory reconciliation creates “missing” parts)
System integrations (automated imports with different formats)
Contractors and consultants (temporary workers, no training)

Each entry point has different conventions, different rigor, different priorities. Without automated validation, inconsistency is inevitable.

3. Legacy of Mergers and Migrations

Every acquisition brings another catalog with another numbering scheme. “Consolidation” projects merge the data without truly consolidating it.

Migration tools move everything from System A to System B. But they don’t deduplicate, standardize, or validate. They just transfer the chaos faster.

4. No One Owns MRO Data Quality

Ask who’s responsible for master data quality in most organizations:

IT says it’s an operations problem
Operations says it’s a data management problem
Data management says they don’t have resources
Procurement says they just buy what they’re told

Everyone’s responsible, so no one’s accountable. Data quality becomes an orphaned issue.

5. The Problem Compounds Over Time

Duplicates breed more duplicates. When a technician can’t find a part (because it’s listed under a different description), they create a new part record. Now you have two duplicates. Next person can’t find either, creates a third.

Without intervention, the problem accelerates. A 30% duplicate rate this year becomes 35% next year, then 40% the year after.

The Wake-Up Call: How the Manufacturer Discovered the Problem

The organization didn’t set out to find duplicates. They were planning an EAM system consolidation across business units—moving from multiple legacy systems to a unified platform.

During the planning phase, someone asked a seemingly simple question: “How many unique parts do we have across all facilities?”

The answer should have been straightforward. Each business unit provided their counts:

Manufacturing Division: 85,000 parts
Energy Division: 62,000 parts
Infrastructure Division: 43,000 parts
Total: 190,000 parts

But the VP of Operations was skeptical. “That seems high for our scale of operations. Let’s verify before we migrate all this data.”

That’s when they engaged us for a data quality assessment.

What We Found

Our analysis revealed:

Actual unique parts: ~140,000
Duplicate records: ~50,000 (26% of total catalog)
Cross-business unit duplicates: 18,000 (same parts, different numbering schemes)
Within-business unit duplicates: 32,000 (even within single systems)

The duplicates fell into categories:

Type 1: Exact Duplicates (15,000 records)

Same part, different part numbers
Usually from emergency purchases or different facilities
Example: “BOLT-M12X50” and “M12-50-BOLT” for identical bolt

Type 2: Near Duplicates (22,000 records)

Slight variations in description, same functional part
Example: “BEARING 6205” vs “6205 BEARING” vs “BALL BEARING 6205”

Type 3: Equivalents (13,000 records)

Different manufacturers, functionally interchangeable
Example: SKF 6205 vs NSK 6205 (both suitable for the application)

The Reaction

The leadership team was stunned. “We’ve been managing this data for 20 years. How did we not know?”

The answer: Without systematic analysis, duplicates are invisible. They blend into the noise of day-to-day operations. Each individual duplicate is a minor inconvenience. Collectively, they’re a major business problem.

The Solution: Engineering a Clean Foundation

Once the problem was visible, the organization committed to fixing it permanently—not just temporarily.

We proposed a three-phase approach:

Phase 1: Baseline Cleansing (8 weeks)

Objective: Eliminate the 50,000 duplicates before EAM migration

Approach:

Automated duplicate detection using our proprietary algorithms
- Fuzzy matching on descriptions
- Manufacturer part number analysis
- Technical specification comparison
- Cross-reference with industry catalogs
Manual validation of flagged duplicates
- Data stewards reviewed AI-suggested matches
- Engineering team validated technical equivalents
- Business unit leaders approved consolidations
Systematic consolidation
- Established “golden records” for each unique part
- Merged transaction history from duplicate records
- Updated work orders and BOMs to reference consolidated parts
- Archived obsolete part numbers with cross-references

Results:

50,247 duplicate records eliminated
139,753 clean, validated unique parts ready for migration
1,200+ new categories defined with industry-standard classification
98.5% confidence in data accuracy post-cleansing

Phase 2: Smart Governance Deployment (4 weeks)

Objective: Prevent future duplicates from being created

Approach: Implemented Ark’s prevention-first governance platform with:

Real-time duplicate checking before new parts are added
Standardized naming conventions enforced automatically
Manufacturer part number validation against industry databases
Approval workflows for unusual or custom parts
User guidance suggesting existing parts before creating new ones

Results:

Zero duplicates created in first 6 months post-implementation
93% user adoption (high acceptance due to intuitive interface)
Average part creation time reduced from 12 minutes to 3 minutes
Confidence in catalog increased across organization

Phase 3: Continuous Monitoring (Ongoing)

Objective: Maintain data quality over time

Approach:

Automated quality scoring for all parts records
Monthly reports highlighting potential new duplicates
Quarterly audits of high-risk categories
Continuous enrichment as manufacturer data updates

Results (12 months post-implementation):

Data quality improved from 67% to 99.2% (measured by completeness, accuracy, consistency)
Duplicate rate maintained below 1% (down from 26%)
Ongoing governance sustainable with minimal manual effort

The Business Impact: Multi-Million Dollar Recovery

Twelve months after completing the project, the manufacturer measured the results:

Immediate Savings (Year 1)

The organization measured tangible improvements across all areas:

Procurement Efficiency

Eliminated majority of redundant purchases by finding existing inventory
Negotiated improved terms with consolidated spend visibility
Reduced emergency purchases significantly through better part findability
Annual procurement savings in the hundreds of thousands

Inventory Optimization

Reduced excess inventory substantially (freeing up working capital)
Repurposed warehouse space for revenue-generating activity
Cut obsolescence write-offs dramatically
Reduced inventory management overhead

Operational Productivity

Maintenance technicians found parts 85% faster
Work order cycle time reduced by 23%
Emergency work orders decreased by 41%
Measurable improvement in maintenance KPIs

Strategic Advantages

Renegotiated supplier contracts with accurate spend visibility
Implemented vendor scorecard with reliable volume data
Enabled competitive bidding for major categories with clear requirements

Total Impact: Measured savings and efficiency gains in the multi-million dollar range annually, validating the estimated impact of duplicate parts on operations.

Ongoing Benefits (Year 2+)

Beyond direct savings, the clean data enabled:

Predictive Maintenance Implementation

Required clean historical data to train models
Pilot program on critical assets showing 32% reduction in unplanned downtime
Projected to scale across operations

EAM Migration Success

Data quality eliminated major migration risk
Go-live happened on schedule with no data-related delays
User adoption higher than industry average (partly due to trustworthy data)

Strategic Decision Making

Leadership finally had reliable reports for capital planning
Procurement strategy based on accurate spend analysis
Inventory optimization model built on clean data

Continuous Improvement

Data quality became competitive advantage, not liability
Teams trusted the system, leading to better adherence to processes
Foundation for future digital transformation initiatives

The Lesson: Duplicates Are a Symptom, Not the Disease

Here’s what we learned from this engagement:

The problem isn’t duplicates. Duplicates are a symptom of a deeper issue: lack of data architecture.

Organizations treat MRO data as a byproduct of operations rather than a strategic asset. They invest millions in EAM platforms but neglect the data foundation those platforms depend on.

It’s like building a skyscraper on sand. The technology is sophisticated, but without a solid foundation, it can’t deliver value.

How to Find Your Hidden Duplicates

If you’re wondering what duplicates are costing your organization, here’s how to find out:

Option 1: DIY Assessment (Limited Accuracy)

Simple SQL Queries:

-- Find exact description matches with different part numbers
SELECT description, COUNT(*) as count
FROM parts_master
GROUP BY description
HAVING COUNT(*) > 1

-- Find similar manufacturer part numbers
SELECT manufacturer_pn, COUNT(*) as count
FROM parts_master
WHERE manufacturer_pn IS NOT NULL
GROUP BY manufacturer_pn
HAVING COUNT(*) > 1

This catches obvious duplicates but misses:

Near-matches with slightly different descriptions
Functional equivalents from different manufacturers
Duplicates across different business units or systems

Better than nothing, but typically finds only 30-40% of true duplicates.

Option 2: Professional Assessment (Comprehensive)

We offer complimentary data quality assessments that use:

Proprietary AI algorithms trained on 40 years of MRO data
Fuzzy matching and natural language processing
Industry catalog cross-references
Technical specification analysis

Assessment includes:

Sample of your data (10K-25K parts)
Comprehensive duplicate analysis
Classification gaps and missing attributes
Estimated annual cost impact
Remediation roadmap

Typical findings:

25-45% of records are duplicates
$2-8M annual impact (varies by organization size)
40-60% of parts missing critical attributes
70-80% inconsistent classification

Three Takeaways

If you remember nothing else from this article, remember:

1. Duplicates Are Universal

Every organization with an EAM system has duplicates. You’re not unique. The question is magnitude and cost—which you need to measure.

2. Cleansing Without Governance Is Temporary

Don’t waste money on another data cleansing project that degrades within months. Fix the root cause: implement systems that prevent duplicates at the source.

3. Clean Data Is a Competitive Advantage

Organizations with clean MRO data can:

Make faster, better decisions
Negotiate better with suppliers
Implement predictive maintenance
Reduce operational costs
Free up capital from excess inventory

In an industry where margins are thin and competition is fierce, data quality isn’t optional—it’s strategic.

The Bottom Line

The conglomerate’s story has a happy ending. They caught the duplicate problem before it torpedoed their EAM migration. They invested in permanent solutions, not temporary fixes. And they’re now seeing millions in annual savings.

But most organizations discover duplicates too late—or never discover them at all. They just live with the hidden costs, year after year, never realizing how much value they’re losing.

Don’t be that organization.

Find out what duplicates are costing you. Quantify the problem. Then fix it permanently.

Your EAM investment is too important to waste on dirty data.

Want to see exactly how many duplicates you have and what they're costing you?

We’ll analyze a sample of your MRO data and show you:

Duplicate count and types
Missing critical attributes
Classification gaps
Estimated annual cost impact
Remediation recommendations

No sales pitch. Just clear insights into your data—and what to do about it.

About the Author

Raghu Vishwanath is Managing Partner at Bluemind Solutions, providing technical and business leadership across Data Engineering and Software Product Engineering.

With over 30 years in software engineering, technical leadership, and strategic account management, Raghu has built expertise solving complex problems across retail, manufacturing, energy, utilities, financial services, hi-tech, and industrial operations. His broad domain coverage and deep expertise in enterprise architecture, platform modernization, and data management provide unique insights into universal organizational challenges.

Raghu’s journey from Software Engineer to Managing Partner reflects evolution from technical leadership to strategic business development and product innovation. He has led complex programs at global technology organizations, managing strategic relationships and building high-performing teams.

At Bluemind, Raghu has transformed the organization from a data services company to a comprehensive Data Engineering and Software Product Engineering firm with two major initiatives: developing Ark—the SaaS platform challenging legacy MRO Master Data Governance products with prevention-first architecture—and building the Software Product Engineering practice that partners with clients on multi-year engagements to develop world-class, market-defining products.

Raghu is recognized for bridging business and IT perspectives, making complex problems solvable. He focuses on genuine partnerships and understanding what clients truly need. His approach combines analytical thinking with pragmatic engineering—addressing root causes rather than symptoms.

Raghu continues advancing technical expertise with recent certifications in AI, machine learning, and graph databases—staying at the forefront of technologies powering modern software solutions and driving innovation in enterprise platforms.

Related Insights

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After decades watching companies waste millions governing dirty data, we built something fundamentally different. Here’s why prevention beats remediation.

5 Signs Your EAM Data is Destroying Value →

Is your EAM system delivering value or creating expensive chaos? Learn the warning signs that bad data is costing you millions—and what to do about each one.

Ready to Eliminate Your Duplicate Parts Problem?

Duplicates are costing you millions—but they’re fixable. We’ve helped organizations eliminate tens of thousands of duplicate parts and establish governance systems that prevent them from recurring.

Start with a complimentary data quality assessment to see exactly how many duplicates exist in your catalog and what they’re costing you annually.

Bluemind Solutions engineers MRO data solutions for asset-intensive industries. We don’t just consult – we build. From foundation cleansing through ongoing governance, we deliver complete solutions that transform data from liability to strategic asset.