Disjointed maintenance operations, isolated procurement processes, and fragmented inventory management often lead to a ripple effect across the organization.
Among the most frequent and costly outcomes is poor spare parts management, which is evident in the form of duplicate records, unexpected stockouts, hard-to-locate and improperly managed inventory data, and outdated or obsolete data within ERP systems.
While most organizations have ERP or CMMS platforms in place, what remains missing is a specialized, purpose-built layer of control and intelligence over their MRO spare parts data. This is precisely where Spare Parts Management Software (SPMS) comes into play.
Operational Complexity Across Spare Parts Lifecycle
Spare parts data may seem like a back-office concern but in reality, it’s a live operational asset, central to maintenance, inventory, and procurement decisions.
In complex industrial environments, be it manufacturing, energy, oil & gas, or utilities, this data is touched and modified by multiple departments, each with different priorities, systems, and processes.
The result is a fragmented ecosystem where spare parts records are incomplete, inconsistent, or outright inaccurate.
Let’s break this down across key functions:
The engineering or design function typically defines what spare parts are needed – materials, dimensions, tolerances, ratings, and usage context. This information is often stored in:
Equipment design documents
Vendor manuals and drawings
CAD files and internal standards
BOMs linked to production assets
However, very little of this data makes it to the ERP or CMMS in a structured, digitized manner.
For Example: Engineering may define a bearing as “SKF 6204 ZZ,” but the ERP might capture it generically as “ball bearing” or worse, with no description at all. There’s often no ownership to ensure that what is designed is also correctly represented in the materials master.
Procurement is primarily focused on fulfilling needs quickly – sourcing from suppliers, negotiating pricing, and issuing POs. But when material masters are incomplete or missing altogether:
Buyers create free-text PRs or material records on the fly
Vendor-specific part descriptions are entered into ERP with little standardization
No linkages are maintained between alternate manufacturers or equivalent parts
In urgent cases, they may bypass the system entirely, purchasing spares without formally adding them to the item master.
Over time, this leads to multiple entries of the same part, each with slight variations – often indistinguishable to automated systems but invisible to the user until the damage is done.
Maintenance teams operate in real time, especially during breakdowns or unplanned downtime. In such high-pressure environments:
Material codes are entered manually under duress
Incomplete records are created just to raise a work order or PR
Technicians rely on tribal knowledge or legacy naming conventions (“Pump Shaft – Line 3”)
BOMs are often outdated or maintained offline in spreadsheets
Because of this, maintenance becomes a major source of non-standard or redundant entries—where the same item may be referenced differently across departments, shifts, or plants.
Inventory and warehouse teams are expected to track and reconcile actual stock with what the ERP claims is available. But when:
Items are entered multiple times under different codes
Units of measure are inconsistent (e.g., “each” vs. “piece” vs. “unit”)
No manufacturer details or specifications are listed
– then stores personnel cannot confidently issue parts or plan for replenishment. In many cases, stockouts occur despite the item being present on the shelf, simply because the system can’t match the physical part with the correct record.
When data ownership is scattered and governance is absent, the spare parts master quickly deteriorates. Some of the most common symptoms include:
Entradas duplicadas
The same bearing or gasket is stored under 3 or 4 different codes, sometimes with slightly different specs or suppliers.
Missing Critical Attributes
Essential details like material composition, size, pressure rating, voltage, or brand may be missing, making sourcing and comparison difficult or impossible.
No Linkages to Equipment Boms and Hierarchies
Without proper associations, the system can’t predict what parts will be needed for a maintenance task - or whether they are already in stock.
Obsolete Parts Still Shown as Active
Legacy parts that are no longer manufactured continue to appear as viable options, leading to procurement delays and technical mismatches.
Approximately 15% of MRO inventory is truly obsolete, and in many cases, as much as 20–30% of spare parts are unused or written off due to obsolescence, equipment changes, or over-ordering. This creates significant waste and holding cost exposure
These issues don’t just bloat the system, they erode operational confidence. Teams stop trusting the ERP. Technicians hoard parts. Buyers double order. Everyone starts working around the system rather than within it.
When this complexity goes unmanaged, it directly affects:
Maintenance Efficiency: Delayed repairs due to part identification or availability issues.
Inventory Carrying Costs: Overstocking to hedge against data inaccuracy.
Procurement Productivity: Time lost chasing specs or clarifying part numbers.
Compliance & Audits: Discrepancies in stock vs. records during inspections.
This is where Spare Parts Management Software becomes essential, not just for cleaning up the data, but also for establishing structured workflows, intelligent automation, and governance for spare parts that persist over time.
What does a Spare Parts Management Software Does?
Gestión de piezas de recambio Software is not built to simply store spare parts records – it is always also about the equipment and bom data mapped to it, the inventory management at different plants and sites.
Spare Parts Management is engineered to resolve the root causes of poor data, fragmented processes, and inefficient sourcing that plague asset-intensive operations.
Let’s explore how its capabilities address real operational constraints.
Centralized Item Master Management
Spare parts data usually originates from multiple plant sites, warehouses, departments, and vendor systems.
With no proper centralized governance system, the item master quickly becomes fragmented – with duplicate entries, plant-specific codes, and inconsistent descriptions across locations.
Creating a clean, governed item master, helps organizations enable more accurate sourcing, faster maintenance planning, and reliable analytics across the enterprise.
A modern Spare Parts Management Software consolidates these disparate data sources into a single, unified master, removing site-level silos and enforcing global naming conventions, based on taxonomies.
Whether the data originates from SAP Material Master, Oracle Item Master, or a legacy Excel database, the software builds a harmonized structure – complete with ownership controls, audit history, and change tracking.
This centralization is essential not just for visibility, but for enforcing data integrity at the organizational level - ensuring all maintenance, procurement, and finance teams operate from the same source of truth.
Automated Classification & Taxonomy Mapping
Spare parts are pretty hard to categorize. A single valve could belong to three different categories, equipments, and machines, depending on how it’s described.
Without a well-maintained classification system, analytics, reporting, and even simple search becomes unreliable.
Using a combination of AI models, pattern recognition, and domain rules, Spare Parts Management Software classifies parts into structured taxonomies such as UNSPSC, eCl@ss, or ISO-based custom hierarchies.
These are not just tags – they form the backbone for:
Strategic sourcing initiatives
Spend visibility by category
Identification of duplicates or functional equivalents
Enhanced material search within ERP or CMMS systems
This capability also enables downstream applications like predictive demand planning and asset-based part recommendations.
Here is a walkthrough of how Verdantis’ AI agent standardizes and as per the taxonomies:
Optimización de inventarios
Without reliable visibility into spare parts movement and usage trends, inventory policies tend to swing between two extremes: stockouts and overstocking. Both have direct cost and uptime implications.
Spare Parts Management Software pulls stock levels across locations, flags non-moving, underused, and obsolete items, and recommends safety stock thresholds and reorder points based on consumption patterns, part criticality, and lead time variability.
Rather than treating inventory as a static list, it transforms it into a living dataset, dynamically adjusted based on actual operations.
Este forms the foundation of effective MRO inventory management, enabling data-driven decisions that align spare parts availability with asset maintenance needs.
And it provides the necessary context to:
Defer or cancel unnecessary purchases
Consolidate stock across facilities
Pre-position critical parts for high-risk equipment
Here’s a video that highlights how Verdantis improves inventory accuracy, reduces excess stock, and streamlines spare parts management
Implementing optimized MRO data and inventory management can result in a 50% reduction in unplanned downtime, 40% lower inventory costs, 35% decrease in maintenance budgets, and a 25% improvement in service levels.
Duplicate Detection and Data Cleansing
Duplicate entries are one of the most persistent issues in spare parts masters. Sometimes the same bearing is listed under four different item codes, with slightly varied specs or descriptions. This leads to:
- Inflated stock levels
- Inaccurate demand forecasting
- Procurement errors
- Inventory valuation discrepancies
A structured approach to spare parts and MRO data cleansing helps identify and consolidate such duplicates, ensuring that each part is uniquely and accurately represented.
It helps in improving inventory accuracy and overall data reliability across maintenance and procurement systems.
Spare Parts Management Software deploys fuzzy logic, NLP models, and semantic similarity engines to detect duplicates even when naming conventions differ. For example:
“Bearing SKF 6204-ZZ”
“Ball Brg 6204 Shielded”
“6204Z Ball Bearing, SKF”
These would be flagged as potential duplicates for review. The platform then facilitates controlled consolidation – ensuring nothing is lost, but everything is standardized.
Below is a video, how our AI agent removes L1 duplicates, and flags L2 duplicates, standardizing the data.
Cleansing isn't a one-time activity - it’s built into the system as a continuous governance loop.
Obsolescence Management & Alternate Part Mapping
Spare parts obsolescence is more than a data issue. It directly impacts asset uptime and leads to inefficiencies across sourcing and inventory.
In many cases, ERP systems continue to show items that are no longer manufactured or supported, leading to repeated failed sourcing attempts.
Spare Parts Management Software:
Flags parts based on inactivity, vendor status, and lifecycle stage
Checks availability across supplier databases or manufacturer portals
Suggests modern equivalents or alternate parts with similar specifications
Creates part equivalency groups for interchangeable SKUs
This ensures technicians and buyers are never forced to act on outdated or unsupported data. Instead, they’re given up-to-date, procurement-ready alternatives – enabling continuity without guesswork.
Here is a video of how our AI agents helps in locating obsolete parts, and suggests alternative parts
Supplier Integration & Sourcing Automation
In conventional systems, datos del proveedor is often incomplete or outdated, making it difficult to evaluate sourcing options efficiently.
Spare Parts Management Software bridges this by integrating external supplier catalogs, approved vendor lists, and real-time lead time and pricing data.
It allows users to:
View preferred suppliers for each part
Check historical PO data and pricing trends
Flag vendor-specific attributes (e.g., MOQ, delivery timelines)
Generate enriched purchase requisitions or RFQs with accurate technical descriptions
This capability is especially valuable during urgent maintenance events or when exploring strategic sourcing alternatives across global suppliers.
ERP and CMMS Integration
An isolated spare parts system is of little use if it cannot synchronize with the systems where actual operations occur.
That’s why robust ERP data integration and tight, bi-directional integration with platforms like SAP, Oracle EBS, IBM Maximo, and Infor EAM is a core capability – not an afterthought.
The software can:
Pull and update material masters directly
Synchronize BOMs and work order requirements
Push cleansed and enriched records back into ERP
Maintain referential integrity across planning, maintenance, and finance modules
This creates an end-to-end closed loop where data flows seamlessly between maintenance triggers, inventory updates, and procurement actions, with no loss of fidelity or manual duplication.
Mapping to Equipment Hierarchies & BOM Management
In any asset-intensive operation, spare parts don’t exist in isolation.
They are procured, stocked, and consumed for a reason: to support specific assets and equipment, whether it’s a centrifugal pump in a chemical plant, a gearbox in a steel mill, or a packaging line in a food processing facility.
Yet in most ERP and CMMS environments, the relationship between spare parts and the assets they serve is either weakly defined or completely missing.
Spare Parts Management Software addresses this critical gap by building and maintaining contextual linkages between:
Individual spare parts
Functional locations and equipment tags
Structured equipment hierarchies
Work orders and maintenance plans
Digital Bills of Materials (BOMs)
Here is a video of how our AI agents maps BOM data and creates hierarchical mapping
Equipment & Asset Mapping
In asset-intensive industries, effective equipment maintenance hinges on having accurate, accessible asset data – and at the heart of that data lies a clear understanding of which spare parts are needed to keep equipment running.
Every asset – whether rotating or static – has a defined set of spare parts associated with its upkeep. These can include:
Consumables (gaskets, seals, lubricants)
Replaceable mechanical components (shafts, bearings, impellers)
Electrical and control elements (sensors, actuators, relays)
Despite their importance, this mapping between equipment and spare parts is often incomplete or entirely missing in enterprise systems. In many organizations, the ERP or CMMS may only capture partial associations, if any.
As a result, maintenance teams frequently rely on tribal knowledge, legacy spreadsheets, or references to historical work orders to determine which parts are required for a given piece of equipment.
This lack of structured data leads to multiple operational inefficiencies – including delays during reactive maintenance, incorrect parts being ordered or installed, and difficulty forecasting spare part demand based on actual asset usage.
The absence of clear linkage between assets and spares often stems from gaps in the underlying asset master data used in maintenance workflows.
Without this foundational data being complete and consistent, even the most advanced ERP or CMMS platforms fall short in supporting effective maintenance planning.
Spare Parts Management Software addresses this by enabling structured mapping between parts and equipment hierarchies. It does so by:
Ingesting equipment data from ERP, EAM, or CMMS
Linking spare parts to equipment based on past usage, BOMs, and technical documentation
Maintaining a searchable association between functional locations and part records
Enabling impact analysis – so if a part is flagged as obsolete, users can see which assets will be affected
This structured approach not only improves day-to-day maintenance planning but also supports impact analysis.
For example, if a part is flagged as obsolete, users can instantly identify which assets are affected and plan substitutions accordingly.
Ultimately, this level of traceability empowers planners and technicians to navigate from equipment to its required parts – and vice versa – with confidence and clarity.
BOM (Bill of Materials) Management
Bills of Materials (BOMs) serve as the blueprint for how industrial assets are constructed, maintained, and serviced. They provide a structured breakdown of the components, subassemblies, and spare parts required for each asset.
A well-maintained BOM doesn’t just list parts – it plays a strategic role in enabling preventive maintenance planning, aligning inventory levels with actual asset needs, and driving standardization of parts across asset classes and facilities.
Unfortunately, in many organizations, BOMs are far from complete or reliable. They are often missing altogether from enterprise systems or exist only as unstructured PDFs and legacy engineering drawings, disconnected from real-time operations.
Even when available, these BOMs may not reflect recent modifications – such as retrofits, emergency repairs, or substituted parts – leading to discrepancies between what is needed and what is recorded.
Moreover, they’re frequently disconnected from the master data repository, meaning the parts listed in the BOM cannot be easily traced or validated in the ERP.
This misalignment creates confusion during procurement, increases the risk of incorrect parts being ordered, and hampers maintenance effectiveness.
Effective spare parts management software addresses these challenges by digitizing, validating, and linking BOMs directly to item masters and equipment hierarchies, turning them from static documents into dynamic, operational tools.
Spare Parts Management Software modernizes BOM management by:
Digitizing legacy BOMs from scanned documents, drawings, or spreadsheets using AI-powered document extraction agents
Normalizing part data within the BOM—ensuring that each part listed is traceable, standardized, and enriched in the master database
Establishing parent-child relationships between assemblies, subassemblies, and individual spares
Automatically updating BOMs when part records are enriched or replaced with alternates
This ensures that every BOM becomes a live, system-connected artifact, rather than a static document buried in an archive.
Real-World Enrichment Workflows within SPMS
Just like how Verdantis’ Auto Enrich AI operates, modern SPMS platforms can automate enrichment for MRO and spare parts using the following structured methods:
A. Enrichment from Public Sources
Utilizes verified online supplier catalogs and OEM portals to complete missing fields in the spare parts database.
E.g., Manufacturer name, part number, datasheets, dimensional specs.
B. Enrichment from First-Party Sources
Listas de materiales digitales: Links spare parts with specific equipment hierarchies.
Work Orders: Extracts part usage history from historical maintenance records.
Equipment Drawings: Parses technical diagrams for part specifications.
Invoices & POs: Backfills missing data when ERP entries are created post-procurement.
These are parsed using AI agents capable of document intelligence, transforming unstructured files into structured, actionable records in bulk.
| Característica | ERP | GMAO | Spare Parts Management Software |
| Enfoque | Financial & transactional data | Maintenance task tracking | Spare part lifecycle & inventory |
| Data Quality | Generic item master | Dependent on ERP integration | Specialized classification & cleansing |
| Optimization | Limitado | Indirect | Direct support for optimization strategies |
| Obsolescence Tracking | Manual | Minimal | Automated alerts & replacements |
How AI and ML Are Enhancing Spare Parts Management
Spare Parts Demand
For preventing the spare part failures, and predictive manitenance AI models analyze historical maintenance records, sensor data from equipment, and patterns in asset utilization to understand when specific parts are likely to fail or require replacement.
This predictive capability allows organizations to proactively stock critical components, avoid last-minute procurements, and reduce downtime caused by part unavailability.
Based on Technical Attributes
Machine Learning algorithms can automatically categorize spare parts using structured and unstructured data – such as part descriptions, datasheets, or manufacturer catalogs.
These models reduce manual classification errors, accelerate the onboarding of new items, and ensure consistency across taxonomies like UNSPSC, eCl@ss, or internal schemas.
Interchangeable Parts
AI tools can identify alternate parts by analyzing dimensional, material, and functional equivalencies, even when brand or model numbers differ.
This is especially valuable when original parts become obsolete or unavailable, allowing organizations to minimize disruption and maintain equipment continuity.
Procurement Inefficiencies
By monitoring purchasing trends and part usage patterns, AI can surface anomalies such as duplicate orders, unusual price fluctuations, or non-preferred vendor usage.
These insights help procurement teams take corrective actions, enforce sourcing policies, and reduce costs associated with inefficient processes.
Together, these AI and ML capabilities lead to smarter, faster decision-making, better part availability, and improved spare parts lifecycle efficiency.
Choosing the Right Spare Parts Management Software
When evaluating solutions, consider:
Compatibility with your ERP/CMMS systems: Ensure the software integrates natively with your existing enterprise systems—such as SAP, Oracle, IBM Maximo, or Infor.
Without tight integration, clean data and insights cannot flow freely across procurement, maintenance, and finance functions, limiting the platform’s effectiveness.
Ability to handle multi-site, multi-language, and multi-currency data: If your operations span regions or countries, the platform should be able to handle variations in languages, currencies, unit systems, and plant-specific terminology.
This capability is essential for standardizing data across global footprints and enabling unified reporting and governance.
Data cleansing and enrichment capabilities: Look for a solution that can handle legacy and poor-quality data by identifying duplicates, filling missing attributes, and standardizing nomenclature using AI.
A clean, enriched item master lays the foundation for effective planning, sourcing, and inventory control.
AI/ML-based features for automation: Modern platforms should go beyond basic master data tools and offer AI/ML-driven automation—such as intelligent classification, alternate item suggestions, or dynamic demand forecasting. These features reduce manual intervention, accelerate decision-making, and improve data quality continuously.
Scalability and vendor support: The solution should scale easily with your growing asset base, increased spare parts data, and evolving operational requirements.
Equally important is strong vendor support – ranging from implementation assistance to ongoing training and technical support—to ensure sustained success.
Spare Parts Management Software
Below are some of the companies, that provide spare parts management software:
Verdantis offers SpareSeek, which offers AI-driven solutions for managing and optimizing spare parts data.
Its AI agents specialize in classifying parts, identifying duplicates, enriching missing attributes, and mapping BOMs to equipment data.
Using AI-powered aftermarket parts planning tools can cut spare parts inventory levels by up to 30%, while improving service levels up to 97% through more accurate demand forecasts.
Here are a list of industries that Verdantis caters to:
Below is a walkthrough of our Spare Parts Management Software:
Hexagon, through its NRX AssetHub platform, helps organizations improve the quality and structure of their spare parts and maintenance data.
It offers features like equipment-to-spare-part mapping, BOM creation, and seamless integration with SAP and IBM Maximo. NRX is widely used in industries such as energy, chemicals, and heavy manufacturing.
It is an enterprise asset management (EAM) solution with built-in capabilities for spare parts tracking, maintenance work orders, inventory forecasting, and supplier management.
It supports structured BOM integration and is especially popular in industries like transportation, energy, utilities, and oil & gas.
Infor EAM provides a modern, cloud-based solution that integrates asset management with spare parts inventory, purchasing, and lifecycle planning.
Its flexibility and depth make it suitable for manufacturing, healthcare, public infrastructure, and utilities. Infor focuses heavily on aligning asset health with spare part availability.
PartAnalytics is an AI-powered platform that helps companies classify parts, find alternate suppliers, reduce sourcing risk, and improve part visibility.
It focuses on procurement and engineering use cases, particularly where data normalization and sourcing insights are critical for cost control and lead-time reduction.
e-Emphasys provides an integrated ERP system for equipment dealerships and rental businesses.
It includes advanced spare parts and inventory management capabilities tightly connected to equipment service history, rental data, and customer support.
The platform is tailored for industries like construction, agriculture, and heavy machinery.
Syncron delivers a spare parts inventory and aftermarket management platform designed for OEMs and industrial equipment manufacturers.
Its strengths lie in demand forecasting, safety stock optimization, and service parts availability – making it ideal for organizations focused on after-sales service and global distribution networks.
Conclusión
As assets become more complex and supply chains more volatile, Spare Parts Management Software isn’t just a nice-to-have, it’s a competitive necessity.
With the right solution in place, organizations can reduce costs, boost reliability, and make informed decisions rooted in clean, actionable data.
