Digital Tools Solving MRO Lead Time Issues

MRO lead times are a costly bottleneck for industrial automation. With downtime costing the top 500 industrial firms €1.3 trillion annually, delays in sourcing critical parts like PLCs or motion controllers - sometimes taking over 52 weeks - can cripple production. Manufacturers face two major problems: excessive spare part inventories that tie up capital and frequent stockouts of essential components.

Key challenges include:

• Long lead times: Some components take 20–52 weeks to procure.
• Inefficient processes: Manual data entry and fragmented systems delay procurement.
• Inventory mismanagement: Up to 50% of spare parts remain unused for years, while critical parts are often unavailable.
• Poor data quality: Duplicate entries and errors in ERP systems cause "invisible stock."

Digital tools are addressing these issues by:

• AI-powered forecasting: Predicting part needs based on equipment lifecycle and historical data, reducing emergency orders and cutting inventory costs.
• Real-time inventory platforms: Synchronizing stock data across sites to prevent redundant purchases and improve availability.
• Cloud-based collaboration: Connecting teams and standardizing data for faster decision-making.

Solutions like Automa.Net streamline MRO procurement by integrating supplier networks, automating part identification, and offering tools like BOM Search and AI-driven quote management. Companies using such platforms report reduced lead times, lower inventory costs, and improved efficiency.

The bottom line: Digital tools are transforming how manufacturers manage MRO, saving time and money while minimizing downtime risks.

Why MRO Lead Times Get Delayed

To understand why lead times stretch from days to months, it's important to look beyond shipping delays. The real culprits are fragmented systems, manual workflows, and supply chains that struggle to keep up with today's demands.

Supply Chain Problems and OEM Delays

When a critical component fails, the pressure is on. Yet, vendor production lead times often feel like a "black box" - buyers have little to no insight into the vendor's production schedules or raw material availability. This lack of transparency makes every order somewhat of a gamble. For example, lead times for motion controllers can stretch to 30–50 weeks, while PLCs may take 20–36 weeks.

OEMs often add to the problem by shifting financial risks downstream. Dr. Lukas Biedermann, COO at SPARETECH, explains:

"OEM spare parts packages are typically oversized by design. Spare parts are an after sales business, and risk is shifted away from the OEM and onto the manufacturer".

These oversized packages, sold during machine ramp-ups, often include parts that go unused. On average, 22% of MRO inventory sits untouched for over five years. At the same time, 45% of manufacturing executives cite poor inventory visibility across sites as their biggest challenge. This creates a frustrating paradox: warehouses overflow with unused parts, while production lines are left waiting for critical components.

But it's not just external supply chain issues causing delays. Internal inefficiencies play a big role too.

Disconnected Data and Manual Work

Sometimes, internal processes delay parts even more than shipping. Manual approvals and data entry can take longer than the actual transit time. As F7i.ai highlights:

"If your internal approval process takes 48 hours, and the vendor ships overnight, your administrative lead time is 200% longer than the transportation time".

Data fragmentation makes matters worse. When parts are tracked using vendor-specific SKUs instead of standardized manufacturer codes, or when crucial details like frame size or protection class are missing, the system grinds to a halt. Maintenance teams often face "invisible stock" - items that are physically in the warehouse but can't be found in the ERP system due to duplicate entries, typos, or inconsistent naming. Instead of wasting time searching through flawed databases, technicians often reorder parts, further extending lead times. This lack of trust in the system leads to workarounds that only deepen the issue.

Poor data management doesn't just slow things down - it also throws off demand forecasting, making inventory problems even worse.

Poor Forecasting and Inventory Problems

With lead times for sensors ranging from 18–32 weeks and collaborative robots taking 26–52 weeks, even a minor forecasting error can disrupt production for months. Surprisingly, 32% of manufacturers report frequent stockouts of critical spare parts while simultaneously holding excess inventory. This contradiction stems from data mismanagement, not actual shortages.

Bryan Hellman from Industrial Automation Co. explains the stakes:

"When a single failed controller card with a 26-week lead time forces a line to run at 60% capacity for months, the cost isn't measured in purchase orders - it's measured in lost throughput, premium freight, expedited labor, and delayed customer shipments".

The financial impact goes far beyond the cost of the part itself. Carrying costs for MRO inventory typically range from 20–30% of the inventory's value annually. Meanwhile, 48% of procurement executives cite high inventory expenses as a major challenge, with this figure rising to 61% in the United States. When forecasting fails, companies pay twice: once for parts they don't need and again for production they can't maintain.

These challenges highlight why digital tools are becoming essential in transforming MRO procurement processes.

How Digital Tools Fix MRO Lead Time Problems

Digital tools are transforming how Maintenance, Repair, and Operations (MRO) processes are managed by automating outdated workflows and improving forecasting. By moving away from manual spreadsheets to intelligent platforms, businesses can better manage spare parts and reduce delays.

AI-Powered Demand Forecasting

AI-driven forecasting tools predict spare part needs by analyzing equipment life cycles and historical failure data. Unlike static min/max inventory systems that rarely adapt, these tools flag shortages and recommend stocking adjustments in real time. They take into account factors like supplier performance and network risks, leading to more precise inventory planning.

The impact is notable: AI forecasting can improve fill rates by up to 92%, significantly reducing the need for emergency shipments. For instance, a global mining company using Verusen’s AI platform unified materials data from multiple ERP and EAM systems. Within just 90 days, the platform identified over 3,000 duplicate materials, resulting in a 10% to 20% reduction in working capital and approximately €18.5 million in cost avoidance. Verusen’s semantic matching capabilities also uncover "hidden" inventory across warehouses by identifying functionally identical parts, cutting part identification time from 30–45 minutes to under 10 seconds.

Once forecasting is optimized, real-time inventory management ensures seamless availability of parts across facilities.

Real-Time Inventory Management Platforms

Real-time inventory platforms synchronize stock data across multiple production sites, helping companies avoid redundant purchases by identifying where critical parts are already available. Martin Weber, CEO of SPARETECH, highlights the inefficiency in current systems:

"Manufacturers keep millions of spare parts in stock in their production networks without realising that up to 50% of these parts have not been used in the last three years"

Take Hymmen, an industrial machinery manufacturer, as an example. In May 2026, they adopted the PartsOS Planning platform to transition from manual procurement to AI-driven management. By connecting the platform to their ProAlpha ERP system, the company achieved remarkable results in just a few weeks: manual planning efforts dropped by 80%, inventory levels decreased by 20%, and spare parts availability improved by 20%. Michel Ahring, the company’s Head of Division Service, described the transformation:

"What was once reactive and manual is now proactive, automated, and fully under control"

These platforms also clean up messy master data by identifying duplicates and standardizing part numbers, reducing search times by 30–40%. Automated agents within the systems further streamline operations by triggering planning tasks and generating order recommendations based on historical demand, reducing dependency on manual intervention.

To complement these inventory tools, cloud-based platforms enable better collaboration and decision-making across teams.

Cloud-Based Collaboration Tools

Cloud platforms bring maintenance, engineering, and purchasing teams together on a unified, data-driven interface. Often referred to as "Industrial Reliability Networks", these tools standardize and enrich data across thousands of organizations, making the system smarter over time. They also ensure that stocking recommendations are implemented through review and approval workflows, speeding up responses to critical shortages.

These platforms also capture and retain team expertise, preserving standards for interchangeable replacements even as personnel change. Acting as a "decision layer" above the ERP, cloud tools integrate data to push approved stocking policies and transfer recommendations back into the main system. Companies using AI-powered cloud platforms for MRO typically experience a 10–20% reduction in working capital and achieve an average ROI of 10x.

Automa.Net: A Digital Solution for MRO Lead Times

Automa.Net tackles the challenge of sourcing the right part at the right time by connecting buyers with a global network of over 600 verified suppliers and 3,500 industry experts - all through a single, streamlined platform.

Main Features of Automa.Net

AutomaSEARCH delivers real-time insights into stock levels, prices, and lead times for over 37 million spare parts. With 18 million offers processed daily, users no longer need to manually check multiple distributor websites or exchange Excel files.

The Request Board is a go-to solution for sourcing hard-to-find or obsolete components. When a standard search doesn’t yield results, users can submit a 7-day request, inviting direct responses from suppliers with unlisted inventory.

Data standardisation eliminates confusion and speeds up processes by consolidating 140 inconsistent product condition descriptions into just 8 categories. Terms like "new", "factory sealed", "refurbished", or "used" are now uniformly understood.

The BOM Search feature allows procurement teams to upload entire Bills of Materials for bulk sourcing, while the WatchList sends notifications when critical out-of-stock items become available. Additionally, the Deals Module simplifies RFQ management by centralizing requests from email, phone, and web into one dashboard. Paired with AutomaQUOTE, it even uses AI to draft quote responses.

Benefits for Industrial Automation Users

These features bring clear advantages to users in industrial automation. Take PLC-City for example - a global industrial automation broker with a €50 million turnover. In April 2024, they onboarded 30 users onto Automa.Net. By standardizing 140 product condition descriptions into 8 categories, they significantly reduced the time needed to check stock availability and handle customer inquiries.

"With improved efficiency and capabilities, PLC-City can now better serve its customers and continue to grow its global presence in the automation distribution sector".

For distributors, brokers, and system integrators, the platform also provides AutomaINSIGHTS, a set of market intelligence tools that reveal pricing trends and demand patterns. The Global Availability API integrates seamlessly with ERP systems, giving purchasing teams real-time stock visibility without interrupting their workflows.

How Automa.Net Improves Operations

Automa.Net doesn’t just simplify search and procurement - it transforms operations. It addresses three major challenges: cutting search times, improving data accuracy, and resolving supplier fragmentation. With its API standardizing manufacturer part numbers and brand names, manual identification time drops from 30–45 minutes to just seconds. By automating supplier matching and streamlining processes, the platform significantly shortens MRO lead times.

For companies managing surplus inventory, Automa.Net offers three recovery options:

• Outright sale: Receive 3–20% of market value.
• Consignment: Earn 50%, with storage and marketing included.
• Marketplace listing: Sell at 75–85% of market value.

This is especially useful given that opening a factory-sealed box for an MRO spare part can reduce its market value by an average of 27%, while resellers typically move only 25–30% of surplus stock in the first year.

Lastly, the platform includes B2B finance tools offering 30- or 60-day payment terms, easing international transactions and reducing credit risks.

Using Digital Tools to Reduce MRO Lead Times

Effective integration of digital tools is the next big step in streamlining MRO (Maintenance, Repair, and Operations) processes.

Steps for Integration

The integration process starts with a thorough audit of all ERP systems, suppliers, and material records. This audit pinpoints which categories stand to gain the most from automation. Once that's done, centralizing ERP data is essential. This step helps standardize materials and identify duplicates before moving to full-scale automation. For platforms like Automa.Net, API integration plays a crucial role by enabling smooth synchronization with systems like SAP, Oracle, or CMMS, which helps eliminate manual data entry errors.

Pilot programs are a great way to showcase the potential of these tools. For example, a 30-day trial focusing on 100–1,000 high-friction parts can provide a clear return on investment before rolling out the solution across the organization. AI-powered photo identification can also be optimized by ensuring clean nameplates and proper lighting, achieving over 90% accuracy. Automated workflows can then process high-confidence data matches directly into the ERP, while exceptions are flagged for manual review. This "fast lane" approach drastically reduces operational costs - by as much as 97% in some cases.

Traditional vs. Digital Methods

Digital tools bring a host of advantages over traditional methods, as shown below:

These distinctions underline the operational advantages of digital tools.

Results from Digital Tools

Once integration and standardization are complete, the benefits become clear. For instance, RUD Ketten Rieger & Dietz GmbH partnered with Facturee, a digital procurement specialist, in 2021. By December 2025, they had halved their procurement lead times and cut administrative efforts by 20% across 132 orders.

Similarly, North America's largest downstream oil refining company leveraged a digital platform for four years, uncovering €73 million in savings opportunities. Specifically, €9 million was saved by consolidating suppliers and eliminating duplicate materials across multiple sites.

Overall, companies using digital tools have reported cutting frozen capital by 15–30%, reducing material review times by 60%, and lowering procurement costs by 37% through AI verification. These results highlight the transformative potential of digital tools in MRO processes.

Conclusion

MRO lead time issues stem from supply chain disruptions, fragmented data systems, and poor forecasting, which can lead to both operational inefficiencies and financial strain.

Digital tools are proving to be a direct solution to these challenges. For instance, AI-powered data standardisation speeds up part identification by 30% while eliminating duplicate entries. Real-time inventory tracking across multiple locations helps avoid unnecessary purchases, and cloud-based platforms connect buyers with verified sourcing experts seamlessly.

The benefits are clear: companies report a 15–30% reduction in locked-up capital, an 8–15% drop in procurement costs, and a 35% boost in technician efficiency.

"MRO data standardisation is much more than just housekeeping. It is a core reliability discipline." – Automa.Net

Automa.Net stands out with its AI-driven part matching, cross-site inventory synchronisation, and a Request Board that links users to 3,500 sourcing specialists. These features collectively ensure a stronger and more reliable MRO procurement process.

FAQs

Which MRO parts should we digitise first to reduce lead times fastest?

To cut down lead times effectively, start by digitising parts that are essential for keeping operations running smoothly, as well as components frequently used or needed for regular maintenance. Pay particular attention to items that are harder to identify - like those with serial numbers or specific technical parameters - since tools like AI scanning can make managing these much easier. This strategy ensures better inventory accuracy, reduces mistakes, and simplifies procurement workflows, helping you achieve quicker lead times and greater overall efficiency.

How can duplicate and inconsistent spare-part data be fixed without disrupting SAP/ERP workflows?

To address duplicate and inconsistent spare-part data without interfering with SAP/ERP workflows, digital tools play a key role in streamlining data management. These tools are designed to handle tasks like identifying duplicates, correcting errors, filling in missing information, and standardising data attributes across multiple systems. By embedding these processes within your current workflows, you can enhance data accuracy and reliability while keeping disruptions to a minimum.

What’s the quickest way to start using Automa.Net for hard-to-find or obsolete parts?

The quickest way to find rare or obsolete parts on Automa.Net is by using the Request Board. All you need to do is post your request with the specific part details. Verified suppliers will then provide you with tailored offers. This approach makes the entire process much more efficient compared to conventional sourcing methods.