Top 10 Challenges in Spare Parts Management

Paweł Bęś, Logistics and Maintenance Marketing Expert, QRmaint

Posted 4/16/2026

Do you know which issues are most problematic in spare parts management? Well, there are multiple issues with the approach to handling the high volume of your spare parts. There is actually no one-time optimal setup for your spare parts. A funny fact from the ’90s in the USA: of all spare parts at MARS, 40 percent had no usage during 1995-1997, and even 80 percent had no usage in the last half year. Only 1.15% of spare parts had a mean usage of more than 0.15 per day. Let’s remember the cost of inflation at that time; today, it’s about 2.5% higher per year than then. Quick calculations, but they give relevance to the costs in this area.

This article outlines key problems in spare parts management and practical solutions for manufacturing plants.

What are the problems with spare parts management in maintenance?

1. Before diving into the main challenges, it’s important to understand that spare parts management faces several complex issues. These challenges, especially those related to rising maintenance costs and aging equipment, often result in obsolete inventory and tied-up capital. Experts have proposed methods to integrate obsolescence risk into inventory control and demand forecasting. Here are the key problems:

Even smaller equipment manufacturers are often tasked with managing inventories of more than 100,000 distinct parts. Major Original Equipment Manufacturers (OEMs) can be responsible for overseeing more than one million items. The sheer magnitude renders manual oversight impractical and necessitates advanced, systematic intervention.

2. High Cost of Stock-Outs

Service level requirements are exceptionally high because machine downtime is often catastrophic. A missing spare part can halt entire production lines, resulting in significant productivity losses and financial penalties, especially when governed by Service Level Agreements (SLAs).

3. Intermittent and “Sparse” Demand

Unlike retail goods, spare parts often have “thin” demand patterns. They are needed only occasionally and in very low volumes. This makes it difficult to find a meaningful “average” or trend to follow.

4. Failure of Classic Forecasting Models

Traditional methods like moving averages or linear regression were designed for “thick” demand (high-rotation products). When applied to spare parts, these models often return a statistical forecast of zero, which is mathematically “accurate” but useless for inventory planning.

5. Misleading Accuracy Metrics

The industry-standard MAPE (Mean Absolute Percentage Error) is often insufficient for measuring performance. Relying solely on minimizing forecast error in spare parts may inadvertently drive inventory to zero—missing the actual objective: ensuring the required parts are reliably available when failures occur.

6. Flawed “Mean” Forecast Logic

A traditional forecast centers on the statistical mean, implying a 50% likelihood of deviation above or below actual need. Achieving service levels above 90% requires extrapolation through safety stock calculations—a process that introduces significant inaccuracies as the desired reliability threshold increases.

7. The “Normal Distribution” Fallacy

Conventional safety stock theory presumes demand follows a Normal (Gaussian) distribution. While this method applies to high-volume goods, spare parts demand is inherently sporadic and count-based; the normal curve does not accurately reflect this reality.

8. Separation of Forecast and Replenishment

Standard technology treats forecasting and inventory policy (reorder points) as two separate steps. This “lossy” process often fails to transform demand data into an actionable, reliable stock level.

9. Asymmetrical Risk (Under-stocking vs. Over-stocking)

In spare parts, the cost of being “too low” (a stock-out) is usually much higher than the cost of being “too high” (holding an extra part). Classic models often struggle to weigh these risks appropriately, whereas newer approaches, such as quantile forecasting, use specific functions (e.g., “pinball loss”) to bias results toward safety.

10. Complexity of Lead Times

Effective inventory management requires not only accurate demand prediction but also precise calculation for the relevant lead time. Legacy models seldom provide direct methods for establishing minimum inventory levels that adequately mitigate the risk of a stock-out during replenishment periods.

Based on the issues mentioned earlier—such as high volume, aging equipment, obsolete inventory, and the high cost of downtime—here is how a solution like QRmaint CMMS addresses these specific “spare parts management” problems.

Solutions for Spare Parts Management

1. Managing complex spare parts inventories for aging equipment is no longer an insurmountable task. Modern software platforms are engineered to resolve these challenges efficiently and systematically:

Insufficient visibility into existing inventory and storage locations remains a primary operational weakness.

The Solution: QRmaint uses QR codes and barcodes to automate the distribution and reception of parts. By simply scanning a code with a mobile phone, a technician can instantly withdraw a part, ensuring the digital inventory matches the physical shelf.

2. Preventing “Stock-Outs” through Minimum Levels

As previously outlined, tracking mean usage rates as low as 0.15 per day is inherently challenging, yet overlooking such items can result in substantial operational and financial consequences.

The Solution: You can set minimum stock levels for every part. When the inventory drops below your safety threshold, the system alerts you immediately. This prevents the “long downtime and financial losses” that occur when a critical repair is stalled by a missing 10-cent screw.

3. Solving the “Obsolete Inventory” Problem

Aging equipment often leads to “zombie” parts—inventory that sits on shelves for years (as shown in the MARS data: 80% of inventory is non-usage).

The Solution: QRmaint provides a full history of inventory changes. You can see exactly which parts are moving and which are just gathering dust. This transparency allows managers to clear out obsolete stock and free up working capital.

4. Direct Link: Parts to Work Orders

Often, parts disappear because they aren’t logged against a specific machine or repair.

The Solution: The software keeps you “in the loop” by tracking which employee took which part and for which specific work order. This accountability reduces “shrinkage” and helps calculate the true maintenance cost of aging assets.

5. Proactive “Preventive” Maintenance

Waiting for machinery to fail before acting is inefficient. Proactive maintenance planning is essential for sustainable operations.

The Solution: Use the graphical schedule to automate preventive tasks. By scheduling inspections and parts replacements based on a calendar or machine readings, you reduce the “emergency” demand for spare parts, making your supply chain more predictable.

6. Real-Time Communication (ANDON & Dashboards)

In contemporary manufacturing, every minute of unplanned downtime translates into an immediate financial loss, especially when adjusted for inflation.

The Solution: The ANDON system and Dashboard TVs show the real-time condition of the machine park. When a failure is reported via a mobile app, the maintenance team gets a PUSH notification instantly. This reduces response times by 40%–50%.

Summary

Well, it may not give you direct answers for all spare parts issues, but it should now be clearer that you are not ‘on an island’ when it comes to this subject. Keep in mind that there is always a solution available through digitalization and QR code tagging for a CMMS system (one of the prime examples).

Avoid legacy practices in spare parts management. Gain comprehensive visibility and accuracy in your inventory processes.

Paweł Bęś

Paweł Bęś, Logistics and Maintenance Marketing Expert for QRmaint. He is a B2B marketer with 8 years of experience in the logistics industry in the Netherlands. His work included business analysis of distribution and supply chain operations of high-tech companies in EMEA and APAC. He was responsible for directing, coordinating, planning and supervising transportation tasks and internal operations. He is currently responsible for marketing activities at QRmaint, a company that provides CMMS systems for various industries.

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Top 10 Challenges in Spare Parts Management