A fundamental aspect of supply chain management is accurate demand forecasting. Some product items have an intermittent demand pattern that makes them all but impossible to forecast with traditional, smoothing-based forecasting methods. We address the problem of forecasting intermittent demand (or irregular demand), i.e. random demand with a large proportion of zero values. This pattern is characteristic of demand for companies that manage large inventories of service and spare parts in industries such as aviation, aerospace, automotive, high tech, and electronics, as well as in MRO (Maintenance, Repair and Overhaul).
Accurate forecasting of demand is important in inventory control, but the intermittent nature of demand makes forecasting especially difficult for service parts planning. Similar problems arise when an organization manufactures slow-moving items and requires sales forecasts for planning purposes. Because forecasts of intermittent and lumpy demand have been so unreliable, most companies forecast inventory requirements relying primarily on subjective business knowledge, forecast only a fraction of their higher volume inventory, use simple “rule of thumb” estimates, or traditional statistical forecasting that incorrectly assumes a particular type demand distribution for inventory control.
Learn industry best practices on how to improve intermittent demand forecasting and create supply chain efficiencies in the articles below.
Top Differences Between Inventory Planning for Finished Goods and for MRO and Spare Parts
In today’s competitive business landscape, companies are constantly seeking ways to improve their operational efficiency and drive increased revenue. Optimizing service parts management is an often-overlooked aspect that can have a significant financial impact. Companies can improve overall efficiency and generate significant financial returns by effectively managing spare parts inventory. This article will explore the economic implications of optimized service parts management and how investing in Inventory Optimization and Demand Planning Software can provide a competitive advantage.
Centering Act: Spare Parts Timing, Pricing, and Reliability
In this article, we’ll walk you through the process of crafting a spare parts inventory plan that prioritizes availability metrics such as service levels and fill rates while ensuring cost efficiency. We’ll focus on an approach to inventory planning called Service Level-Driven Inventory Optimization. Next, we’ll discuss how to determine what parts you should include in your inventory and those that might not be necessary. Lastly, we’ll explore ways to enhance your service-level-driven inventory plan consistently.
5 Steps to Improve the Financial Impact of Spare Parts Planning
In today’s competitive business landscape, companies are constantly seeking ways to improve their operational efficiency and drive increased revenue. Optimizing service parts management is an often-overlooked aspect that can have a significant financial impact. Companies can improve overall efficiency and generate significant financial returns by effectively managing spare parts inventory. This article will explore the economic implications of optimized service parts management and how investing in Inventory Optimization and Demand Planning Software can provide a competitive advantage.
Bottom Line Strategies for Spare Parts Planning
Managing spare parts presents numerous challenges, such as unexpected breakdowns, changing schedules, and inconsistent demand patterns. Traditional forecasting methods and manual approaches are ineffective in dealing with these complexities. To overcome these challenges, this blog outlines key strategies that prioritize service levels, utilize probabilistic methods to calculate reorder points, regularly adjust stocking policies, and implement a dedicated planning process to avoid excessive inventory. Explore these strategies to optimize spare parts inventory and improve operational efficiency.
Prepare your spare parts planning for unexpected shocks
In today’s unpredictable business climate, we do have to worry about supply chain disruptions, long lead times, rising interest rates, and volatile demand. With all these challenges, it’s never been more vital for organizations to accurately forecast parts usage, stocking levels, and to optimize replenishment policies such as reorder points, safety stocks, and order quantities. In this blog, we’ll explore how companies can leverage innovative solutions like inventory optimization and parts forecasting software that utilize machine learning algorithms, probabilistic forecasting, and analytics to stay ahead of the curve and protect their supply chains from unexpected shocks.
Why Spare Parts Tradeoff Curves are Mission-Critical for Parts Planning
When managing service parts, you don’t know what will break and when because part failures are random and sudden. As a result, demand patterns are most often extremely intermittent and lack significant trend or seasonal structure. The number of part-by-location combinations is often in the hundreds of thousands, so it’s not feasible to manually review demand for individual parts. Nevertheless, it is much more straightforward to implement a planning and forecasting system to support spare parts planning than you might think.
Recent Posts
Why Inventory Planning Shouldn’t Rely Exclusively on Simple Rules of ThumbFor too many companies, a critical piece of data fact-finding ― the measurement of demand uncertainty ― is handled by simple but inaccurate rules of thumb. For example, demand planners will often compute safety stock by a user-defined multiple of the forecast or historical average. Or they may configure their ERP to order more when on hand inventory gets to 2 x the average demand over the lead time for important items and 1.5 x for less important ones. This is a huge mistake with costly consequences. […]
Direct to the Brain of the Boss – Inventory Analytics and ReportingIn this blog, the spotlight is cast on the software that creates reports for management, the silent hero that translates the beauty of furious calculations into actionable reports. Watch as the calculations, intricately guided by planners utilizing our software, seamlessly converge into Smart Operational Analytics (SOA) reports, dividing five key areas: inventory analysis, inventory performance, inventory trending, supplier performance, and demand anomalies. […]
You Need to Team up with the AlgorithmsThis article is about the real power that comes from the collaboration between you and our software that happens at your fingertips. We often write about the software itself and what goes on “under the hood”. This time, the subject is how you should best team up with the software. […]
Rethinking forecast accuracy: A shift from accuracy to error metricsMeasuring the accuracy of forecasts is an undeniably important part of the demand planning process. This forecasting scorecard could be built based on one of two contrasting viewpoints for computing metrics. The error viewpoint asks, “how far was the forecast from the actual?” The accuracy viewpoint asks, “how close was the forecast to the actual?” Both are valid, but error metrics provide more information. […]
Using Key Performance Predictions to Plan Stocking PoliciesI can't imagine being an inventory planner in spare parts, distribution, or manufacturing and having to create safety stock levels, reorder points, and order suggestions without using key performance predictions of service levels, fill rates, and inventory costs. […]
Inventory Optimization for Manufacturers, Distributors, and MRO
Top Differences Between Inventory Planning for Finished Goods and for MRO and Spare PartsIn today’s competitive business landscape, companies are constantly seeking ways to improve their operational efficiency and drive increased revenue. Optimizing service parts management is an often-overlooked aspect that can have a significant financial impact. Companies can improve overall efficiency and generate significant financial returns by effectively managing spare parts inventory. This article will explore the economic implications of optimized service parts management and how investing in Inventory Optimization and Demand Planning Software can provide a competitive advantage. […]
Centering Act: Spare Parts Timing, Pricing, and ReliabilityIn this article, we'll walk you through the process of crafting a spare parts inventory plan that prioritizes availability metrics such as service levels and fill rates while ensuring cost efficiency. We'll focus on an approach to inventory planning called Service Level-Driven Inventory Optimization. Next, we'll discuss how to determine what parts you should include in your inventory and those that might not be necessary. Lastly, we'll explore ways to enhance your service-level-driven inventory plan consistently. […]
5 Steps to Improve the Financial Impact of Spare Parts PlanningIn today’s competitive business landscape, companies are constantly seeking ways to improve their operational efficiency and drive increased revenue. Optimizing service parts management is an often-overlooked aspect that can have a significant financial impact. Companies can improve overall efficiency and generate significant financial returns by effectively managing spare parts inventory. This article will explore the economic implications of optimized service parts management and how investing in Inventory Optimization and Demand Planning Software can provide a competitive advantage. […]
Bottom Line Strategies for Spare Parts PlanningManaging spare parts presents numerous challenges, such as unexpected breakdowns, changing schedules, and inconsistent demand patterns. Traditional forecasting methods and manual approaches are ineffective in dealing with these complexities. To overcome these challenges, this blog outlines key strategies that prioritize service levels, utilize probabilistic methods to calculate reorder points, regularly adjust stocking policies, and implement a dedicated planning process to avoid excessive inventory. Explore these strategies to optimize spare parts inventory and improve operational efficiency. […]
The Problem
Some product items have an intermittent demand pattern that makes them all but impossible to forecast with traditional, smoothing-based forecasting methods. Items with intermittent demand – also known as lumpy, volatile, variable or unpredictable demand – have many zero or low volume values interspersed with random spikes of demand that are often many times larger than the average. This problem is especially prevalent in companies that manage large inventories of service and spare parts in industries such as aviation, aerospace, automotive, high tech, and electronics, as well as in MRO (Maintenance, Repair and Overhaul).
Intermittent demand
In these businesses, as much as 80% of the parts and product items may have intermittent or lumpy demand. Intermittent demand makes it difficult to accurately estimate the safety stock and service level inventory requirements needed for successful supply chain planning. Because forecasts of intermittent and lumpy demand have been so unreliable, most companies forecast inventory requirements relying primarily on subjective business knowledge, forecast only a fraction of their higher volume inventory, use simple “rule of thumb” estimates, or traditional statistical forecasting that incorrectly assumes a particular type demand distribution for inventory control. The result is that billions of dollars are wasted every year because of either excess inventory costs or poor customer service due to stock-outs.
Intermittent demand – also known as lumpy, volatile, variable or unpredictable demand.
The Smart Solution
SmartForecasts and Smart Inventory Optimization use a unique empirical probabilistic forecasting approach that results in accurate forecasts of inventory requirements where demand is intermittent. The solution works particularly well whenever demand does not conform to a simple normal distribution. Our patented, APICS award-winning “bootstrapping” technology rapidly generates tens of thousands of possible scenarios of future demand sequences and cumulative demand values over an item’s lead time. These scenarios are statistically similar to the item’s observed data, and they capture the relevant details of intermittent demand without relying on the assumptions commonly made about the nature of demand distributions by traditional forecasting methods. The result is a highly accurate forecast of the entire distribution of cumulative demand over an item’s full lead time. With the information these demand distributions provide, you can easily plan your company’s safety stock and service level inventory requirements for thousands of intermittently demanded items with nearly 100% accuracy.
The Benefits
Companies using our powerful intermittent demand forecasting and planning solution typically reduce standing inventory by 20% in the first year, increase parts availability 10-20%, and reduce the need for and associated costs of emergency transshipment to close gaps in their supply chain. Repair and service parts inventories are truly optimized, leading to more efficient operations, improvements in customer service, and significantly less cash tied up in inventory.
White Paper: Smart Software Gen2
In this white paper, we introduce “Gen2”, our next generation of probabilistic modeling technology that powers the Smart IP&O Platform. We recount the evolution of Smart Software’s forecasting methods and we detail how Gen2 substantially expands the capabilities that have made Gen1 so useful to so many companies. Finally, we will also give a high-level view of the probability math behind Gen2 . Fill in this form and we'll email you the paper.