Basically, the method uses samples of historical demand data to create thousands of realistic scenarios that show the evolution of cumulative demand over a lead time.
Forecast intermittent demand
Recent Posts
Prepare your spare parts planning for unexpected s…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. […]
Uncover data facts and improve inventory performan…The best inventory planning processes rely on statistical analysis to uncover relevant facts about the data. When you have the facts and add your business knowledge, you can make more informed stocking decisions that will generate significant returns. You'll also set proper expectations with internal and external stakeholders, ensuring there are fewer unwelcome surprises. […]
Electric Utilities’ Problems with Spare PartsEvery organization that runs equipment needs spare parts. All of them must cope with issues that are generic no matter what their business. Some of the problems, however, are industry specific. This post discusses one universal problem that manifested in a nuclear plant and one that is especially acute for any electric utility. […]
Smart Posts
- Uncover data facts and improve inventory performan…Blog, Inventory control, Inventory OptimizationThe best inventory planning processes rely on statistical analysis to uncover relevant facts about the data. When you have the facts and add your business knowledge, you can make more informed stocking decisions that will generate significant returns. You'll also set proper expectations with internal and external stakeholders, ensuring there are fewer unwelcome surprises. […]
What Silicon Valley Bank Can Learn from Supply Cha…Blog, Excellence in Forecasting, Inventory Optimization, Operational AnalyticsIf you had your head up lately, you may have noticed some additional madness off the basketball court: The failure of Silicon Valley Bank. Those of us in the supply chain world may have dismissed the bank failure as somebody else’s problem, but that sorry episode holds a big lesson for us, too: The importance of stress testing done right. […]
Why Days of Supply Targets Don’t Work when Computi…Blog, Inventory OptimizationCFOs tell us they need to spend less on inventory without impacting sales. One way to do that is to move away from using targeted day of supply rules to determine reorder points and safety stock buffers. Here is how a target days of supply/coverage approach works: […]