A New (and Smarter) Way to Forecast Leadtime Demand with Intermittent Data
Forecasting intermittent demand occurs in practice, when creating lead time demand forecasts for inventory planning. creating multiple forecasts of low volume items for a particular period in the future based […]Read more ›
EDA: How Data Analysis Becomes a Necessary First Step for Big Data and Predictive Analytics Modeling
When a multidisciplinary research study group at Princeton University undertook a study of the paired uses of electricity and gas in townhouses, it contacted the residents of Twin Rivers, a […]Read more ›
How You Can Improve Forecasting Performance with the MAPE by Finding and Fixing Data Quality Issues in Your Demand History
In a recent article entitled Improving Forecasting Performance with Intermittent Data – A New Way of Scoring Performance, I gave some insight into why the MAPE (Mean Absolute Percentage Error) […]Read more ›
When NOT to Use the Croston Method for Intermittent Demand Forecasting
In an earlier article on Forecasting with Intermittent Demand, a reader asked me whether my (Structured Inference Base) SIB approach for intermittent demand modeling was applicable to daily and weekly […]Read more ›
How to Measure Leadtime Demand Accuracy for Forecast Profiles – An Information-theoretic Approach
Demand forecasting and performance evaluation in today’s disrupted consumer demand-driven supply chain environment has become an extremely challenging discipline for business planners to master. For instance, current forecasting performance metrics for […]Read more ›
A New Way to Monitor Accuracy of Intermittent Lead-time Demand Forecasts: The Forecast Profile Performance (FPP) Index
Intermittency in demand forecasting is a well-known and challenging problem for sales, inventory and operations planners, especially in today’s global supply chain environment. Intermittent demand for a product or service […]Read more ›
Improving Forecasting Performance for intermittent data: A New Measurement Approach
With today’s disruptions in global supply chains as a result of the coronavirus pandemic, intermittent sales volumes, shipments and service parts inventory levels are becoming more common across many industries, […]Read more ›
How Demand Planners Can Become Smarter in Dealing with Intermittency in Demand Forecasting.
When economic disruptions in the global supply start creating shortages in inventory, demand planners are seeing more intermittent demand in sales and shipment data across the entire enterprise. Intermittent demand […]Read more ›
Are Your Safety Stock Levels Suited for Intermittent Data Lead-times?
As a follow-up to my previous article on smarter intermittent demand forecasting, I will now provide an algorithmic modeling approach for setting suitable safety stock levels without normality (Gaussian) assumptions. […]Read more ›
Forecasting with Intermittent Demand – A New Approach
Before making any modeling assumptions, we should first consider an application and examine the underlying historical data. The spreadsheet table shows the demand series for a SKU and location in […]Read more ›
Do You Need Something More Credible than the Croston Method for Forecasting Items with Intermittent Demand?
Data quality in forecast errors and other sources of unusual data values should never be ignored in demand forecast modeling and accuracy measurement, especially when forecasting intermittent demand. Intermittent demand or […]Read more ›