Selecting the right forecasting methods can be highly critical in how accurate your forecasts are. Unfortunately, there isn’t a golden ticket to forecasting which can essentially ensure accuracy. While the best-fit forecasting method is dependent on a business’ specific situation, understanding the types of forecasting methods can aid in your decision-making.
How to determine when to use a best-fit analysis and when to use prediction techniques for demand forecasting analysis.
Demand forecasting forms an essential component of the supply chain process. It’s the driver for almost all supply chain related decisions. While demand forecasting is undeniably important, it’s also one of the most difficult aspects of supply chain planning.
How to use demand planning statistical models to enhance the value of your sales input during the forecasting process.
Demand Planning directly affects the business financial plan, pricing, capex decisions, customer segmentation and resource allocation. Considering the criticality and implication of this process, Demand Planners and Managers need to continually evaluate their current Demand Planning process and ensure that the Demand Plan generated is holistic, relevant and timely.
What is Demand Forecasting? Demand Forecasting is the process in which the historical sales data is used to develop an estimate of expected forecast of customer demand.
How global businesses can build a collaborative demand planning process
Here are some guidelines on selecting the right statistical forecasting methods for your business.
During the last storm, I was watching the snow plows go to work and thinking about the amount of planning that must go into the resources needed to deal with the snow - what with salt, and plows needed. That must be a whole supply chain.
Should you factor returns in your forecast error calculation? In this article, we’ll use a sample data set, to demonstrate if you should consider returns when calculating your forecast errors.