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.
Here's a quick visual aid on some of the key attributes of a successful demand planner.
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
Is demand management illusively complex? Here's a look at some best practices in demand management and characterization.
A demand-driven supply chain management process, no matter the industry, is built based on some fundamental principles. These principles are applied taking into consideration the requirements of the particular industry or company involved.
Here are some guidelines on selecting the right statistical forecasting methods for your business.
A Demand-driven Supply Chain (DDSC) is defined as a supply chain management method focused on building supply chains in response to demand signals. The main force of DDSC is that it is driven by customer demand. In comparison with the traditional supply chain, DDSC uses the pull (Demand pull) technique. It gives the market opportunities to share more information and to collaborate with others in the supply chain.