One of my favorite Holiday songs growing up was “The 12 Days of Christmas.” There was something about Christmas having 12 days that put me in the holiday spirit.
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.
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.
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.
We are thrilled about presenting a session with Arkieva customer — Lush Handmade Cosmetics. The session that focuses on how Lush delivers a unique brand experience also discusses how effective demand planning solutions help with creating that experience. Last year we created the 2017 Gartner Supply Chain Conference list of Must-Attend Sessions. To continue along that tradition, here is the list of Must-Attend sessions at the Gartner Supply Chain Conference this year.
A digital supply chain is a supply chain network (DSN) that focuses on using digital systems or technology tools to reduce the need for disparate systems through connectivity; eliminating manual processes and leveraging the data that is available through these systems to enhance the entire supply chain network.
In a recent study, Gartner estimates that 50% of Supply Chain Planning Solutions are not fully utilized1. How can organizations ensure that they have the user adoption needed to attain the full benefits from their existing or new supply chain solution?
An open order is defined as an order placed by the customer which is under process and is yet to be fulfilled by the supplier. For effective analysis, open order data needs to be recorded daily in an ERP system. A minimum of twelve to eighteen months of open order history is required for your sales forecasting analysis and fine-tuning process. A shorter period could render unreliable and skew the results of your data analysis.
In an ideal world, demand and supply would be steady and predictable, resulting in optimal capacity utilization and no back orders or missed customer orders. However, in the actual supply chain world variations in actual sales vs. projected sales result in lower forecast accuracy, and either overstocking or stock out situations.