4 Planning Strategies Under NetSuite Demand Planning For Increasing Productivity

Manufacturing and wholesale businesses are heavily dependent on one factor: Demand.

Every aspect of these businesses, right from production to supply chain, procurement of raw materials to inventory management, shipping and after-sale service is dependent heavily on the demand aspect.

What if manufacturers, wholesalers and other businesses are able to know which products will be in demand, and accordingly plan their moves?

What if an ERP platform understands their business so well, that it can actually predict the demand in advance, and this can enable them to carve out their plans, in accordance with the supply?

No wastage of inventory, optimal production, and timely delivery of all products will be the outcome.

No, it isn’t any fiction anymore, because of NetSuite Demand Planning.

NetSuite Demand Planning: The Module Which Predicts The Actual Demand

Based on years of experience of managing businesses all across the world, especially manufacturing and wholesale, NetSuite has created a robust module called Demand Planning.

Based on the inventory data, and sales history of any company or product, NetSuite Demand Planning can predict the required inventory, which gives a huge advantage to manufacturers and distributors.

Demand Planning module from NetSuite empowers the organizations to acquire the right products, at the right time, in the right place. And this single aspect can ensure higher revenues, higher profits, and maximum ROI.

4 Planning Models Under NetSuite Demand Planning

There are not one but four planning methods incorporated within NetSuite Demand Planning module, which helps businesses to plan their next moves, based on sales forecast, historical sales data, inventory position and more.

These 4 planning models are:

Linear Regression Model

In this planning model, the businesses are able to project and forecast future inventory needs and requirements, based on the previous demand metrics using the ordinary least-square regression method. This is a statistical model, which estimates the unknown parameters based on Linear regression.

Moving Average Model

In this planning model, organizations can calculate the overall average inventory level required for a product, based on the moving average of historical demand. All future stock levels are then projected, using the overall average.

This is a dynamic planning model, especially relevant for fast-moving consumer products.

Seasonal Average Model

In this planning model, businesses can predict the future demand for a product using seasonal trends, and historical data related with it. Based on the predictions, manufacturers and wholesalers, and retailers can stock up their seasonal products, and ensure seamless distribution and sales.

This model is especially relevant for products that are in high demand during holidays or particular seasons like raincoat or umbrella during monsoon or woolen clothes, blazers during winters. Such prediction models can be potential game-changers.

Sales Forecast Model

Under this model, businesses can stock up inventories based on the forward-looking sales forecast data. Examples of such sales forecast data can include opportunities, estimates and more.

This is again a dynamic demand planning model, beneficial for sales operations of an organization, and can prove to be that extra edge required to beat your competitors.

To know more about NetSuite Demand Planning, and how it can transform your business, contact Inspirria right now.

Friday, April 10, 2020

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