Monday, September 2, 2013

Some Thoughts About the Forecasting in SCM

This week’s topic is about product design and demand/supply forecasting. Personally I am more interested in analytics stuff so I decide to do some extra research on the forecasting in SCM.

A manufacture need to decide how many product they need to product, and the answer to this question decide how many raw material they need to purchase. A retailer need to decide how many product their customer demand and how many product they need to purchase from the manufacturer. Forecasting is associated with these important decisions.

Forecasting may play a different role for different type of company. For those companies who produce product with short production time and have a strong control on the raw material, they don’t greatly rely on their forecasting result. They could produce product right after they receive a order. As for those companies with a long production time, like automobile manufacturer, they may need accurate forecasting demand to help them set up a production plan in advance. 

Based on that, there are two kinds of inventory control system - push and pull. The push system of inventory control involves forecasting inventory needs to meet customer demand. The pull inventory control system begins with a customer's order. [1] If a company use a push system and have a poor forecast result, what they should do is either change the inventory control system to pull, or improve their forecasting. 

As we discuss in our first lecture, there are three flows associated with the supply chain management - product, fund, and information. One way to improve the their forecasting is to smoothen the information flow. 

There is a jargon in SCM called “bullwhip effect”. It means that as the information get passed along the supply chain, it get distorted and magnified. There are lots of stakeholders involved in the supply chain - end customers, retailers, distribution, manufacturer and raw material supplier. When they make the forecast on their own (with their own information), the bullwhip effect occurs and it serious affect the quality of the forecasting result. 

Supply chain vertical integration could serve as a method to reduce the bullwhip effect. In this week’s assigned reading, the P&G realize the bullwhip effect in the supply chain of its one of the most popular product - diaper, and it establish a system so that all the stakeholder involved share the same information in the supply chain. For example, the manufacturer and even the raw material supplier could know the exact sale volume day-by-day at the retailers so based on that, they could make better forecasting. 

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