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Forecasting Supply Chain Demand: Starbucks Corporation

Shool Project

Chad McKerlie

on 25 October 2016

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Transcript of Forecasting Supply Chain Demand: Starbucks Corporation

Forecasting Supply Chain Demand: Starbucks Corporation
Colwick, Kevin
Le, Thanh Ha
Makki, Amr
McKerlie, Chad
Patel, Niralee
Thapa, Aditi

Team 2
Starbucks logo branded coffee maker

It is distributed from five distribution centers in the US

They want to simplify the supply chain

New system is programmed to use one of two forecasting methods:
Simple Moving Average
Exponential Smoothing
Simple Moving Average
What is it?
Three Weeks and Five Weeks of Data

Evaluation Methods
Mean Absolute Deviation
Mean Absolute Percent Error
Tracking Signal

Simple Moving Average Results:
3-Week data is less biased
28% Error from Actual Demand

Three Weeks and Five Weeks of Data

No need to continually carry large amounts of historical data

Most used of all forecasting techniques

Exponential Smoothing Results:
.4 alpha-value is less biased
26.3 % Error from Actual Demand

Exponential Smoothing
Future Considerations
Exponential Smoothing is the Forecasting Method of Choice
Provides more accurate results
Easy to use and requires little computation

Starbucks should consolidate to a single distribution center
Uniform data
Lower maintenance cost
In Conclusion
Any Questions?
Full transcript