Instructor:

Cecil Bozarth , PhD
North Carolina State University
Author of "Introduction to Operations and Supply Chain Management," 2nd edition, Pearson, Prentice-Hall

 

SECTION Index

Introduction

Basic Rules of Forecasting

Time Series Models

   1. Exponential Smoothing

   2. Double Exponential Smoothing

Advanced Techniques

   1. Single Regression

   2. Multiple Regression

Qualitative Methods

Measuring Forecast Accuracy

Forecasting Strategies

   1. 3-Step Process

   2. Q2 Forecasting

Summary

References

 

 

Approaches to Forecasting : A Tutorial

Time Series Models

 

Time Series Models

Time Series Components of Demand...

Basic Idea Behind Time Series Models

Moving Average Models

Table of Forecasts & Demand Values...

... and Resulting Graph

 

What Are Time Series Models

• Quantitative forecasting models that use chronologically arranged data to develop forecasts.

• Assume that what happened in the past is a good starting point for predicting what will happen in the future.

• These models can be designed to account for:
• Randomness
• Trend
• Seasonality effects

• Advantages
• Can quickly be applied to a large number of products
• Forecast accuracy measures can be used to identify forecasts that need adjustment (management by exception

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Time Series Components of Demand...

Randomness

 

Randomness & trend

 

Randomness, trend & seasonality

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Basic Idea Behind Time Series Models

…Distinguish between random fluctuations & true changes in underlying demand patterns.

Simplicity is a virtue – Choose the simplest model that does the job

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Moving Average Models

• Based on last x periods

• Smoothes out random fluctuations

• Different weights can be applied to past observations, if desired

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Table of Forecasts & Demand Values...

 

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... and Resulting Graph

 

Note how the forecasts smooth out variations.

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