Chapter 8 Supplement Forecasting.

Slides:

Advertisements

Similar presentations

Forecasting OPS 370.

Advertisements

Operations Management Forecasting Chapter 4

Bina Nusantara Model Ramalan Peretemuan 13: Mata kuliah: K0194-Pemodelan Matematika Terapan Tahun: 2008.

What is Forecasting? A forecast is an estimate of what is likely to happen in the future. Forecasts are concerned with determining what the future will.

Forecasting 5 June Introduction What: Forecasting Techniques Where: Determine Trends Why: Make better decisions.

Qualitative Forecasting Methods

Forecasting Ross L. Fink.

Data Sources The most sophisticated forecasting model will fail if it is applied to unreliable data Data should be reliable and accurate Data should be.

CHAPTER 3 Forecasting.

Chapter 3 Forecasting McGraw-Hill/Irwin

To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ PERTEMUAN 14.

Chapter 13 Forecasting.

Operations Management Forecasting Chapter 4

© 2004 by Prentice Hall, Inc., Upper Saddle River, N.J Operations Management Forecasting Chapter 4.

Copyright 2006 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Forecasting Operations Chapter 12 Roberta Russell & Bernard.

Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

Copyright 2013 John Wiley & Sons, Inc. Chapter 8 Supplement Forecasting.

Demand Forecasts The three principles of all forecasting techniques: –Forecasting is always wrong –Every forecast should include an estimate of error –The.

Demand Forecasting By Prof. Jharna Lulla.

LSS Black Belt Training Forecasting. Forecasting Models Forecasting Techniques Qualitative Models Delphi Method Jury of Executive Opinion Sales Force.

Chapter 4 Forecasting Mike Dohan BUSI Forecasting What is forecasting? Why is it important? In what areas can forecasting be applied?

Chapter 15 Demand Management & Forecasting

Forecasting Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill.

Chapter 5 Demand Forecasting. Qualitative Forecasts Survey Techniques Planned Plant and Equipment Spending Expected Sales and Inventory Changes Consumers’

Chapter 2 – Business Forecasting Takesh Luckho. What is Business Forecasting?  Forecasting is about predicting the future as accurately as possible,

Business Forecasting Used to try to predict the future Uses two main methods: Qualitative – seeking opinions on which to base decision making – Consumer.

Forecasting OPS 370.

Forecasting supply chain requirements

Forecasting Professor Ahmadi.

Operations Management For Competitive Advantage 1Forecasting Operations Management For Competitive Advantage Chapter 11.

MBA.782.ForecastingCAJ Demand Management Qualitative Methods of Forecasting Quantitative Methods of Forecasting Causal Relationship Forecasting Focus.

Introduction to Forecasting IDS 605 Spring Forecasting 4 A forecast is an estimate of future demand.

Forecasting February 26, Laws of Forecasting Three Laws of Forecasting –Forecasts are always wrong! –Detailed forecasts are worse than aggregate.

Time-Series Forecasting Overview Moving Averages Exponential Smoothing Seasonality.

Demand Management and Forecasting Module IV. Two Approaches in Demand Management Active approach to influence demand Passive approach to respond to changing.

Operations Fall 2015 Bruce Duggan Providence University College.

1 1 Slide Forecasting Professor Ahmadi. 2 2 Slide Learning Objectives n Understand when to use various types of forecasting models and the time horizon.

Forecasting. 預測 (Forecasting) A Basis of Forecasting In business, forecasts are the basis for budgeting and planning for capacity, sales, production and.

Forecasting Chapter 9. Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall Define Forecast.

1 Chapter 13 Forecasting  Demand Management  Qualitative Forecasting Methods  Simple & Weighted Moving Average Forecasts  Exponential Smoothing  Simple.

Business Processes Sales Order Management Aggregate Planning Master Scheduling Production Activity Control Quality Control Distribution Mngt. © 2001 Victor.

Welcome to MM305 Unit 5 Seminar Prof Greg Forecasting.

FORECASTING Kusdhianto Setiawan Gadjah Mada University.

Forecasting Demand. Forecasting Methods Qualitative – Judgmental, Executive Opinion - Internal Opinions - Delphi Method - Surveys Quantitative - Causal,

DEPARTMENT OF MECHANICAL ENGINEERING VII-SEMESTER PRODUCTION TECHNOLOGY-II 1 CHAPTER NO.4 FORECASTING.

Forecasting is the art and science of predicting future events.

Chapter 7 Demand Forecasting in a Supply Chain

CHAPTER 12 FORECASTING. THE CONCEPTS A prediction of future events used for planning purpose Supply chain success, resources planning, scheduling, capacity.

3-1Forecasting CHAPTER 3 Forecasting McGraw-Hill/Irwin Operations Management, Eighth Edition, by William J. Stevenson Copyright © 2005 by The McGraw-Hill.

Forecasting Demand. Problems with Forecasts Forecasts are Usually Wrong. Every Forecast Should Include an Estimate of Error. Forecasts are More Accurate.

Demand Management and Forecasting Chapter 11 Portions Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin.

Chapter 11 – With Woodruff Modications Demand Management and Forecasting Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin.

Predicting Future. Two Approaches to Predition n Extrapolation: Use past experiences for predicting future. One looks for patterns over time. n Predictive.

Welcome to MM305 Unit 5 Seminar Dr. Bob Forecasting.

Welcome to MM305 Unit 5 Seminar Forecasting. What is forecasting? An attempt to predict the future using data. Generally an 8-step process 1.Why are you.

Forecasting Chapter 9.

Operations Management Contemporary Concepts and Cases

OPERATIONS MANAGEMENT for MBAs Fourth Edition

RAJEEV GANDHI COLLEGE OF MANAGEMENT STUDIES

Demand Management and Forecasting

Forecasting Chapter 11.

“The Art of Forecasting”

FORCASTING AND DEMAND PLANNING

Principles of Supply Chain Management: A Balanced Approach

Forecasting Elements of good forecast Accurate Timely Reliable

Forecasting is an Integral Part of Business Planning

BEC 30325: MANAGERIAL ECONOMICS

Demand Management and Forecasting

Presentation transcript:

Chapter 8 Supplement Forecasting

Forecasting Purposes and Methods Must forecast future to plan An accurate estimate of demand is crucial to the efficient operation of a system Not only demand can be forecasted New technology Economic conditions Changes in lead time, scrap rates, and so on

Primary Uses of Forecasting To determine if sufficient demand exists To determine long-term capacity needs To determine midterm fluctuations in demand to avoid short-sighted decisions To determine short-term fluctuations in demand for production planning, workforce scheduling, and materials planning

Forecasting Methods Figure 8S.1

Qualitative Methods Life cycle Surveys Delphi Historical analogy Expert opinion Consumer panels Test marketing

Quantitative Methods Causal Time series analysis Input-output Econometric Box-Jenkins Time series analysis Simple regression Exponential smoothing Moving average

Choosing a Forecasting Method Availability of representative data Time and money limitations Accuracy needed

Time Series Analysis Time series is a set of values measured either at regular points in time or over sequential intervals of time Can be collected over short or long periods of time

Components of Time Series Trend T Seasonal variation S Cyclical variation C Random variation R

Common Trend Patterns Figure 8S.2a

Common Trend Patterns Figure 8S.2b

Common Trend Patterns Figure 8S.2c

Moving Averages

Four-Period Moving Average of Intel’s Monthly Stock Closing Price Figure 8S.3

Exponential Smoothing

Using Exponential Smoothing To Forecast Intel’s Closing Stock Price Figure 8S.4

Simple Regression: The Linear Trend Multiplicative Model Y = α + βX + ε Where: X = Independent variable Y = Dependent variable α and β are the parameter of the model

Fitting Regression Line to Data Figure 8S.5

Example Relationships Between Variables Figure 8S.8

Least Squares Approach to Fitting Line to a Set of Data Figure 8S.9

Regression Analysis Assumptions The residuals are normally distributed The expected value of the residuals is zero The residuals are independent of one another The variance of the residuals is constant

The Multiple Regression Model Simple regression uses one independent variable Using more than one independent variable is called multiple regression Form of the model is:

Developing Regression Models Identify candidate independent variables to include in the model Transform the data Select the variables to include in the model Analyze the residuals