Chapter 4 Forecasting Mike Dohan BUSI 2016. Forecasting What is forecasting? Why is it important? In what areas can forecasting be applied?

Slides:

Advertisements

Similar presentations

Forecasting OPS 370.

Advertisements

© 1997 Prentice-Hall, Inc. S2 - 1 Principles of Operations Management Forecasting Chapter S2.

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.

Forecasting Ross L. Fink.

CHAPTER 3 Forecasting.

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.

Principles of Supply Chain Management: A Balanced Approach

Operations Management R. Dan Reid & Nada R. Sanders

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.

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

FORECASTING Operations Management Dr. Ron Lembke.

Mr. David P. Blain. C.Q.E. Management Department UNLV

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

Slides 13b: Time-Series Models; Measuring Forecast Error

Chapter 5 DEMAND FORECASTING Prepared by Mark A. Jacobs, PhD

Winter’s Exponential smoothing

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

Operations and Supply Chain Management

Sales Management Sales Forecasting Topic 13. Sales Forecasting What is it? Why do it? Qualitative vs Quantitative Goal = Accuracy Commonly Done by Marketing.

The Importance of Forecasting in POM

CHAPTER 3 FORECASTING.

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

Forecasting OPS 370.

3-1 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved.

Forecasting supply chain requirements

Forecasting Professor Ahmadi.

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

Time-Series Forecasting Overview Moving Averages Exponential Smoothing Seasonality.

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.

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.

McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 3 Forecasting.

OM3-1 McGraw-Hill/Irwin Operations Management, Seventh Edition, by William J. Stevenson Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights.

FORECASTING Kusdhianto Setiawan Gadjah Mada University.

Chapter 5 Forecasting. Eight Steps to Forecasting 1. Determine the use of the forecast—what objective are we trying to obtain? 2. Select the items or.

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

MGS3100_03.ppt/Feb 11, 2016/Page 1 Georgia State University - Confidential MGS 3100 Business Analysis Time Series Forecasting Feb 11, 2016.

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

Chapter 12 Forecasting. Lecture Outline Strategic Role of Forecasting in SCM Components of Forecasting Demand Time Series Methods Forecast Accuracy Regression.

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.

3-1Forecasting William J. Stevenson Operations Management 8 th edition.

13 – 1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. Forecasting 13 For Operations Management, 9e by Krajewski/Ritzman/Malhotra.

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Chapter 8 Forecasting To Accompany.

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

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

Demand Forecasting Production and Operations Management Judit Uzonyi-Kecskés Ph.D. Student Department of Management and Corporate Economics Budapest University.

Forecasting. ©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 9, Slide 2 Why Forecast?

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

Demand Forecasting Production and Operations Management Judit Uzonyi-Kecskés Ph.D. Student Department of Management and Corporate Economics Budapest University.

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.

Operations Management Contemporary Concepts and Cases

RAJEEV GANDHI COLLEGE OF MANAGEMENT STUDIES

Forecasting Chapter 11.

Module 2: Demand Forecasting 2.

Forecasting Elements of good forecast Accurate Timely Reliable

Forecasting is an Integral Part of Business Planning

Chapter 8 Supplement Forecasting.

Presentation transcript:

Chapter 4 Forecasting Mike Dohan BUSI 2016

Forecasting What is forecasting? Why is it important? In what areas can forecasting be applied?

Forecasting What is forecasting? “art and science of predicting future events” Why is it important? allows for planning of future events, within a defined time horizon What should a good forecast be? ACCURATE Timely, interpretable, ability to detect trends In what areas can forecasting be applied? SCM – demand quantity from suppliers HR – labour demand for scheduling and planning Capacity – how many units to meet customer demand

Seven Steps 1.Determine the use of the forecast 2.Select items to be forecasted 3.Determine time horizon 4.Select forecasting model 5.Gather the data needed to make the forecast 6.Make the forecast 7.Validate and implement the results

Qualitative Approaches Jury of experts Delphi method Sales force composite Market survey

Quantitative Approach Time Series Models – “the future is a function of the past” Naïve Approach Moving Averages Exponential Smoothing Trend projection Associative Models – “what other numbers are related to demand” Linear Regression

Time Series Forecasting Future values predicted based on past values Four Components: Trend, Seasonality, Cycles, Random Variations

Naïve Approach Demand of next period is equal to last period Example Demand in January was 87 Therefore demand in February will be 87

Moving Averages

Weighted Moving Averages

Exponential Smoothing

Trends and “Lag”

Measuring Forecast Error of Time Series Models

Exponential Smoothing w Trend Adjustment

Trend Projection Find equation for trend line, use that for prediction Figure 4.4 Assumes linear relationship * * * * * * *

Variations in Data Seasonal Ie Swimming trunks sell more in the summer than in the winter Forecasting can incorporate a “Seasonal Index” SI = 3 year historical ave. demand for the month (ie all Januaries) / average monthly demand Forecast = (yearly demand / number of months) * SI More accuracy can be achieved by incorporating Seasonality and Trend to the forecast..

Associative Forecasting Methods

Correlation Coefficient r = -1 r = -0.5 r = 1 r = 0.5 r = 1

Multiple Regression

Monitoring and Controlling Forecasts Tracking Signal: used to make sure forecasts are acceptably accurate

Business Intelligence - the use of existing data in new ways is a popular area in industry and research Also: