Operations Management Chapter – Forecasting PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 7e Operations Management, 9e © 2008 Prentice Hall, Inc 4–1 Outline Global Company Profile: Disney World What Is Forecasting? Forecasting Time Horizons The Influence of Product Life Cycle Types Of Forecasts © 2008 Prentice Hall, Inc 4–2 Outline – Continued The Strategic Importance of Forecasting Human Resources Capacity Supply Chain Management Seven Steps in the Forecasting System © 2008 Prentice Hall, Inc 4–3 Outline – Continued Forecasting Approaches Overview of Qualitative Methods Overview of Quantitative Methods © 2008 Prentice Hall, Inc 4–4 Outline – Continued Time-Series Forecasting Decomposition of a Time Series Naive Approach Moving Averages Exponential Smoothing Exponential Smoothing with Trend Adjustment Trend Projections Seasonal Variations in Data Cyclical Variations in Data © 2008 Prentice Hall, Inc 4–5 Outline – Continued Associative Forecasting Methods: Regression and Correlation Analysis Using Regression Analysis for Forecasting Standard Error of the Estimate Correlation Coefficients for Regression Lines Multiple-Regression Analysis © 2008 Prentice Hall, Inc 4–6 Outline – Continued Monitoring and Controlling Forecasts Adaptive Smoothing Focus Forecasting Forecasting In The Service Sector © 2008 Prentice Hall, Inc 4–7 Learning Objectives When you complete this chapter you should be able to : Understand the three time horizons and which models apply for each use Explain when to use each of the four qualitative models Apply the naive, moving average, exponential smoothing, and trend methods © 2008 Prentice Hall, Inc 4–8 Learning Objectives When you complete this chapter you should be able to : Compute three measures of forecast accuracy Develop seasonal indexes Conduct a regression and correlation analysis Use a tracking signal © 2008 Prentice Hall, Inc 4–9 Forecasting at Disney World Global portfolio includes parks in Hong Kong, Paris, Tokyo, Orlando, and Anaheim Revenues are derived from people – how many visitors and how they spend their money Daily management report contains only the forecast and actual attendance at each park © 2008 Prentice Hall, Inc – 10 Correlation Coefficient r= © 2008 Prentice Hall, Inc nΣ xy - Σ xΣ y [nΣ x2 - (Σ x)2][nΣ y2 - (Σ y)2] – 100 Correlation Coefficient y y nΣ xy - Σ xΣ y r= 2 2 [ n Σ x ( Σ x ) ][ n Σ y ( Σ y ) x (a) Perfect positive (b) Positive ] correlation: r = +1 x correlation: 0