Lecture Operations and supply chain management: The Core (3/e) – Chapter 3: Forecasting

The main goals of this chapter are to: Understand the role of forecasting as a basis for supply chain planning; identify the basic components of demand: average, trend, seasonal, and random variation; show how to make a time series forecast using moving averages, exponential smoothing, and regression;...

Forecasting Chapter 03 McGraw­Hill/Irwin         Copyright © 2013 by The McGraw­Hill Companies, Inc. All rights reserved Learning Objectives Understand the role of forecasting as a basis for supply chain planning Identify the basic components of demand: average, trend, seasonal, and random variation Show how to make a time series forecast using moving averages, exponential smoothing, and regression Use decomposition to forecast when trend and seasonality is present Show how to measure forecast error Describe the common qualitative forecasting techniques, such as the Delphi method and collaborative forecasting 3­2 The Role of Forecasting  Forecasting is a vital function and impacts every significant management decision     Finance and accounting use forecasts as the basis for budgeting and cost control Marketing relies on forecasts to make key decisions such as new product planning and personnel compensation Production uses forecasts to select suppliers, determine capacity requirements, and to drive decisions about purchasing, staffing, and inventory Different roles require different forecasting approaches   Decisions about overall directions require strategic forecasts Tactical forecasts are used to guide day-to-day decisions 3­3 Components of Demand Excel: Components 3­4 Time Series Analysis  Using the past to predict the future 3­5 Forecasting Method Selection Guide Fo re c as ting  Me tho d Amo unt o f His to ric al  Data Data Patte rn Fo re c as t  Ho rizo n Simple moving average to 12 months; weekly data are often used Stationary (i.e no trend or seasonality) Short Weighted moving to 10 observations average and simple needed to start exponential smoothing Stationary Short Exponential smoothing to 10 observations with trend needed to start Stationary and trend Short Linear regression Stationary, trend, and seasonality Short to Medium 10 to 20 observations 3­6 Forecast Error Measurements   Ideally, MAD will be zero (no forecasting error) Larger values of MAD indicate a less accurate model   MAPE scales the forecast error to the magnitude of demand Tracking signal indicates whether forecast errors are accumulating over time (either positive or negative errors) 3­7 Computing Forecast Error 3­8 Causal Relationship Forecasting  Causal relationship forecasting uses independent variables other than time to predict future demand   This independent variable must be a leading indicator Many apparently causal relationships are actually just correlated events – care must be taken when selecting causal variables 3­9 Multiple Regression Techniques   Often, more than one independent variable may be a valid predictor of future demand In this case, the forecast analyst may utilize multiple regression   Analogous to linear regression analysis, but with multiple independent variables Multiple regression is supported by statistical software packages 3­10 Qualitative Forecasting Techniques    Generally used to take advantage of expert knowledge Useful when judgment is required, when products are new, or if the firm has little experience in a new market Examples     Market research Panel consensus Historical analogy Delphi method 3­11 Collaborative Planning, Forecasting, and Replenishment (CPFR)  A web-based process used to coordinate the efforts of a supply chain      Demand forecasting Production and purchasing Inventory replenishment Integrates all members of a supply chain – manufacturers, distributors, and retailers Depends upon the exchange of internal information to provide a more reliable view of demand 3­12 CPFR Steps 3­13 Principles     Forecasting is a fundamental step in any planning process Forecast effort should be proportional to the magnitude of decisions being made Web-based systems (CPFR) are growing in importance and effectiveness All forecasts have errors – understanding and minimizing this error is the key to effective forecasting processes 3­14 ...Learning Objectives Understand the role of forecasting as a basis for supply chain planning Identify the basic components of demand: average, trend, seasonal, and random variation Show how to... and collaborative forecasting 3­2 The Role of Forecasting  Forecasting is a vital function and impacts every significant management decision     Finance and accounting use forecasts as the. .. Collaborative Planning, Forecasting, and Replenishment (CPFR)  A web-based process used to coordinate the efforts of a supply chain      Demand forecasting Production and purchasing Inventory