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The Operations Management Club organizes industry mixers, seminars, technical workshops, and conferences for students with an interest in Operations Management and Management Science. If you are interested in joining the OM Club, or are considering a major in Operations Management and have any questions about the degree, we would like to hear from you. For more information on the club, membership, and events, visit http://studentweb.bus.ualberta.ca/om/ or email [email protected] Meeting: Tuesday, January 16 at 5:00 PM, Bus 4-10 Announcements • HW 1 due Wednesday, 11:59 PM • OM Club Excel workshops – Jan 20, 11 AM – 1 PM – Free – Watch for a sign up link on the course page • Don’t have course pack yet? – Get one Friday in Lab MGTSC 352 Lecture 2: Forecasting Why forecast? Types of forecasts “Simple” time series forecasting methods Including SES = Simple Exponential Smoothing Performance measures Plant Site Selection • Alberta Manufacturer • Has one old plant, in Calgary • Planning to build new plant, but where? – Edmonton or Calgary? Recent Demand Figures Calgary Edmonton Fort McMurray Red Deer 2001 2002 2003 2004 2005 What Would you Do? Perspectives on Forecasting • Forecasting is difficult, especially if it's about the future! Niels Bohr • Rule #0: Every forecast is wrong! – Provide a range More sarcastic quotes about forecasting: http://www.met.rdg.ac.uk/cag/forecasting/quotes.html What is the Driver Doing? Forecasting • Technological forecasts – New product, product life cycle (Ipod, Blackberry) – Moore’s Law – Gates’ Law • Economic forecasts – Macro level (unemployment, inflation, markets, etc.) • Demand forecasts – Focus in MGTSC 352 Moore's Law: Computing power doubles about every two years. 1,000,000,000 100,000,000 Transistors 10,000,000 1,000,000 Gates’ Law: “The speed of software halves every 18 months.” 100,000 10,000 1,000 1965 1975 1985 Year 1995 2005 Data from ftp://download.intel.com/museum/Moores_Law/Printed_Materials/Moores_Law_Backgrounder.pdf Economic Forecasts An economist is an expert who will know tomorrow why the things he predicted yesterday didn't happen today. Evan Esar Why do economists make forecasts? “We forecast because people with money ask us to.” Kenneth Galbraith Forecasting – Quantitative • Time series analysis: uses only past records of demand to forecast future demand – moving averages – exponential smoothing – ARIMA • Causal methods: uses explanatory variables (timing of advertising campaigns, price changes) – multiple regression – econometric models Active learning • Groups of two • Recorder: person that is born closest to Telus 150. • Task: think of three quantities that you’d like to forecast • 1 minute Choosing a Forecasting Method START Is forecast important? Yes No Are accurate historical data available? No Yes Is forecast important? Yes No Is there at least 1-2 Flip a coin; months before use your intuition; forecast is needed? No look at your horoscope; consult an economist Yes Select appropriate qualitative method Are you willing to pay for greater accuracy? Yes No Use a causal Use time-series method method END Simple models • Notation – Dt = Actual demand in time period t – Ft = Forecast for period t – Et = Dt - Ft = Forecast error for period t • Problem: Forecast the TSX index 4 simple models Excel (Simple) Exponential Smoothing • Generalization of the WMA method • Uses a single parameter for weights 0 LS 1 • Three steps – Initialization ... F2 = D1 – Calibration ... Ft+1 = LS Dt + (1 - LS) Ft – Prediction ... same formula Note the formula is a weighted average of Demand and Forecast from last period Excel SES weights • Decrease “exponentially” as data age • Most recent data gets a weight of LS • Ft+1 = [LS Dt ] + [(1 - LS) Ft ] Rearrange... • Ft+1 = Ft + LS (Dt - Ft) = Ft + LS Et • A learning model How do we choose LS • Active learning (1 min.): – High LS (≈ 1) results in .... – Low LS (≈ 0) results in .... • Suggested range for LS: (0.01,0.3) • Performance measures (formulas in course pack, pg. 21) – – – – – BIAS MAD SE MSE MAPE Excel Famously Incorrect Forecasts • “I think there is a world market for maybe five computers.” Thomas Watson, chairman of IBM, 1943 • “There is no reason anyone would want a computer in their home.” Ken Olson, president, chairman and founder of Digital Equipment Corp., 1977 • “The concept is interesting and well-formed, but in order to earn better than a 'C,' the idea must be feasible.” A Yale University management professor in response to Fred Smith's paper proposing reliable overnight delivery service. (Smith went on to found Federal Express Corp.)