Chapter_9_-_Forecasting

Chapter_9_-_Forecasting - BUS 370: Forecasting Chapter 9...

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BUS 370: Forecasting Chapter 9 Tracy Freeman Poole College of Management North Carolina State University 1
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Chapter Objectives Be able to: Discuss the importance of forecasting and identify the most appropriate type of forecasting approach, given different forecasting situations. Apply a variety of time series forecasting models, including moving average, exponential smoothing, and linear regression models. Develop causal forecasting models using linear regression and multiple regression. Calculate measures of forecasting accuracy and interpret the results. 2
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Cheeznax Snack Foods Three Products: Puffed Cheese Balls, Cheese Nachos, Cheese Flavored Potato Chips Assignment – 2011 Forecast of 2011 Demand Suppliers Upstream Downstream Retailer - Gas N’Grub Manufacturer 3
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How many new stores in 2011? How will new stores affect  demand? Any advertising campaigns or  promotions? How do I break out sales into  the three products? Other issues? 2010 monthly sales data is a good start, but what is missing? Month Sales ($) January $ 230,000 February $ 230,000 March $ 240,000 April $ 250,000 May $ 240,000 June $ 250,000 July $ 270,000 August $ 260,000 September $ 260,000 October $ 260,000 November* $ 280,000 December* $ 290,000 TOTAL: $ 3,060,000 Cheeznax Snack Foods 4 2010 History
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Forecast Demand Firm-level Market-level Supply Materials Labor supply Price Cost of supplies and services Cost of money — interest rates, currency rates Market price for firm’s product or service Definition : An estimate of the future level of some variable. Common variables include: 5
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Why forecast? Assess long-term capacity needs Develop budgets, hiring plans, etc. Plan production or order materials Get agreement within  company and across   supply chain partners 6
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Forecasting “Laws” Law 1 – Forecasts are almost always  wrong (however are still useful) Law 2 – Forecasts for the near term tend to  be more accurate Law 3 – Forecasts for groups of products  or services tend to be more accurate Law 4 - Forecasts are no substitute for  calculated values (Future Chapter on MRP) 7
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Used when situation is  ‘stable’ and historical  data exist Existing products Current technology Heavy use of  mathematical techniques Example - forecasting  sales of a mature  products Quantitative Methods Used when situation is  vague and little data  exist New products New technology Involves intuition,  experience Example - forecasting  sales to a new market Qualitative Methods Forecasting Approaches 8
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Selecting a Forecasting Method Quantitative historical data available. Evidence of a relationship between
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Chapter_9_-_Forecasting - BUS 370: Forecasting Chapter 9...

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