Forecasting - College of Business Administration Cal State...

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Unformatted text preview: College of Business Administration Cal State San Marcos Production & Operations Management HTM 305 Dr. M. Oskoorouchi Summer 2006 CHAPTER 3 Forecasting FORECAST : • A statement about the future value of a variable of interest such as demand. • Forecasts affect decisions and activities throughout an organization • Accounting, finance • Human resources • Marketing • MIS • Operations • Product / service design What is Forecasting? What is Forecasting? Accounting Cost/profit estimates Finance Cash flow and funding Human Resources Hiring/recruiting/training Marketing Pricing, promotion, strategy MIS IT/IS systems, services Operations Schedules, MRP, workloads Product/service design New products and services Uses of Forecasts Uses of Forecasts • Assumes causal system past ==> future • Forecasts rarely perfect because of randomness • Forecasts more accurate for groups vs. individuals • Forecast accuracy decreases as time horizon increases I see that you will get an A this semester. Common in all forecasts Common in all forecasts Elements of a Good Forecast Elements of a Good Forecast Timely Accurate Reliable M e a n i g f u l Written E s y t o Steps in the Forecasting Process Steps in the Forecasting Process Step 1 Determine purpose of forecast Step 2 Establish a time horizon Step 3 Select a forecasting technique Step 4 Gather and analyze data Step 5 Prepare the forecast Step 6 Monitor the forecast “The forecast” Types of Forecasts Types of Forecasts • Judgmental- uses subjective inputs • Time series - uses historical data assuming the future will be like the past • Associative models - uses explanatory variables to predict the future Judgmental Forecasts Judgmental Forecasts • Executive opinions • Sales force opinions • Consumer surveys • Outside opinion Time Series Forecasts Time Series Forecasts • Trend- long-term movement in data • Seasonality- short-term regular variations in data • Cycle – wavelike variations of more than one year’s duration • Irregular variations - caused by unusual circumstances • Random variations - caused by chance Forecast Variations Forecast Variations Trend Irregular variation Seasonal variations 90 89 88 Cycles Naive Forecasts Naive Forecasts Uh, give me a minute. ... We sold 250 wheels last week. ... Now, next week we should sell. ... The forecast for any period equals the previous period’s actual value. • Stable time series data • F(t) = A(t-1) • Seasonal variations • F(t) = A(t-n) • Data with trends • F(t) = A(t-1) + (A(t-1) – A(t-2)) Uses for Naive Forecasts Uses for Naive Forecasts • Simple to use • Virtually no cost • Quick and easy to prepare • Easily understandable • Can be a standard for accuracy • Cannot provide high accuracy Naive Forecasts Naive Forecasts Techniques for Averaging Techniques for Averaging • Moving average • Weighted moving average • Exponential smoothing Moving Averages...
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Forecasting - College of Business Administration Cal State...

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