Podcast
Questions and Answers
What is one of the primary learning objectives regarding time horizons in forecasting?
What is one of the primary learning objectives regarding time horizons in forecasting?
Which forecasting method involves calculating an average of past data points?
Which forecasting method involves calculating an average of past data points?
What is the key purpose of monitoring and controlling forecasts?
What is the key purpose of monitoring and controlling forecasts?
Which of the following approaches uses historical data to identify patterns and predict future outcomes?
Which of the following approaches uses historical data to identify patterns and predict future outcomes?
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What is an important aspect of conducting regression and correlation analysis in forecasting?
What is an important aspect of conducting regression and correlation analysis in forecasting?
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What is the primary focus of a short-range forecast?
What is the primary focus of a short-range forecast?
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Which forecasting approach is most suitable when dealing with vague situations and little data?
Which forecasting approach is most suitable when dealing with vague situations and little data?
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What is typically true about the accuracy of short-term forecasts compared to long-term forecasts?
What is typically true about the accuracy of short-term forecasts compared to long-term forecasts?
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Which of the following is NOT one of the seven steps in forecasting?
Which of the following is NOT one of the seven steps in forecasting?
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Which time horizon is classified as medium-range forecasting?
Which time horizon is classified as medium-range forecasting?
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Study Notes
Course Information
- Course title: Production & Operations Management
- Course code: IME 316
- Instructor: Zakaria Yahia, PhD
- Associate Professor of Industrial Engineering and Systems Management
- Area of expertise: Innovative Design Engineering
Forecasting Overview
- Forecasting is the art and science of predicting future events.
- It's the foundation for all business decisions related to production, inventory, personnel, and facilities.
- Forecasting approaches can be qualitative or quantitative.
Forecasting Time Horizons
- Short-range: Less than 3 months, used for purchasing, workforce levels, and production levels.
- Medium-range: 3 months to 3 years, used for sales and production planning.
- Long-range: 3+ years, used for new product planning and facility location.
Distinguishing Differences
- Medium/long-range forecasts address broader issues impacting planning, products, plants, and processes.
- Short-term forecasts use different methodologies than longer-term forecasts.
- Short-term forecasts tend to be more accurate than longer-term ones.
Seven Steps in Forecasting
- Determine the use of the forecast.
- Select what needs forecasting.
- Determine the forecast time horizon.
- Select the appropriate forecasting model.
- Collect the necessary data.
- Develop the forecast.
- Validate and implement the results.
Forecasting Approaches
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Qualitative: Used when data is limited (new products, new technologies).
- Relies on intuition, experience, and expert opinion.
- Methods include jury of executives' opinion, sales force composite, Delphi method, and consumer market survey.
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Quantitative: Used when historical data is available and the situation is stable (existing products).
- Relies on mathematical and statistical methods.
- Methods encompass time-series models (naive approach, moving averages, exponential smoothing, trend projections) and associative models (linear regression).
Overview of Quantitative Approaches
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Time-Series Models: The future is a function of the past.
- Trend: A long-term upward or downward movement.
- Seasonal: Regular fluctuations over a specific period.
- Cyclical: Repeating up and down movements over longer periods.
- Random: Unexpected variations.
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Associative Models: Variables or factors influencing the variable being forecast.
- Linear regression.
Components of Demand
- Trend component: A long-term movement in demand.
- Seasonal peaks: Short-term fluctuations in demand.
- Random variation: Unexpected changes in demand.
Forecasting and Competitiveness of Disney!
- Disney uses multiple forecasting methods (daily, weekly, monthly, annual, and 5-year forecasts).
- Forecasts support labor, maintenance, operations, finance, and park scheduling decisions.
- Forecasts help adjust operating hours, rides, shows, staffing, and guest capacity.
- Forecast data is gathered from surveys to 1 million guests, employees, and travel professionals each year.
- Inputs include airline specials, Federal Reserve policies, market trends, and vacation/holiday schedules.
- Average forecast error is 5% for 5-year forecasts, and 0-3% for annual forecasts.
Overview of Quantitative Approaches (Time-Series Models)
- Naive approach: Assumes next period's demand is the same as the most recent period's demand.
- Moving averages: A series of arithmetic means, used for smoothing when no trend exists.
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Exponential smoothing: A weighted moving average where weights decline exponentially.
- Requires a smoothing constant (α), typically between 0.05 and 0.5.
Overview of Quantitative Approaches (Time-Series Models)
- Trend projections: Fitting a trend line to historical data to project into the medium to long range. Using the least squares technique.
- Least squares method: used to get the equation to the regression line.
Overview of Quantitative Approaches (Associative Models)
- Associative Forecasting: used when changes in one or more independent variables can be used to predict changes in the dependent variable.
- Linear Regression commonly used technique.
Correlation Coefficient
- Strength of linear relationship between variables.
- Does not imply causation, only association.
- Ranges from -1 to +1, 1 being a perfect positive correlation, -1 being perfect negative correlation.
Which technique to use?
- Select the appropriate method based on accuracy.
- Forecast error (Actual - Forecast).
- Evaluate using measures of error (MAD, MSE, MAPE).
Common Measures of Error
- Mean Absolute Deviation (MAD): Average absolute difference between forecast and actual values.
- Mean Squared Error (MSE): Average of squared differences between forecast and actual values.
- Mean Absolute Percent Error (MAPE): Average absolute percentage difference between forecast and actual values.
Choosing the Technique
- Accurate forecasting is the goal.
- Selecting the technique with the lowest forecast error.
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Description
Test your knowledge on forecasting in Production and Operations Management. This quiz covers forecasting time horizons and distinguishes between short-range, medium-range, and long-range forecasting techniques. Assess your understanding of how these forecasts influence business decisions.
