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Prin. of Mgt. & Prod. // EXAM 3 (Ch.3&5)
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Terms in this set (35)
Forecast
A statement about the future value of a variable of interest
1) Demand Expectancy- May be a function of some structural variation such as trend or seasonal variation
2) Accuracy- Potential size of forecast error
2 Important Aspects of Forecasts:
1) Plan the System- long range plans related to type of products/services to offer and facilities
2) Plan the use of the system- short and medium range plans related to inventory mgt., workforce levels, purchasing, budgeting, and scheduling
2 Uses for Forecasts:
1) Techniques assume some underlying system that existed in the past will persist in to the future
2) Forecasts are not perfect
3) Forecasts for groups of items are more accurate than those for individual items
4) Forecasts accuracy decreases as the forecasting horizon increases
4 Features Common to All Forecasts:
1) Reasonable
2) Accurate
3) Reliable
4) Expressed in meaningful units
5) Technique should be simple and easy to use
6) Cost-effective
6 Elements of a God Forecast:
1) Determine the goal of the forecast
2) Establish a time horizon
3) Obtain, clear, and analyze appropriate data
4) Selecting a forecasting technique
5) Make the forecast
6) Monitor the forecast errors
6 Steps in the Forecasting Process:
MAD (Mean Absolute Deviation)
Weights all errors evenly
MSE (Mean Squared Error)
Weights error according to their squared values
MAPE (Mean Absolute Percent Error)
Weights errors according to relative error
Qualitative Forecasting
Forecasting techniques that permit the inclusion of info such as human factors, personal opinions, and hunches; these factors are difficult or near impossible to quantify
Quantitative Forecasting
Forecasting techniques that rely on empirical data
1) Judgmental (Qualitative)
2) Associative Models (Quantitative)
3) Time Series (Quantitative)
3 Types of Forecasts:
1) Executive Opinions
2) Sales Force Opinions
3) Consumer Surveys
4) Other Approaches
4 Qualitative Methods of Judgmental Forecasting:
Simple Linear Regression
Technique that fits a variable to a set pf data points to estimate the relationship between variables
Correlation (r)
A measure of the similarity and direction of relationship between two variables
Correlation (r-squared)
A measure of the degree of variability in the values of y that is "explained" by the independent variable
1) Variations around the line are constant
2) Deviations around the average value (the line) should be normally distributed
3) Predictions are made only within the range of observed values
4) Assumes a relationship between predictor and outcome variables
4 Assumptions with Simple Linear Regression:
Time-Series Forecast
Forecasts that project data identified in recent observations at regular intervals
1) Trends- long-term shift in data
2) Seasonability- short-term variations in data
3) Irregular Variations- variations due to unusual circumstances
4) Random Variations- residual variations
5) Cycles- wavelike variations lasting more than one ???
5 Time-Series Behaviors:
Naive Forecast
Uses a previous value of a time series as the basis for a forecast
1) The model may be inadequate
2) Irregular variations may have occurred
3) The forecasting technique has been incorrectly applied
4) Random Variation
4 Sources of Forecast Errors:
1) Control Mechanisms
2) Tracking Signals
2 Tools for IDing Forecast Errors:
Reactive Approach
Views the forecast as future demand; reacts to meet that demand
Proactive Approach
Seeks to actively influence demand
Capacity
The upper limit on the load that an operating unit can handle
To achieve a balance between long-term supple capabilities and the predicted level of long-term demand
What is the goal of Capacity Planning?
Design Capacity
The maximum output rate or service capacity an operation, process, or facility is designed for
Effective Capacity
Design capacity minus allowances such as personal time, maintenance, and scrap
Actual Output
Rate of output achieved; cannot exceed effective capacity
Leading Capacity Strategy
Capacity strategy that builds capacity in advance of future demand increases
Following Capacity Strategy
Capacity strategy that build capacity when demand exceeds current capacity
Tracking Capacity Strategy
Similar to the following strategy, but adds capacity in relatively small increments to keep pace with increasing demand
Capacity Cushion
Buffer capacity used to offset demand uncertainty
Economies of Scale
If output rate is less than the optimal level, increasing the output rate results in lower average per unit costs
Diseconomies of Scale
If the output rate is more than the optimal level, increasing the output rate results in higher average per unit costs
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