FORECASTING Flashcards
(32 cards)
The art and science of predicting future events.
FORECASTING
TYPES OF FORECAST
- Economic Forecast
- Technological Forecast
- Demand Forecast
COMMON FEATURES OF FORECASTS
- Forecasting repeats itself after a few years
- Forecasts are not perfect
- Forecast accuracy decreases as the time period covered by forecast (time horizon) increases.
ELEMENTS OF A GOOD FORECAST
- Timely
- Accurate
- Reliable
- Expressed in meaningful units
- Should be in writing
- Simple to understand and use
- Cost effective
FORECASTING PROCESS
- Determine the purpose
- Establish time horizon
- Obtain clean, and analyze appropriate data
- Select a forecasting technique
- Make a forecast
- Monitor the forecast errors
FORECASTING: TIME HORIZONS
- Short Range
- Medium Range
- Long Range
3 AREAS/ASPECTS OF OPERATIONS
- Supply Chain Management
- Human Resources
- Capacity
Approaches to Forecasting
- Qualitative
- Quantitative
Qualitative
- Executive Opinion
- Sales force composite
- Delphi Method
- Market Survey
Quantitative
- Naive Approach
- Moving Average
- Exponential Smoothing
- Trend Projections
- Linear Regression
This can often be accomplished by merely plotting the data and visually examining the plot.
Time Series Models
Time Series Models: Analyze Patterns
- Trend
- Seasonality
- Cycles
- Irregular Variations
- Random Variations
A forecast for any period that equals the previous period’s actual value.
NAIVE
A forecasting method that uses an average of the n most recent periods of data to forecast the next period.
MOVING AVERAGE
Similar to a moving average, except that it assigns more weight to the most recent values in a time series.
Weighted Moving Average
A weighted moving average forecasting technique in which data points are weighted by an exponential function.
Exponential Smoothing
Difference between the actual value and the value that was predicted for a given period.
Measuring Forecast Error
A measure of the overall forecast error for a model.
Mean Absolute Deviation
The average of the squared differences between the forecasted and observed values.
Mean Squared Error
The average of the absolute differences between the forecast and actual values, expressed as a percent of actual values.
Mean Absolute Percentage Error
ASSOCIATIVE MODELS
- Trend Projection
- Regression Analysis
- Standard Error of the Estimate
- Correlation Coefficient for Regression
A time series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecast
Trend Projection
A straight-line mathematical model to describe the functional relationships between independent and dependent variables.
Regression Analysis
A measure of variability around the regression line—its standard deviation.
Standard Error of the Estimate
