CH 3 - Forecasting Flashcards
Medium- and longterm forecasts used for decisions related to strategy and estimating aggregate demand
Strategic Forecasts
Short-Term forecasts used as input for making day-to-day decisions related to meeting demand
Tactical Forecasts
Forecasting can be classified into four basic types:
- Qualitative
- Time Series Analysis
- Causal Relationships
4 Simulation
Based on the idea that data relating to past demand can be used to predict future demand
Time Series Analysis
______ techniques are subjective or judgemental and are based on estimates and options.
Qualitative
Cyclical factors are more difficult to determine because
the time span may be unknown or the cause of the cycle may not be considered
This influence may come from political elections, war, economic conditions, or sociological pressures
Cyclical Influence
Caused by chance events
Random Variations
Denotes the persistence of occurrence. The value expected at any point is highly correlated with its own past values
Autocorrelation
What are the four common types of trends?
- Linear Trend
- S-Curve Trend
- Asymptotic Trend
- Exponential Trend
A ______ trend is a straight continuous relationship
linear
An ______ trend is typical of a product growth and maturity cycle
S-Curve
An ______ Trend starts with the highest demand growth at the beginning but then tapers off.
Asymptotic
An _______ trend is common in products with explosive growth.
Exponential
In Forecasting, short term refers to?
Under three months
In Forecasting, medium term refers to?
three months to two years
In Forecasting, long term refers to?
greater than two years
Short term forecasts are used for ____ decisions
tactical
Use of _____ term forecasts for planning a strategy for meeting demand over the next 6 to 18 months
Medium
Short term models compensate for ____ ____ and adjust for short term changes
Random Variation
Medium term forecasts are useful for capturing _____ effects
Seasonal
____ term models detect general trends are useful in identifying major turning points
Long
Which forecasting model a firm should choose depends on: (Name 5)
- Time Horizon to Forecast
- Data Availability
- Accuracy Required
- Size of Forecasting Budget
- Availability of Qualified Personnel
Can be useful in removing the random fluctuations for forecasting. Simply calculate the average demand over more recent periods. Each time a new forecast is made, the oldest period is discarded and the newest included.
Moving Average
What’s the main disadvantage in calculating a moving average?
All individual elements must be carried as data because a new forecast period involves adding new data and dropping the earliest data.
A forecast made with past data where more recent data are given more significance than older data
Weighted Moving Average
What’s the simplest ways to choose weights in forecasting?
Experience and Trial and Error
Exponential smoothing techniques have become well accepted for six major reasons:
- It’s surprisingly accurate
- It’s relatively easy to formulate
- The user can understand how the model works
- Little computation is required to use the model
- Computer storage requirements are small due to limited use of historical data
- Tests for accuracy are easy to compute
In the exponential smoothing method, what three pieces of data are needed to forecast the future?
- The most recent forecast
- The actual demand that occured for that forecast period
- The smoothing constant alpha
The parameter in the exponential smoothing equation that controls the speed of reaction to differences between forecasts and actual demand
Smoothing Constant Alpha
The exponential smoothing with trend method involves adding a smoothing constant ____ to the equation
Delta
Exponential smoothing requires that the smoothing constants be given a value between __ and __
0, 1
A functional relationship between two or more correlated variables
Regression
A forecasting technique that assumes that past data and future projections fall around a straight line
Linear Regression Forecasting
Linear regression is useful for ___ ___ forecasting of major occurrences and _____ planning
Long Term, Aggregate
Linear regression is used both for ___ ____ forecasting and for _____ relationship forecasting
Time Series, Casual
When the dependent variable changes as a result of time, it is….
Time Series Analysis
If one variable changes because of the change in another variable, this is…
Casual Relationship
Chronologically ordered data that may contain one or more components of demand
Time Series
_____ of a time series means identifying and separating the time series data into components
Decomposition
The seasonal factor is constant no matter what the trend or average amount is. This is reffered to?
additive seasonal variation
The trend is multiplied by the seasonal index
Multiplicative seasonal variation
Period of the year characterized by some particular activity
Seasonal
Indicates other than annual recurrent periods of repetitive activity
Cyclical
The difference between what actually occurred and what was forecasted
Forecast Error
____ ____ occur when a consistent mistake is made in a forecast
Bias Errors
Sources of ____ include the failure to include the right variables, the use of the wrong relationships among variables, employing the wrong trend line, a mistaken shift in the seasonal demand from where it normally occurs, and the existence of some undetected secular trend
Bias
____ ____ can be defined as those that cannot be explained by the forecast model being used
Random Errors
The average forecast error using absolute values of the error of each past forecast
Mean Absolute Deviation
_____ is computed using the differences between the actual demand and the forecast demand without regard to sign.
MAD (Mean Absolute Deviation)
1 MAD is approximately ___ standard deviation
0.80
This measure gauges the error relative to the demand as a percentage
MAPE (Mean Absolute Percent Error)
Measurement that indicates whether the forecast average is keeping pace with any genuine upward or downward changes in demand
Tracking Signal (TS)
____ _____ Forecasting involves using independent variables other than time to predict future demand.
Causal Relationship
Forecasting method where a number of variables are considered, together with the effects of each on the item of interest
Multiple Regression Analysis
_______ forecasting techniques generally take advantage of the knowledge of experts and require much judgment.
Qualitative
What are some qualitative forecasting techniques? (name 4)
- Market Research
- Panel Consensus
- Historical Analogy
- Delphi Method
Firms often hire outside companies that specialize in ____ ____ to conduct this type of forecasting
Market Research
____ ____ is used mostly for product research in a sense of looking for new product ideas, likes and dislikes about existing products, which competitive products within a particular class are preferred.
Market Research
In a ____ ____ the idea that two heads are better than one is extrapolated to the idea that a panel of people from a variety of positions can develop a more reliable forecast than a narrower group.
Panel Consensus
____ Forecasts are developed through open meetings with a free exchange of ideas from all levels of management and individuals.
Panel
In trying to forecast demand for a new product, an ideal situation would be where an existing product or generic product could be used as a model.
Historical Analogy
Under panel consensus, a statement/opinion of a higher level person will likely weight more than a lower level person. Worst case is where lower level people feel threatened and won’t contribute their true beliefs. To prevent this, the ___ ____ conceals the identify of the individuals.
Delphi Method
Web-based tool used to coordinate demand forecasting, production and purchase planning, and inventory replenishment between supply chain trading partners.
Collaborative Planning, Forecasting, and Replenishment (CPFR)
____ applications to date are largely focused on the food, apparel, and general merchandise industries
CPFR
CPFR uses a cyclic and iterative approach to derive consensus supply chain forecasts. It consists of the following five steps:
- Creation of a front-end partnership agreement
- Joint Business Planning
- Development of demand forecasts
- Forecast sharing
- Inventory replenishment
Name the five steps in decompositioning a time series forecast
- Determine Seasonal Factor
- Deseasonlize Original Data
- Develop regression line for deseasonalized data
- Project regression line over forecast period
- Adjust regression line for seasonal factor
A tracking signal of __ or higher indicates a good forecast
5
