13 Questions
What is the primary requirement for applying quantitative forecasting techniques?
Existence of adequate and accurate historical data
Why may a qualitative forecasting technique be preferred?
When the demand pattern is unstable over time
What is a key consideration in selecting a forecasting technique?
The demand pattern and available data
What are the two main approaches to forecasting?
Top-down and bottom-up
What is an important consideration when defining the scope of a forecasting project?
The units of measure for the forecast
What is a key difference between qualitative and quantitative forecasting models?
Qualitative models rely on opinion, while quantitative models rely on historical data.
What is a common characteristic of all forecasting models?
They include a degree of inaccuracy.
What is an important factor to consider when choosing a forecasting model?
All of the above.
What should a forecasting model be matched to?
The knowledge and sophistication of the user.
Why do managers often prefer simpler forecasting techniques?
Because they are easier to understand.
What is a limitation of many forecasting models?
They require a large amount of historical data.
Why might a specific forecasting model be indicated?
Because it fits the organizational environment and management expertise.
What should be considered when evaluating different forecasting models?
The desired outputs and significant inputs, as well as various factors such as cost and data availability.
Study Notes
Forecasting Models
- Forecasting models can be classified in various ways, including qualitative or quantitative, formal or informal, intrinsic or extrinsic, statistical or non-statistical, and descriptive or explanatory.
- Qualitative models rely on opinion, judgment, experience, and expertise.
- Quantitative models rely on the use of historical data or associations among variables to develop forecasts.
Characteristics of Forecasting Models
- Some techniques are simple, while others are complex.
- No single technique works all the time, and all forecasts include a degree of inaccuracy.
- Allowances should be made for the inaccuracy.
Factors Influencing Forecasting Model Choice
- The desired outputs and significant inputs (variables) should be considered when selecting a forecasting model.
- Factors such as cost, data availability, staff skills, hardware and software availability, desired accuracy, and time horizon under consideration influence the choice of forecasting model.
Matching Forecasting Models to Users
- The forecasting model should be matched to the knowledge and sophistication of the user.
- Managers are reluctant to use results from techniques they do not understand, and therefore, fairly crude techniques may be more popular.
Data Requirements
- Many models require a substantial amount of historical data.
- The existence of adequate and accurate historical data is essential for quantitative forecasting techniques.
- Poor data cannot yield good forecasts, even with elegant forecasting techniques.
Demand Pattern and Forecasting Techniques
- The demand pattern affects the type of forecasting technique selected.
- If several components (trend, seasonal, cyclic) are apparent, more advanced techniques are needed.
- If the demand pattern is unstable over time, a qualitative technique may be needed.
Forecasting Considerations
- Forecasting involves considering items to be forecast, such as products, product groups, or assemblies.
- Top-down or bottom-up forecasting approaches can be used.
- Forecasting techniques, units of measure, time interval, and forecast horizon must be considered.
Learn about different forecasting models, including qualitative and quantitative models, and their implementation techniques. Understand the classification of forecasting models based on techniques, effort, and cost.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
