Forecasting Models: Key Factors and Methods

Key Factors in Forecasting Models

1. Variables in a Competitive Model Forecast

Variables considered for forecasting in a competitive model:

• Marketing
• Production
• Finance
• Human Resources
• Strategic Planning

2. Defining a Forecast

A forecast is an early estimate of the value of a variable, such as the demand for a product.

3. Main Factors to Predict in a Company

Key variables to forecast in a company include:

• Raw material cost
• Labor cost
• Feedstock availability
• Manpower availability
• Capacity
• Maintenance requirements

4. Characteristics of Forecasting Variables

I. Time Dependence: All forecasting situations deal with the future, and time is directly involved. Forecasts are made for specific points in time, and changes to that point generally alter the prognosis.

II. Uncertainty: Uncertainty is always present in forecasting situations. If administrators had certainty about future circumstances, preparing a forecast would be trivial.

5. Important Factors in Selecting a Forecasting Model

Factors to consider when selecting a forecasting model:

• The context of the forecast
• The relevance and availability of historical data
• The degree of accuracy desired
• The time period to be forecast
• The cost-benefit of the forecast

6. Classification of Forecasting Models

Forecasting models can be classified as:

• Qualitative
• Quantitative
• Time Series Analysis
• Causal Models

7. When to Use Qualitative Techniques

Qualitative techniques are used when data is scarce, such as when introducing a new product to the market. These techniques rely on personal judgment and relationships to transform qualitative information into quantitative estimates.

8. Purpose of the Delphi Method

The Delphi method is used for long-term forecasting, forecasting sales of new products, and technological forecasting.

9. Qualitative Methods: Purpose and Estimated Time

Market Research: Used to evaluate and test hypotheses about real markets.

Estimated time: More than three months. Accuracy can be excellent, depending on the care taken in the research.

10. Visionary Forecasts: Purpose and Estimated Time

Visionary Forecasts: Used to make predictions about the future using personal intuition.

Estimated time: One week. Accuracy is generally poor.

11. Historical Analogy: Purpose and Estimated Time

Historical Analogy: Used for new products based on comparative analysis of the introduction and growth of similar products.

Estimated time: More than a month. Accuracy is fair to good.

12. The Quantitative Method

The quantitative method involves time series analysis, which aims to find patterns in past data and project them into the future.

13. Patterns of a Time Series

Common time series patterns include:

• Horizontal or stationary
• Long-term trend
• Seasonal effect
• Cyclic effect