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Which production forecasting model is most suitable when launching a new product in the absence of historical sales data?
Question

Which production forecasting model is most suitable when launching a new product in the absence of historical sales data?

A.

Time Series Analysis

B.

Causal Modelling

C.

Qualitative Forecasting

D.

Regression Analysis

Correct option is C

Time Series Analysis
Works by analyzing historical data points over time to find trends, seasonality, or patterns.
Since there is no past sales data, this method cannot be used effectively.
Causal Modelling
Relies on relationships between independent variables (like price, advertising) and dependent variables (like sales).
For a brand-new product, it is often difficult to define these relationships accurately because there is no prior performance data.
Qualitative Forecasting
Based on expert judgment, market surveys, focus groups, or Delphi methods.
Experts use experience, intuition, and market research to predict sales.
Does not require historical numerical data, making it ideal for new product launches.
Regression Analysis
Uses statistical relationships between variables to predict outcomes.
Requires past data to establish the regression equation, which is not available for a new product.

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