Judgmental Forecasting is a method that relies on the subjective judgment of experts to make predictions about future outcomes. This approach is particularly useful in scenarios where quantitative data is scarce, unreliable, or where rapid changes render historical data less relevant. It is often used to forecast new products, technology adoption rates, or market trends, providing a flexible and quick forecasting tool.
Identify the forecasting problem and its scope. | Select experts with relevant knowledge and experience. | Gather judgments through surveys, interviews, or meetings. | Consolidate individual judgments into a collective forecast. | Review and adjust the forecast based on additional insights or feedback.
Use structured methods to collect and aggregate judgments | Combine judgmental with quantitative methods for robustness | Regularly review and recalibrate forecasts based on outcomes
Flexible and adaptable to new or unique situations | Quick to implement when time or data constraints exist | Incorporates human intuition and experience
Subject to biases and inconsistencies of individual judgment | Lacks the precision of data-driven models | Can be difficult to validate or replicate
Launching a new product with no historical sales data | Predicting outcomes in rapidly changing markets
When extensive, relevant historical data is available | In highly regulated environments requiring detailed justification