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Accuracy of forecasts in strategic intelligence.

David R Mandel¹, Alan Barnes²

¹Socio-Cognitive Systems Section, Defence Research and Development Canada, Toronto, ON, Canada M3K 2C9; and drmandel66@gmail.com.

Proceedings of the National Academy of Sciences of the United States of America

|July 16, 2014

Summary

Strategic intelligence forecast accuracy was assessed, revealing good discrimination and calibration. Analysts showed underconfidence, especially on harder, more important forecasts, but recalibration improved accuracy.

Keywords:

forecasting intelligence analysis prediction quality control recalibration

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Area of Science:

Intelligence analysis
Decision science
Cognitive psychology

Background:

Assessing the accuracy of strategic intelligence forecasts is crucial for effective policy-making.
Understanding the calibration and discrimination of these forecasts provides insights into analyst performance.

Purpose of the Study:

To evaluate the accuracy of 1,514 strategic intelligence forecasts.
To identify factors influencing forecast accuracy, including analyst seniority and forecast difficulty.
To examine the nature and extent of miscalibration, particularly underconfidence.

Main Methods:

Analysis of 1,514 strategic intelligence forecasts extracted from intelligence reports.
Statistical assessment of forecast discrimination and calibration.
Comparison of accuracy metrics based on analyst seniority, forecast difficulty, and perceived policy importance.

Main Results:

Forecast discrimination and calibration were found to be very good.
Senior analysts and easier forecasts demonstrated better discrimination.
Underconfidence was observed, particularly for harder and more policy-important forecasts, despite high discrimination.

Conclusions:

Strategic intelligence forecasts exhibit a high degree of accuracy, warranting tempered optimism.
Underconfidence in forecasting, while present, can be mitigated through recalibration.
Intelligence producers should focus on promoting informativeness while avoiding overstatement in their forecasts.