Quantifying countermeasure and detection effectiveness to threats using U-boat data from the Second World War

Abstract

ABSTRACT This article provides a detailed analysis using learning theory of the classic naval confrontation between the Allies and Germany in the North Atlantic during the Second World War. New measures of countermeasure effectiveness introduced are the rate and probability of sinking as a function of the risk exposure and learning opportunity on both sides. These replace the ‘sweep rate’ used in earlier analyses, and demonstrates that a relevant risk exposure, experience and learning measure must replace the usual calendar time representation. Using archival data, the analysis confirms that the use of decryption intelligence did not itself result in a statistically significant increase in U-boat sinkings. At both the entire system and the individual human performance levels the rate, probability and number of sinkings are all exponential in form, decreasing with increasing experience and/or risk exposure. The reduction of between five and ten in the merchant ship loss data is exactly the range attained in multiple industrial and technological systems worldwide. The analysis shows the learning rate and countermeasure effectiveness trends are adversely affected by the stress of combat and wartime chaos as compared to peacetime.