The Lockwood Analytical Method for Prediction (LAMP)

A Method for Predictive Intelligence Analysis

Nonfiction, Social & Cultural Studies, Political Science, International, International Security, History
Cover of the book The Lockwood Analytical Method for Prediction (LAMP) by Colonel, USAR, Ret. Jonathan S. Lockwood, Bloomsbury Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Colonel, USAR, Ret. Jonathan S. Lockwood ISBN: 9781623568610
Publisher: Bloomsbury Publishing Publication: September 12, 2013
Imprint: Bloomsbury Academic Language: English
Author: Colonel, USAR, Ret. Jonathan S. Lockwood
ISBN: 9781623568610
Publisher: Bloomsbury Publishing
Publication: September 12, 2013
Imprint: Bloomsbury Academic
Language: English

The Lockwood Analytical Method for Prediction (LAMP) is a systematic technique for predicting short-term, unique behaviors. Using primarily qualitative empirical data, LAMP allows the analyst to predict the most likely outcomes for specific research questions across a wide range of intelligence problems, such as cyber threats in the U.S., the possibility of an Al Qaeda attack, the likelihood of Iran providing nuclear capability to terrorist groups, or the future actions of the Mexican drug cartel.

LAMP offers an innovative and powerful method for organizing all available information based on the perceptions of the national actors, using it to make relevant predictions as to which alternate future is most likely to occur at a given moment in time. Its transparent structure enables anyone to see how an analyst gets from point A to point B to produce an intelligence estimate. LAMP differs from other analytical techniques in that it is based on determining the relative probability of a range of alternate futures, rather than attempting to determine the quantitative probability of their occurrence.

After explaining its theoretical framework, the text leads the reader through the process of predictive analysis before providing practical case studies showing how LAMP is applied against real world problems, such as the possible responses of Israel, the U.S., and Lebanon to the behavior of Hezbollah or the competing visions of the future of Afghanistan. Evaluation of the method is provided with the case studies to show the effectiveness of the LAMP predictions over time. The book is complemented by a website with downloadable software for use by students of intelligence in conducting their own predictive analysis. It will be an essential tool for the analyst and the student, not only for national security issues but also for competitive intelligence.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The Lockwood Analytical Method for Prediction (LAMP) is a systematic technique for predicting short-term, unique behaviors. Using primarily qualitative empirical data, LAMP allows the analyst to predict the most likely outcomes for specific research questions across a wide range of intelligence problems, such as cyber threats in the U.S., the possibility of an Al Qaeda attack, the likelihood of Iran providing nuclear capability to terrorist groups, or the future actions of the Mexican drug cartel.

LAMP offers an innovative and powerful method for organizing all available information based on the perceptions of the national actors, using it to make relevant predictions as to which alternate future is most likely to occur at a given moment in time. Its transparent structure enables anyone to see how an analyst gets from point A to point B to produce an intelligence estimate. LAMP differs from other analytical techniques in that it is based on determining the relative probability of a range of alternate futures, rather than attempting to determine the quantitative probability of their occurrence.

After explaining its theoretical framework, the text leads the reader through the process of predictive analysis before providing practical case studies showing how LAMP is applied against real world problems, such as the possible responses of Israel, the U.S., and Lebanon to the behavior of Hezbollah or the competing visions of the future of Afghanistan. Evaluation of the method is provided with the case studies to show the effectiveness of the LAMP predictions over time. The book is complemented by a website with downloadable software for use by students of intelligence in conducting their own predictive analysis. It will be an essential tool for the analyst and the student, not only for national security issues but also for competitive intelligence.

More books from Bloomsbury Publishing

Cover of the book Data Profiling and Insurance Law by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Gender, Power and Sexual Abuse in the Pacific by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Eat Like a Local PARIS by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book The Lion Heart by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book The School for Scandal by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Arab Feminisms: Gender and Equality in the Middle East by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book The Cavalry Lance by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Operation Pointblank 1944 by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Film Music in 'Minor' National Cinemas by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Citizen Delhi by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Soviet Destroyers of World War II by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Game, Set and Match by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book The Wenger Revolution by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book Peter L. Berger and the Sociology of Religion by Colonel, USAR, Ret. Jonathan S. Lockwood
Cover of the book My First Book of London by Colonel, USAR, Ret. Jonathan S. Lockwood
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy