SMEs

Continuing my comments on the article in the December 2018 issue of the Phalanx by Alt, Morey and Larimer (this is part 6 of 7; see Part 1, Part 2, Part 3, Part 4, Part 5).

SMEs….is a truly odd sounding acronym that means Subject Matter Experts. They talk about it extensively in their article, and this I have no problem with. I do want to make three points related to that:

  1. A SME is not a substitution for validation.
  2. In some respects, the QJM (Quantified Judgment Model) is a quantified and validated SME.
  3. How do you know that the SME is right?

If you can substitute a SME for a proper validation effort, then perhaps you could just substitute the SME for the model. This would save time and money. If your SME is knowledgable enough to sprinkle holy water on the model and bless its results, why not just skip the model and ask the SME. We could certainly simplify and speed up analysis by removing the models and just asking our favorite SME. The weaknesses of this approach are obvious.

Then there is Trevor N. Dupuy’s Quantified Judgment Model (QJM) and Quantified Judgment Method of Analysis (QJMA). This is, in some respects, a SME quantified. Actually it was a board of SMEs, who working with a series of historical studies (the list of studies starts here: http://www.dupuyinstitute.org/tdipubs.htm ). These SMEs developed a set of values for different situations, and then insert them into a model. They then validated the model to historical data (also known as real-world combat data). While the QJM has come under considerable criticism from elements of the Operations Research community…..if you are using SMEs, then in fact, you are using something akin, but less rigorous, than Trevor Dupuy’s Quantified Judgment Method of Analysis.

This last point, how do we know that the SME is right, is significant. How do you test your SMEs to ensure that what they are saying is correct? Another SME, a board of SMEs? Maybe a BOGSAT? Can you validate SMEs? There are limits to SME’s. In the end, you need a validated model.

 

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Christopher A. Lawrence
Christopher A. Lawrence

Christopher A. Lawrence is a professional historian and military analyst. He is the Executive Director and President of The Dupuy Institute, an organization dedicated to scholarly research and objective analysis of historical data related to armed conflict and the resolution of armed conflict. The Dupuy Institute provides independent, historically-based analyses of lessons learned from modern military experience.

Mr. Lawrence was the program manager for the Ardennes Campaign Simulation Data Base, the Kursk Data Base, the Modern Insurgency Spread Sheets and for a number of other smaller combat data bases. He has participated in casualty estimation studies (including estimates for Bosnia and Iraq) and studies of air campaign modeling, enemy prisoner of war capture rates, medium weight armor, urban warfare, situational awareness, counterinsurgency and other subjects for the U.S. Army, the Defense Department, the Joint Staff and the U.S. Air Force. He has also directed a number of studies related to the military impact of banning antipersonnel mines for the Joint Staff, Los Alamos National Laboratories and the Vietnam Veterans of American Foundation.

His published works include papers and monographs for the Congressional Office of Technology Assessment and the Vietnam Veterans of American Foundation, in addition to over 40 articles written for limited-distribution newsletters and over 60 analytical reports prepared for the Defense Department. He is the author of Kursk: The Battle of Prokhorovka (Aberdeen Books, Sheridan, CO., 2015), America’s Modern Wars: Understanding Iraq, Afghanistan and Vietnam (Casemate Publishers, Philadelphia & Oxford, 2015), War by Numbers: Understanding Conventional Combat (Potomac Books, Lincoln, NE., 2017) and The Battle of Prokhorovka (Stackpole Books, Guilford, CT., 2019)

Mr. Lawrence lives in northern Virginia, near Washington, D.C., with his wife and son.

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