Dispersion versus Lethality

This is a follow-up post to the post discussing Trevor Dupuy’s work compared to the Army Research Laboratories (ARL) current work:

The Evolution of Weapons and Warfare?

The work by ARL produced a graph similar to this one by Trevor Dupuy, except it was used to forecast the “figure of regularity” (which I gather means firepower or lethality). But if you note there is another significant line on Trevor Dupuy’s graph, besides the weapons’ “theoretical killing capacity.” It is labeled Dispersion. Note the left side of the graph where it is labeled “Disperion: Square Meters per Man in Combat.” It also goes up as the “theoretical killing capacity” of the weapons goes up.

This is the other side of equation. For every action, there is an equal and opposite reaction to paraphrase a famous theorist. This results in this chart from Col. Dupuy:

Now….this is pretty damn significant….for as firepower, or lethality, or “theoretical killing capacity” has gone up, even geometrically…..daily casualty rates have declined. What is happening? Well, not only “for every action, there is an equal and opposite reaction,” but in fact, the reaction has outweighed the increase in firepower/lethality/killing capacity over time. This is worth thinking about. For as firepower has gone up, daily casualty rates have declined.

In fact, I did discuss this in my book War By Numbers (Chapter 13: The Effects of Dispersion on Combat). Clearly there was more to “dispersion” than just dispersion, and I tried to illustrate that with this chart:

To express it in simple English, people are dispersing, increasing engagement ranges and making more individual use of cover and concealment (page 166). Improvements in weapons, which occur on both sides, have also been counteracted by changes in deployment and defense. These changes have been more significant than the increases in lethality. See pages 166-169 of War by Numbers for a more complete explanation of this chart.

The issues related to lethality and forecasting the future of lethality gets a little complex and multifaceted.

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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.
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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.
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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) , The Battle of Prokhorovka (Stackpole Books, Guilford, CT., 2019), The Battle for Kyiv (Frontline Books, Yorkshire, UK, 2023), Aces at Kursk (Air World, Yorkshire, UK, 2024), Hunting Falcon: The Story of WWI German Ace Hans-Joachim Buddecke (Air World, Yorkshire, UK, 2024) and The Siege of Mariupol (Frontline Books, Yorkshire, UK, 2024).
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Mr. Lawrence lives in northern Virginia, near Washington, D.C., with his wife and son.

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4 Comments

  1. Notice that the difference between losing and winning also has gotten smaller, in terms of daily casualty rates (although not necessarily in terms of relative ratio of percentages, such that the relative ratio of percentages is 30%/20%=1.5 for Thirty Years War and roughly 3%/2%=1.5 for Yom Kippur War).

    Maybe, it is now taking less time and less proportional destruction of a unit/army/etc. for the losing side to “read the writing on the wall.”

    Has anyone encountered a maxim indicating that if a unit/army/etc. becomes aware that it is experiencing a casualty rate for its unit/army/etc. that is 50% higher than the casualty rate being experienced by its opponent then the losing unit/army/etc. “throws in the towel?”

    I wonder whether impovements in communication and command control have led to less time being needed in order to ascertain (and act upon knowledge about) the relative casualty trend and thus the likely result.

    L’Shana Tovah,
    Neal

    • Well, it is “average” percent per day casualty rates. In most cases, the attacker outnumbered the defender. So, if the attacker had 30,000 troops and the defender has 20,000 troops and the attacker losses 20% and the defender losses 30%, then their actual losses are the same. It is their percent losses that are different.

      • Chris, that’s what I stated.

        More importantly, what do you think about the consistency of the pattern of the loser having a daily casualty rate that is 50% higher than the winner’s daily casualty rate? Doesn’t that strike you as an interesting pattern? Might it be a maxim?

  2. By the way, your blog clock isn’t on Daylight Saving Time (DST); of course, that soon won’t matter since DST ends on November 3 (just a month from now).

    Oh, and I am referring to an internal percentage rate when I referred to “rate” in my previous comments.

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