Then-Lt. Gen. James Mattis, commander of U.S. Marine Corps Forces, Central Command, speaks to Marines with Marine Wing Support Group 27, in Al Asad, Iraq, in May 2006. [Photo: Cpl. Zachary Dyer]
Ever since publication of the U.S. National Defense Strategy by then-Secretary of Defense James Mattis’s Defense Department in early 2018 made the term “lethality” a foundational principle, there has been an open-ended discussion as to what the term actually means.
In his recent memoir, co-written with Bing West, Call Sign Chaos: Learning to Lead (Random House, 2019), Mattis offered his own definition of lethality. Sort of.
At the beginning of Chapter 17 (pages 235-236), he wrote (emphasis added):
LETHALITY AS THE METRIC
History presents many examples of militaries that forgot that their purpose was to fight and win. So long as we live in an imperfect world, one containing enemies of democracy, we will need a military strictly committed to combat-effectiveness. Our liberal democracy must be protected by a bodyguard of lethal warriors, organized, trained, and equipped to dominate in battle. …
The need for lethality must be the measuring stick against which we evaluate the efficacy of our military. By aligning the entire military enterprise—recruiting, training, educating, equipping, and promoting—to the goal of compounding lethality, we best deter adversaries, or if conflict occurs, win at lowest cost to our troops’ lives. …
While not defining lethality explicitly, it would appear that Mattis equates it with “combat-effectiveness,” which he also does not explicitly define, but seems to mean as the ability “to dominate in battle.” It would seem that Mattis understands lethality not as the destructive quality of a weapon or weapon system, but as the performance of troops in combat.
More than once he also refers to lethality as a metric, which suggests that it can be quantified and measured, perhaps in terms of organization, training, and equipment. It is likely Mattis would object to that interpretation, however, given his hostility to Effects Based Operations (EBO), as implemented by U.S. Joint Forces Command, before he banned the concept from joint doctrine in 2008, as he related on pages 179-181 in Call Sign Chaos.
M4A1 Sherman destroyed in combat in Tunisia, 1943.
[NOTE: This piece was originally posted on 23 August 2016]
A few years ago, I came across a student battle analysis exercise prepared by the U.S. Army Combat Studies Institute on the Battle of Kasserine Pass in Tunisia in February 1943. At the time, I noted the diagram below (click for larger version), which showed the locations of U.S. tanks knocked out during a counterattack conducted by Combat Command C (CCC) of the U.S. 1st Armored Division against elements of the German 10th and 21st Panzer Divisions near the village of Sidi Bou Zid on 15 February 1943. Without reconnaissance and in the teeth of enemy air superiority, the inexperienced CCC attacked directly into a classic German tank ambush. CCC’s drive on Sidi Bou Zid was halted by a screen of German anti-tank guns, while elements of the two panzer divisions attacked the Americans on both flanks. By the time CCC withdrew several hours later, it had lost 46 of 52 M4 Sherman medium tanks, along with 15 officers and 298 men killed, captured, or missing.
During a recent conversation with my colleague, Chris Lawrence, I recalled the diagram and became curious where it had originated. It identified the location of each destroyed tank, which company it belonged to, and what type of enemy weapon apparently destroyed it; significant battlefield features; and the general locations and movements of the enemy forces. What it revealed was significant. None of CCC’s M4 tanks were disabled or destroyed by a penetration of their frontal armor. Only one was hit by a German 88mm round from either the anti-tank guns or from the handful of available Panzer Mk. VI Tigers. All of the rest were hit with 50mm rounds from Panzer Mk. IIIs, which constituted most of the German force, or by 75mm rounds from Mk. IV’s. The Americans were not defeated by better German tanks. The M4 was superior to the Mk. III and equal to the Mk. IV; the dreaded 88mm anti-tank guns and Tiger tanks played little role in the destruction. The Americans had succumbed to superior German tactics and their own errors.
Counting dead tanks and analyzing their cause of death would have been an undertaking conducted by military operations researchers, at least in the early days of the profession. As Chris pointed out however, the Kasserine battle took place before the inception of operations research in the U.S. Army.
After a bit of digging online, I still have not been able to establish paternity of the diagram, but I think it was created as part of a battlefield survey conducted by the headquarters staff of either the U.S. 1st Armored Division, or one of its subordinate combat commands. The only reference I can find for it is as part of a historical report compiled by Brigadier General Paul Robinett, submitted to support the preparation of Northwest Africa: Seizing the Initiative in the Westby George F. Howe, the U.S. Army Center of Military History’s (CMH) official history volume on U.S. Army operations in North Africa, published in 1956. Robinett was the commander of Combat Command B, U.S. 1st Armored Division during the Battle of Kasserine Pass, but did not participate in the engagement at Sidi Bou Zid. His report is excerpted in a set of readings (pp. 103-120) provided as background material for a Kasserine Pass staff ride prepared by CMH. (Curiously, the account of the 15 February engagement at Sidi Bou Zid in Northwest Africa [pp. 419-422] does not reference Robinett’s study.)
Robinett’s report appeared to include an annotated copy of a topographical map labeled “approximate location of destroyed U.S. tanks (as surveyed three weeks later).” This suggests that the battlefield was surveyed in late March 1943, after U.S. forces had defeated the Germans and regained control of the area.
The report also included a version of the schematic diagram later reproduced by CMH. The notes on the map seem to indicate that the survey was the work of staff officers, perhaps at Robinett’s direction, possibly as part of an after-action report.
If anyone knows more about the origins of this bit of battlefield archaeology, I would love to know more about it. As far as I know, this assessment was unique, at least in the U.S. Army in World War II.
Gerard credited Trevor Dupuy and his colleagues at the Historical Evaluation Research Organization (HERO) with codifying “the military appropriation of the concept” of lethality, which was defined as: “the inherent capability of a given weapon to kill personnel or make materiel ineffective in a given period, where capability includes the factors of weapon range, rate of fire, accuracy, radius of effects, and battlefield mobility.”
It is gratifying for Gerard to attribute this to Dupuy and HERO, but some clarification is needed. The definition she quoted was, in fact, one provided to HERO for the purposes of a study sponsored by the Advanced Tactics Project (AVTAC) of the U.S. Army Combat Developments Command. The 1964 study report, Historical Trends Related to Weapon Lethality, provided the starting point for Dupuy’s subsequent theorizing about combat.
In his own works, Dupuy used a simpler definition of lethality:
“Lethality—the ability to injure and if possible to kill people.” [The Evolution of Weapons and Warfare (Indianapolis, IN: The Bobbs-Merrill Company, Inc., 1980), p. 286]
“All weapons have at least one common characteristic: lethality. This is the ability to injure and, if possible, to kill people.” [Attrition: Forecasting Battle Casualties and Equipment Losses in Modern War (Falls Church, VA: NOVA Publications, 1995), p. 25, which was drawn from earlier HERO reports].
He also used the terms lethality and firepower interchangeably in his writings. The wording of the original 1964 AVTAC definition tracks closely with the lethality scoring methodology Dupuy and his HERO colleagues developed for the study, known as the Theoretical Lethality Index/Operational Lethality Index (TLI/OLI). The original purpose of this construct was to permit some measurement of lethality by which weapons could be compared to each other (TLI), and to each other through history (OLI). It worked well enough that he incorporated it into his combat models, the Quantified Judgement Model (QJM) and Tactical Numerical Deterministic Model (TNDM).
An German Army A7V near the Somme on March 26, 1918 [forces.net] Operation Michael was the first of a series of German Army offensives on the Western Front in the spring of 1918. In late March, 74 German divisions employing infiltration tactics created a breach in a sector of the line held by the British Army. The Germans advanced up to 40 miles and captured over 75,000 British soldiers, but the ability of the British and French to redeploy reserves via rail halted the offensive in early April short of strategic success.
In response to my previous post on Trevor Dupuy’s verity regarding the importance of depth and reserves for successful defense, a commenter posed the following question: “Is the importance of reserves mainly in its own right, or to mitigate the advantages of attacker surprise?”
The importance of reserves to both attacker and defender is as a hedge against the circumstantial uncertainties of combat. Reserves allow attacking and defending commanders the chance to maintain or regain initiative in response to the outcomes of battle. The side that commits its last reserves before its opponent does concedes the initiative to the enemy, probably irrevocably.
In Trevor Dupuy’s theory of combat, the intrinsic superiority of the defensive posture (as per Clausewitz) is the corollary to the attacker’s inherent advantage in initiative. When combined with the combat multipliers of favorable terrain and prepared positions or fortifications, the combat power of a defending force is greatly enhanced. This permits a defending commander to reap the benefit of economy of force to create reserves. When arrayed in sufficient depth to prevent an attacker from engaging them, reserves grant flexibility of response to the defender. A linear defense or improperly placed reserves concede this benefit to the attacker at the outset, permitting the attacking commander to exploit initiative to mass superior combat power at a decisive point without reserves to interfere.
A defender’s reserves are certainly useful in mitigating attacker surprise, but in Dupuy’s theories and models, surprise is a combat multiplier available to both attacker and defender. As perhaps the most powerful combat multiplier available on the battlefield, surprise in the form of a well-timed counterattack by a defender can devastate an attacking force. Even an unexpected tactical wrinkle by a defender can yield effective surprise.
Today’s edition of TDI Friday Read is a roundup of posts by TDI President Christopher Lawrence exploring the details of tank combat between German and Soviet forces at the Battle of Kursk in 1943. The prevailing historical interpretation of Kursk is of the Soviets using their material and manpower superiority to blunt and then overwhelm the German offensive. This view is often buttressed by looking at the ratio of the numbers of tanks destroyed in combat. Chris takes a deeper look at the data, the differences in the ways “destroyed” tanks were counted and reported, and the differing philosophies between the German and Soviet armies regarding damaged tank recovery and repair. This yields a much more nuanced perspective on the character of tank combat at Kursk that does not necessarily align with the prevailing historical interpretations. Historians often discount detailed observational data on combat as irrelevant or too difficult to collect and interpret. We at TDI believe that with history, the devil is always in the details.
This list originated in response to a Twitter query discussing the history of post-World War II U.S. Army doctrine development. It is hardly exhaustive but it does include titles and resources that may not be widely known.
Jensen focused on the institutional processes shaping the Army’s continual post-war World War II efforts to reform its doctrine in response to changes in the character of modern warfare.
In an excellent overview of the evolution of operational thought through the 20th century, Naveh devoted two chapters to the Army’s transition to Active Defense in the 70s and then to AirLand Battle in the 80s.
There are several interesting monographs that are available online:
A really useful place to browse is the Army Command and General Staff College’s online Skelton Combined Arms Research Library (CARL). It is loaded with old manuals and student papers and theses addressing a wide variety of topics related to the nuts and bolts of doctrine.
Another good place to browse is the Defense Technical Information Center (DTIC), which is a huge digital library of government sponsored research. I recommend searches on publications by the Army’s defunct operations research organizations: Operations Research Office (ORO), Research Analysis Corporation (RAC), and the Special Operations Research Office (SORO). The Combat Operations Research Group (CORG), particularly a series of studies of Army force structure from squads to theater HQ’s by Virgil Ney. There is much more to find in DTIC.
Source: David A. Shlapak and Michael Johnson. Reinforcing Deterrence on NATO’s Eastern Flank: Wargaming the Defense of the Baltics. Santa Monica, CA: RAND Corporation, 2016.
[UPDATE] We had several readers recommend games they have used or would be suitable for simulating Multi-Domain Battle and Operations (MDB/MDO) concepts. These include several classic campaign-level board wargames:
Chris Lawrence recently looked at C-WAM and found that it uses a lot of traditional board wargaming elements, including methodologies for determining combat results, casualties, and breakpoints that have been found unable to replicate real-world outcomes (aka “The Base of Sand” problem).
What other wargames, models, and simulations are there being used out there? Are there any commercial wargames incorporating MDB/MDO elements into their gameplay? What methodologies are being used to portray MDB/MDO effects?
With the December 2018 update of the U.S. Army’s Multi-Domain Operations (MDO) concept, this seems like a good time to review the evolution of doctrinal thinking about it. We will start with the event that sparked the Army’s thinking about the subject: the 2014 rocket artillery barrage fired from Russian territory that devastated Ukrainian Army forces near the village of Zelenopillya. From there we will look at the evolution of Army thinking beginning with the initial draft of an operating concept for Multi-Domain Battle (MDB) in 2017. To conclude, we will re-up two articles expressing misgivings over the manner with which these doctrinal concepts are being developed, and the direction they are taking.
There are three versions of force ratio versus casualty exchange ratio rules, such as the three-to-one rule (3-to-1 rule), as it applies to casualties. The earliest version of the rule as it relates to casualties that we have been able to find comes from the 1958 version of the U.S. Army Maneuver Control manual, which states: “When opposing forces are in contact, casualties are assessed in inverse ratio to combat power. For friendly forces advancing with a combat power superiority of 5 to 1, losses to friendly forces will be about 1/5 of those suffered by the opposing force.”[1]
The RAND version of the rule (1992) states that: “the famous ‘3:1 rule ’, according to which the attacker and defender suffer equal fractional loss rates at a 3:1 force ratio the battle is in mixed terrain and the defender enjoys ‘prepared ’defenses…” [2]
Finally, there is a version of the rule that dates from the 1967 Maneuver Control manual that only applies to armor that shows:
As the RAND construct also applies to equipment losses, then this formulation is directly comparable to the RAND construct.
Therefore, we have three basic versions of the 3-to-1 rule as it applies to casualties and/or equipment losses. First, there is a rule that states that there is an even fractional loss ratio at 3-to-1 (the RAND version), Second, there is a rule that states that at 3-to-1, the attacker will suffer one-third the losses of the defender. And third, there is a rule that states that at 3-to-1, the attacker and defender will suffer the same losses as the defender. Furthermore, these examples are highly contradictory, with either the attacker suffering three times the losses of the defender, the attacker suffering the same losses as the defender, or the attacker suffering 1/3 the losses of the defender.
Therefore, what we will examine here is the relationship between force ratios and exchange ratios. In this case, we will first look at The Dupuy Institute’s Battles Database (BaDB), which covers 243 battles from 1600 to 1900. We will chart on the y-axis the force ratio as measured by a count of the number of people on each side of the forces deployed for battle. The force ratio is the number of attackers divided by the number of defenders. On the x-axis is the exchange ratio, which is a measured by a count of the number of people on each side who were killed, wounded, missing or captured during that battle. It does not include disease and non-battle injuries. Again, it is calculated by dividing the total attacker casualties by the total defender casualties. The results are provided below:
As can be seen, there are a few extreme outliers among these 243 data points. The most extreme, the Battle of Tippennuir (l Sep 1644), in which an English Royalist force under Montrose routed an attack by Scottish Covenanter militia, causing about 3,000 casualties to the Scots in exchange for a single (allegedly self-inflicted) casualty to the Royalists, was removed from the chart. This 3,000-to-1 loss ratio was deemed too great an outlier to be of value in the analysis.
As it is, the vast majority of cases are clumped down into the corner of the graph with only a few scattered data points outside of that clumping. If one did try to establish some form of curvilinear relationship, one would end up drawing a hyperbola. It is worthwhile to look inside that clump of data to see what it shows. Therefore, we will look at the graph truncated so as to show only force ratios at or below 20-to-1 and exchange rations at or below 20-to-1.
Again, the data remains clustered in one corner with the outlying data points again pointing to a hyperbola as the only real fitting curvilinear relationship. Let’s look at little deeper into the data by truncating the data on 6-to-1 for both force ratios and exchange ratios. As can be seen, if the RAND version of the 3-to-1 rule is correct, then the data should show at 3-to-1 force ratio a 3-to-1 casualty exchange ratio. There is only one data point that comes close to this out of the 243 points we examined.
If the FM 105-5 version of the rule as it applies to armor is correct, then the data should show that at 3-to-1 force ratio there is a 1-to-1 casualty exchange ratio, at a 4-to-1 force ratio a 1-to-2 casualty exchange ratio, and at a 5-to-1 force ratio a 1-to-3 casualty exchange ratio. Of course, there is no armor in these pre-WW I engagements, but again no such exchange pattern does appear.
If the 1958 version of the FM 105-5 rule as it applies to casualties is correct, then the data should show that at a 3-to-1 force ratio there is 0.33-to-1 casualty exchange ratio, at a 4-to-1 force ratio a .25-to-1 casualty exchange ratio, and at a 5-to-1 force ratio a 0.20-to-5 casualty exchange ratio. As can be seen, there is not much indication of this pattern, or for that matter any of the three patterns.
Still, such a construct may not be relevant to data before 1900. For example, Lanchester claimed in 1914 in Chapter V, “The Principal of Concentration,” of his book Aircraft in Warfare, that there is greater advantage to be gained in modern warfare from concentration of fire.[3] Therefore, we will tap our more modern Division-Level Engagement Database (DLEDB) of 675 engagements, of which 628 have force ratios and exchange ratios calculated for them. These 628 cases are then placed on a scattergram to see if we can detect any similar patterns.
Even though this data covers from 1904 to 1991, with the vast majority of the data coming from engagements after 1940, one again sees the same pattern as with the data from 1600-1900. If there is a curvilinear relationship, it is again a hyperbola. As before, it is useful to look into the mass of data clustered into the corner by truncating the force and exchange ratios at 20-to-1. This produces the following:
Again, one sees the data clustered in the corner, with any curvilinear relationship again being a hyperbola. A look at the data further truncated to a 10-to-1 force or exchange ratio does not yield anything more revealing.
And, if this data is truncated to show only 5-to-1 force ratio and exchange ratios, one again sees:
Again, this data appears to be mostly just noise, with no clear patterns here that support any of the three constructs. In the case of the RAND version of the 3-to-1 rule, there is again only one data point (out of 628) that is anywhere close to the crossover point (even fractional exchange rate) that RAND postulates. In fact, it almost looks like the data conspires to make sure it leaves a noticeable “hole” at that point. The other postulated versions of the 3-to-1 rules are also given no support in these charts.
While we can attempt to torture the data to find a better fit, or can try to argue that the patterns are obscured by various factors that have not been considered, we do not believe that such a clear pattern and relationship exists. More advanced mathematical methods may show such a pattern, but to date such attempts have not ferreted out these alleged patterns. For example, we refer the reader to Janice Fain’s article on Lanchester equations, The Dupuy Institute’s Capture Rate Study, Phase I & II, or any number of other studies that have looked at Lanchester.[4]
The fundamental problem is that there does not appear to be a direct cause and effect between force ratios and exchange ratios. It appears to be an indirect relationship in the sense that force ratios are one of several independent variables that determine the outcome of an engagement, and the nature of that outcome helps determines the casualties. As such, there is a more complex set of interrelationships that have not yet been fully explored in any study that we know of, although it is briefly addressed in our Capture Rate Study, Phase I & II.
[3] F. W. Lanchester, Aircraft in Warfare: The Dawn of the Fourth Arm (Lanchester Press Incorporated, Sunnyvale, Calif., 1995), 46-60. One notes that Lanchester provided no data to support these claims, but relied upon an intellectual argument based upon a gross misunderstanding of ancient warfare.
[Sgt. Meghan Berry, US Army/adapted by U.S. Army Modern War Institute]
The U.S. Army Training and Doctrine Command (TRADOC) released draft version 1.5 of its evolving Multi-Domain Operations (MDO) future operating concept last week. Entitled TRADOC Pamphlet 525-3-1, “The U.S. Army in Multi-Domain Operations 2028,” this iteration updates the initial Multi-Domain Battle (MDB) concept issued in October 2017.
According to U.S. Army Chief of Staff (and Chairman of the Joint Chiefs of Staff nominee) General Mark Milley, MDO Concept 1.5 is the first step in the doctrinal evolution. “It describes how U.S. Army forces, as part of the Joint Force, will militarily compete, penetrate, dis-integrate, and exploit our adversaries in the future.”
TRADOC Commander General Stuart Townsend summarized the draft concept thusly:
The U.S. Army in Multi-Domain Operations 2028 concept proposes a series of solutions to solve the problem of layered standoff. The central idea in solving this problem is the rapid and continuous integration of all domains of warfare to deter and prevail as we compete short of armed conflict. If deterrence fails, Army formations, operating as part of the Joint Force, penetrate and dis-integrate enemy anti-access and area denial systems;exploit the resulting freedom of maneuver to defeat enemy systems, formations and objectives and to achieve our own strategic objectives; and consolidate gains to force a return to competition on terms more favorable to the U.S., our allies and partners.
To achieve this, the Army must evolve our force, and our operations, around three core tenets. Calibrated force posture combines position and the ability to maneuver across strategic distances. Multi-domain formations possess the capacity, endurance and capability to access and employ capabilities across all domains to pose multiple and compounding dilemmas on the adversary. Convergence achieves the rapid and continuous integration of all domains across time, space and capabilities to overmatch the enemy. Underpinning these tenets are mission command and disciplined initiative at all warfighting echelons. (original emphasis)
For a look at the evolution of the Army and U.S. Marine Corps doctrinal thinking about multi-domain warfare since early 2017:
Today’s edition of TDI Friday Read is a roundup of posts by TDI President Christopher Lawrence exploring the details of tank combat between German and Soviet forces 
This list originated in response to a Twitter query discussing the history of post-World War II U.S. Army doctrine development. It is hardly exhaustive but it does include titles and resources that may not be widely known.
With the December 2018 update of the U.S. Army’s Multi-Domain Operations (MDO) concept, this seems like a good time to review the evolution of doctrinal thinking about it. We will start with the event that sparked the Army’s thinking about the subject: the 2014 rocket artillery barrage fired from Russian territory that devastated Ukrainian Army forces near the village of Zelenopillya. From there we will look at the evolution of Army thinking beginning with the initial draft of an operating concept for Multi-Domain Battle (MDB) in 2017. To conclude, we will re-up two articles expressing misgivings over the manner with which these doctrinal concepts are being developed, and the direction they are taking.
