A paratrooper from the French Foreign Legion (1er REP) with a captured fellagha during the Algerian War (1954-1962). [Via Pinterest]
Today’s edition of TDI Friday Read is a compilation of posts addressing the question of manpower and counterinsurgency. The first four posts summarize research on the question undertaken during the first decade of the 21st century, while the Afghan and Iraqi insurgencies were in full bloom. Despite different research questions and analytical methodologies, each of the studies concluded that there is a relationship between counterinsurgent manpower and counterinsurgency outcomes.
The fifth post addresses the U.S. Army’s lack of a formal methodology for calculating manpower requirements for counterinsurgencies and contingency operations.
John Conger recently reported in Defense One that the tax reform initiative championed by the Trump administration and Republican congressional leaders may torpedo an increase in the U.S. defense budget for 2018. Both the House and Senate have passed authorizations approving the Trump administration’s budget request for $574.5 billion in defense spending, which is $52 billion higher than the limit established by the Budget Control Act (BCA). However, the House and Senate also recently passed a concurrent 2018 budget resolution to facilitate passage of a tax reform bill that caps the defense budget at $522 billion as mandated by the BCA.
The House and Senate armed services committees continue to hammer out the terms of the 2018 defense authorization, which includes increases in troop strength and pay. These priorities could crowd out other spending requested by the services to meet strategic and modernization requirements if the budget remains capped. Congress also continues to resist the call by Secretary of Defense James Mattis to close unneeded bases and facilities, which could free spending for other needs. There is also little interest in reforming Defense Department business practices that allegedly waste $125 billion annually.
Congressional Republicans and Democrats were already headed toward a showdown over 2018 BCA limits on defense spending. Even before the tax reform push, several legislators predicted yet another year-long continuing resolution limiting government spending to the previous year’s levels. A bipartisan consensus existed among some armed services committee members that this would constitute “borderline legislative malpractice, particularly for the Department of Defense.”
Despite the ambitious timeline set by President Trump to pass a tax reform bill, the chances of a continuing resolution remain high. It also seems likely that any agreement to increase defense spending will be through the Overseas Contingency Operations budget, which is not subject to the BCA. Many in Congress agree with Democratic Representative Adam Smith that resorting to this approach is “a fiscal sleight of hand [that] would be bad governance and ‘hypocritical.’”
Are tax reform and increased defense spending incompatible? Stay tuned.
[SIGAR, Quarterly Report to Congress, 30 October 2017, p. 107]
While it is too soon to tell if the Trump Administration’s revised strategy in Afghanistan will make a difference, the recent report by the Special Inspector General for Afghanistan Reconstruction (SIGAR) to Congress documents the continued slow erosion of security in that country. Today’s edition of TDI Friday Read offers a selection of recent posts addressing some of the problems facing the U.S. counterinsurgent and stabilization missions there.
This weekend’s edition of TDI’s Friday Read is a collection of posts on the current state of U.S. airpower by guest contributor Geoffery Clark. The same factors changing the character of land warfare are changing the way conflict will be waged in the air. Clark’s posts highlight some of the way these changes are influencing current and future U.S. airpower plans and concepts.
The update is the result of the initial round of work between the U.S. Army and U.S. Air Force to redefine the scope of the multi-domain battlespace for the Joint Force. More work will be needed to refine the concept, but it shows remarkable cooperation in forging a common warfighting perspective between services long-noted for their independent thinking.
What difference can it make if those designing Multi-Domain Battle are acting on possibly the wrong threat diagnosis? Designing a solution for a misdiagnosed problem can result in the inculcation of a way of war unsuited for the wars of the future. One is reminded of the French Army during the interwar period. No one can accuse the French of not thinking seriously about war during these years, but, in the doctrine of the methodical battle, they got it wrong and misread the opportunities presented by mechanisation. There were many factors contributing to France’s defeat, but at their core was a misinterpretation of the art of the possible and a singular focus on a particular way of war. Shaping Multi-Domain Battle for the wrong problem may see the United States similarly sow the seeds for a military disaster that is avoidable.
He suggests that it would be wise for U.S. doctrine writers to take a more considered look at potential implications before venturing too far ahead with specific solutions.
Soldiers from Britain’s Royal Artillery train in a “virtual world” during Exercise Steel Sabre, 2015 [Sgt Si Longworth RLC (Phot)/MOD]
Military History and Validation of Combat Models
A Presentation at MORS Mini-Symposium on Validation, 16 Oct 1990
By Trevor N. Dupuy
In the operations research community there is some confusion as to the respective meanings of the words “validation” and “verification.” My definition of validation is as follows:
“To confirm or prove that the output or outputs of a model are consistent with the real-world functioning or operation of the process, procedure, or activity which the model is intended to represent or replicate.”
In this paper the word “validation” with respect to combat models is assumed to mean assurance that a model realistically and reliably represents the real world of combat. Or, in other words, given a set of inputs which reflect the anticipated forces and weapons in a combat encounter between two opponents under a given set of circumstances, the model is validated if we can demonstrate that its outputs are likely to represent what would actually happen in a real-world encounter between these forces under those circumstances
Thus, in this paper, the word “validation” has nothing to do with the correctness of computer code, or the apparent internal consistency or logic of relationships of model components, or with the soundness of the mathematical relationships or algorithms, or with satisfying the military judgment or experience of one individual.
True validation of combat models is not possible without testing them against modern historical combat experience. And so, in my opinion, a model is validated only when it will consistently replicate a number of military history battle outcomes in terms of: (a) Success-failure; (b) Attrition rates; and (c) Advance rates.
“Why,” you may ask, “use imprecise, doubtful, and outdated history to validate a modem, scientific process? Field tests, experiments, and field exercises can provide data that is often instrumented, and certainly more reliable than any historical data.”
I recognize that military history is imprecise; it is only an approximate, often biased and/or distorted, and frequently inconsistent reflection of what actually happened on historical battlefields. Records are contradictory. I also recognize that there is an element of chance or randomness in human combat which can produce different results in otherwise apparently identical circumstances. I further recognize that history is retrospective, telling us only what has happened in the past. It cannot predict, if only because combat in the future will be fought with different weapons and equipment than were used in historical combat.
Despite these undoubted problems, military history provides more, and more accurate information about the real world of combat, and how human beings behave and perform under varying circumstances of combat, than is possible to derive or compile from arty other source. Despite some discrepancies, patterns are unmistakable and consistent. There is always a logical explanation for any individual deviations from the patterns. Historical examples that are inconsistent, or that are counter-intuitive, must be viewed with suspicion as possibly being poor or false history.
Of course absolute prediction of a future event is practically impossible, although not necessarily so theoretically. Any speculations which we make from tests or experiments must have some basis in terms of projections from past experience.
Training or demonstration exercises, proving ground tests, field experiments, all lack the one most pervasive and most important component of combat: Fear in a lethal environment. There is no way in peacetime, or non-battlefield, exercises, test, or experiments to be sure that the results are consistent with what would have been the behavior or performance of individuals or units or formations facing hostile firepower on a real battlefield.
We know from the writings of the ancients (for instance Sun Tze—pronounced Sun Dzuh—and Thucydides) that have survived to this day that human nature has not changed since the dawn of history. The human factor the way in which humans respond to stimuli or circumstances is the most important basis for speculation and prediction. What about the “scientific” approach of those who insist that we cart have no confidence in the accuracy or reliability of historical data, that it is therefore unscientific, and therefore that it should be ignored? These people insist that only “scientific” data should be used in modeling.
In fact, every model is based upon fundamental assumptions that are intuitive and unprovable. The first step in the creation of a model is a step away from scientific reality in seeking a basis for an unreal representation of a real phenomenon. I have shown that the unreality is perpetuated when we use other imitations of reality as the basis for representing reality. History is less than perfect, but to ignore it, and to use only data that is bound to be wrong, assures that we will not be able to represent human behavior in real combat.
At the risk of repetition, and even of protesting too much, let me assure you that I am well aware of the shortcomings of military history:
The record which is available to us, which is history, only approximately reflects what actually happened. It is incomplete. It is often biased, it is often distorted. Even when it is accurate, it may be reflecting chance rather than normal processes. It is neither precise nor consistent. But, it provides more, and more accurate, information on the real world of battle than is available from the most thoroughly documented field exercises, proving ground less, or laboratory or field experiments.
Military history is imperfect. At best it reflects the actions and interactions of unpredictable human beings. We must always realize that a single historical example can be misleading for either of two reasons: (1) The data may be inaccurate, or (2) The data may be accurate, but untypical.
Nevertheless, history is indispensable. I repeat that the most pervasive characteristic of combat is fear in a lethal environment. For all of its imperfections, military history and only military history represents what happens under the environmental condition of fear.
Unfortunately, and somewhat unfairly, the reported findings of S.L.A. Marshall about human behavior in combat, which he reported in Men Against Fire, have been recently discounted by revisionist historians who assert that he never could have physically performed the research on which the book’s findings were supposedly based. This has raised doubts about Marshall’s assertion that 85% of infantry soldiers didn’t fire their weapons in combat in World War ll. That dramatic and surprising assertion was first challenged in a New Zealand study which found, on the basis of painstaking interviews, that most New Zealanders fired their weapons in combat. Thus, either Americans were different from New Zealanders, or Marshall was wrong. And now American historians have demonstrated that Marshall had had neither the time nor the opportunity to conduct his battlefield interviews which he claimed were the basis for his findings.
I knew Marshall, moderately well. I was fully as aware of his weaknesses as of his strengths. He was not a historian. I deplored the imprecision and lack of documentation in Men Against Fire. But the revisionist historians have underestimated the shrewd journalistic assessment capability of “SLAM” Marshall. His observations may not have been scientifically precise, but they were generally sound, and his assessment has been shared by many American infantry officers whose judgements l also respect. As to the New Zealand study, how many people will, after the war, admit that they didn’t fire their weapons?
Perhaps most important, however, in judging the assessments of SLAM Marshall, is a recent study by a highly-respected British operations research analyst, David Rowland. Using impeccable OR methods Rowland has demonstrated that Marshall’s assessment of the inefficient performance, or non-performance, of most soldiers in combat was essentially correct. An unclassified version of Rowland’s study, “Assessments of Combat Degradation,” appeared in the June 1986 issue of the Royal United Services Institution Journal.
Rowland was led to his investigations by the fact that soldier performance in field training exercises, using the British version of MILES technology, was not consistent with historical experience. Even after allowances for degradation from theoretical proving ground capability of weapons, defensive rifle fire almost invariably stopped any attack in these field trials. But history showed that attacks were often in fact, usually successful. He therefore began a study in which he made both imaginative and scientific use of historical data from over 100 small unit battles in the Boer War and the two World Wars. He demonstrated that when troops are under fire in actual combat, there is an additional degradation of performance by a factor ranging between 10 and 7. A degradation virtually of an order of magnitude! And this, mind you, on top of a comparable built-in degradation to allow for the difference between field conditions and proving ground conditions.
Not only does Rowland‘s study corroborate SLAM Marshall’s observations, it showed conclusively that field exercises, training competitions and demonstrations, give results so different from real battlefield performance as to render them useless for validation purposes.
Which brings us back to military history. For all of the imprecision, internal contradictions, and inaccuracies inherent in historical data, at worst the deviations are generally far less than a factor of 2.0. This is at least four times more reliable than field test or exercise results.
I do not believe that history can ever repeat itself. The conditions of an event at one time can never be precisely duplicated later. But, bolstered by the Rowland study, I am confident that history paraphrases itself.
If large bodies of historical data are compiled, the patterns are clear and unmistakable, even if slightly fuzzy around the edges. Behavior in accordance with this pattern is therefore typical. As we have already agreed, sometimes behavior can be different from the pattern, but we know that it is untypical, and we can then seek for the reason, which invariably can be discovered.
This permits what l call an actuarial approach to data analysis. We can never predict precisely what will happen under any circumstances. But the actuarial approach, with ample data, provides confidence that the patterns reveal what is to happen under those circumstances, even if the actual results in individual instances vary to some extent from this “norm” (to use the Soviet military historical expression.).
It is relatively easy to take into account the differences in performance resulting from new weapons and equipment. The characteristics of the historical weapons and the current (or projected) weapons can be readily compared, and adjustments made accordingly in the validation procedure.
In the early 1960s an effort was made at SHAPE Headquarters to test the ATLAS Model against World War II data for the German invasion of Western Europe in May, 1940. The first excursion had the Allies ending up on the Rhine River. This was apparently quite reasonable: the Allies substantially outnumbered the Germans, they had more tanks, and their tanks were better. However, despite these Allied advantages, the actual events in 1940 had not matched what ATLAS was now predicting. So the analysts did a little “fine tuning,” (a splendid term for fudging). Alter the so-called adjustments, they tried again, and ran another excursion. This time the model had the Allies ending up in Berlin. The analysts (may the Lord forgive them!) were quite satisfied with the ability of ATLAS to represent modem combat. (Or at least they said so.) Their official conclusion was that the historical example was worthless, since weapons and equipment had changed so much in the preceding 20 years!
As I demonstrated in my book, Options of Command, the problem was that the model was unable to represent the German strategy, or to reflect the relative combat effectiveness of the opponents. The analysts should have reached a different conclusion. ATLAS had failed validation because a model that cannot with reasonable faithfulness and consistency replicate historical combat experience, certainly will be unable validly to reflect current or future combat.
How then, do we account for what l have said about the fuzziness of patterns, and the fact that individual historical examples may not fit the patterns? I will give you my rules of thumb:
The battle outcome should reflect historical success-failure experience about four times out of five.
For attrition rates, the model average of five historical scenarios should be consistent with the historical average within a factor of about 1.5.
For the advance rates, the model average of five historical scenarios should be consistent with the historical average within a factor of about 1.5.
Just as the heavens are the laboratory of the astronomer, so military history is the laboratory of the soldier and the military operations research analyst. The scientific basis for both astronomy and military science is the recording of the movements and relationships of bodies, and then analysis of those movements. (In the one case the bodies are heavenly, in the other they are very terrestrial.)
I repeat: Military history is the laboratory of the soldier. Failure of the analyst to use this laboratory will doom him to live with the scientific equivalent of Ptolomean astronomy, whereas he could use the evidence available in his laboratory to progress to the military science equivalent of Copernican astronomy.
An Israeli tank unit crosses the Sinai, heading for the Suez Canal, during the 1973 Arab-Israeli War [Israeli Government Press Office/HistoryNet]
It has been noted throughout the history of human conflict that some armies have consistently fought more effectively on the battlefield than others. The armies of Sparta in ancient Greece, for example, have come to epitomize the warrior ideal in Western societies. Rome’s legions have acquired a similar legendary reputation. Within armies too, some units are known to be superior combatants than others. The U.S. 1st Infantry Division, the British Expeditionary Force of 1914, Japan’s Special Naval Landing Forces, the U.S. Marine Corps, the German 7th Panzer Division, and the Soviet Guards divisions are among the many superior fighting forces from history.
Trevor Dupuy found empirical substantiation of this in his analysis of historical combat data. He discovered that in 1943-1944 during World War II, after accounting for environmental and operational factors, the German Army consistently performed more effectively in ground combat than the U.S. and British armies. This advantage—measured in terms of casualty exchanges, terrain held or lost, and mission accomplishment—manifested whether the Germans were attacking or defending, or winning or losing. Dupuy observed that the Germans demonstrated an even more marked effectiveness in battle against the Soviet Army throughout the war.
He found the same disparity in battlefield effectiveness in combat data on the 1967 and 1973 Arab-Israeli wars. The Israeli Army performed uniformly better in ground combat over all of the Arab armies it faced in both conflicts, regardless of posture or outcome.
The clear and consistent patterns in the historical data led Dupuy to conclude that superior combat effectiveness on the battlefield was attributable to moral and behavioral (i.e. human) factors. Those factors he believed were the most important contributors to combat effectiveness were:
Leadership
Training or Experience
Morale, which may or may not include
Cohesion
Although the influence of human factors on combat effectiveness was identifiable and measurable in the aggregate, Dupuy was skeptical whether all of the individual moral and behavioral intangibles could be discreetly quantified. He thought this particularly true for a set of factors that also contributed to combat effectiveness, but were a blend of human and operational factors. These include:
Logistical effectiveness
Time and Space
Momentum
Technical Command, Control, Communications
Intelligence
Initiative
Chance
Dupuy grouped all of these intangibles together into a composite factor he designated as relative combat effectiveness value, or CEV. The CEV, along with environmental and operational factors (Vf), comprise the Circumstantial Variables of Combat, which when multiplied by force strength (S), determines the combat power (P) of a military force in Dupuy’s formulation.
P = S x Vf x CEV
Dupuy did not believe that CEVs were static values. As with human behavior, they vary somewhat from engagement to engagement. He did think that human factors were the most substantial of the combat variables. Therefore any model or theory of combat that failed to account for them would invariably be inaccurate.
Introduce students to the main facts about conflict. Apply theoretical and empirical economic tools to the study of conflict. Give students an appreciation of the main questions at the research frontier in the economic analysis of conflict. Draw some policy conclusions on how the international community should deal with conflict. Study data issues that arise when analysing conflict.
Dupuy was critical of combat models and simulations that failed to address these relationships. The prevailing approach to the design of combat modeling used by the U.S. Department of Defense is known as the aggregated, hierarchical, or “bottom-up” construct. Bottom-up models generally use the Lanchester equations, or some variation on them, to calculate combat outcomes between individual soldiers, tanks, airplanes, and ships. These results are then used as inputs for models representing warfare at the brigade/division level, the outputs of which are then fed into theater-level simulations. Many in the American military operations research community believe bottom-up models to be the most realistic method of modeling combat.
It is almost undeniable that there must be some interaction among and within the effects of physical as well as behavioral variable factors. I know of no way of measuring this. One thing that is reasonably certain is that the use of the bottom-up approach to model design and development cannot capture such interactions. (Most models in use today are bottom-up models, built up from one-on-one weapons interactions to many-on-many.) Presumably these interactions are captured in a top-down model derived from historical experience, of which there is at least one in existence [by which, Dupuy meant his own].
Dupuy was convinced that any model of combat that failed to incorporate human factors would invariably be inaccurate, which put him at odds with much of the American operations research community.
War does not consist merely of a number of duels. Duels, in fact, are only a very small—though integral—part of combat. Combat is a complex process involving interaction over time of many men and numerous weapons combined in a great number of different, and differently organized, units. This process cannot be understood completely by considering the theoretical interactions of individual men and weapons. Complete understanding requires knowing how to structure such interactions and fit them together. Learning how to structure these interactions must be based on scientific analysis of real combat data.[1]
While this unresolved debate went dormant some time ago, bottom-up models became the simulations of choice in Defense Department campaign planning and analysis. It should be noted, however, that the Defense Department disbanded its campaign-level modeling capabilities in 2011 because the use of the simulations in strategic analysis was criticized as “slow, manpower-intensive, opaque, difficult to explain because of its dependence on complex models, inflexible, and weak in dealing with uncertainty.”
One of the basic problems facing military commanders at all levels is deciding how to allocate available forces to accomplish desired objectives. A guiding concept in this sort of decision-making is economy of force, one of the fundamental and enduring principles of war. As defined in the 1954 edition of U.S. Army Field Manual FM 100-5, Field Service Regulations, Operations (which Trevor Dupuy believed contained the best listing of the principles):
Economy of Force
Minimum essential means must be employed at points other than that of decision. To devote means to unnecessary secondary efforts or to employ excessive means on required secondary efforts is to violate the principle of both mass and the objective. Limited attacks, the defensive, deception, or even retrograde action are used in noncritical areas to achieve mass in the critical area.
How do leaders determine the appropriate means for accomplishing a particular mission? The risk of failing to assign too few forces to a critical task is self-evident, but is it possible to allocate too many? Determining the appropriate means in battle has historically involved subjective calculations by commanders and their staff advisors of the relative combat power of friendly and enemy forces. Most often, it entails a rudimentary numerical comparison of numbers of troops and weapons and estimates of the influence of environmental and operational factors. An exemplar of this is the so-called “3-1 rule,” which holds that an attacking force must achieve a three to one superiority in order to defeat a defending force.
Through detailed analysis of combat data from World War II and the 1967 and 1973 Arab-Israeli wars, Dupuy determined that combat appears subject to a law of diminishing returns and that it is indeed possible to over-allocate forces to a mission.[1] By comparing the theoretical outcomes of combat engagements with the actual results, Dupuy discovered that a force with a combat power advantage greater than double that of its adversary seldom achieved proportionally better results than a 2-1 advantage. A combat power superiority of 3 or 4 to 1 rarely yielded additional benefit when measured in terms of casualty rates, ground gained or lost, and mission accomplishment.
Dupuy also found that attackers sometimes gained marginal benefits from combat power advantages greater than 2-1, though less proportionally and economically than the numbers of forces would suggest. Defenders, however, received no benefit at all from a combat power advantage beyond 2-1.
Two human factors contributed to this apparent force limitation, Dupuy believed, Clausewitzian friction and breakpoints. As described in a previous post, friction accumulates on the battlefield through the innumerable human interactions between soldiers, degrading combat performance. This phenomenon increases as the number of soldiers increases.
A breakpoint represents a change of combat posture by a unit on the battlefield, for example, from attack to defense, or from defense to withdrawal. A voluntary breakpoint occurs due to mission accomplishment or a commander’s order. An involuntary breakpoint happens when a unit spontaneously ceases an attack, withdraws without orders, or breaks and routs. Involuntary breakpoints occur for a variety of reasons (though contrary to popular wisdom, seldom due to casualties). Soldiers are not automatons and will rarely fight to the death.
As Dupuy summarized,
It is obvious that the law of diminishing returns applies to combat. The old military adage that the greater the superiority the better, is not necessarily true. In the interests of economy of force, it appears to be unnecessary, and not really cost-effective, to build up a combat power superiority greater than two-to-one. (Note that this is not the same as a numerical superiority of two-to-one.)[2] Of course, to take advantage of this phenomenon, it is essential that a commander be satisfied that he has a reliable basis for calculating relative combat power. This requires an ability to understand and use “combat multipliers” with greater precision than permitted by U.S. Army doctrine today.[3] [Emphasis added.]
John Conger recently reported in Defense One
The U.S. Army Training and Doctrine Command has released a revised draft version of its 
Below is an aggregated list of links to Dr. 
