In 1931, Lieutenant Colonel (later Brigadier General) Love, then a Medical Corps physician in the U.S. Army Medical Field Services School, published a study of American casualty data in the recent Great War, titled “War Casualties.”[1] This study was likely the source for tables used for casualty estimation by the U.S. Army through 1944.[2]
Love’s research was likely the basis for rate tables for calculating casualties that first appeared in the 1932 edition of the War Department’s Staff Officer’s Field Manual.[3]
Battle Casualties, including Killed, in Percent of Unit Strength, Staff Officer’s Field Manual (1932).
The 1932 Staff Officer’s Field Manual estimation methodology reflected Love’s sophisticated understanding of the factors influencing combat casualty rates. It showed that both the resistance and combat strength (and all of the factors that comprised it) of the enemy, as well as the equipment and state of training and discipline of the friendly troops had to be taken into consideration. The text accompanying the tables pointed out that loss rates in small units could be quite high and variable over time, and that larger formations took fewer casualties as a fraction of overall strength, and that their rates tended to become more constant over time. Casualties were not distributed evenly, but concentrated most heavily among the combat arms, and in the front-line infantry in particular. Attackers usually suffered higher loss rates than defenders. Other factors to be accounted for included the character of the terrain, the relative amount of artillery on each side, and the employment of gas.
The 1941 iteration of the Staff Officer’s Field Manual, now designated Field Manual (FM) 101-10[4], provided two methods for estimating battle casualties. It included the original 1932 Battle Casualties table, but the associated text no longer included the section outlining factors to be considered in calculating loss rates. This passage was moved to a note appended to a new table showing the distribution of casualties among the combat arms.
Rather confusingly, FM 101-10 (1941) presented a second table, Estimated Daily Losses in Campaign of Personnel, Dead and Evacuated, Per 1,000 of Actual Strength. It included rates for front line regiments and divisions, corps and army units, reserves, and attached cavalry. The rates were broken down by posture and tactical mission.
Estimated Daily Losses in Campaign of Personnel, Dead and Evacuated, Per 1,000 of Actual Strength, FM 101-10 (1941)
The source for this table is unknown, nor the method by which it was derived. No explanatory text accompanied it, but a footnote stated that “this table is intended primarily for use in school work and in field exercises.” The rates in it were weighted toward the upper range of the figures provided in the 1932 Battle Casualties table.
The October 1943 edition of FM 101-10 contained no significant changes from the 1941 version, except for the caveat that the 1932 Battle Casualties table “may or may not prove correct when applied to the present conflict.”
The October 1944 version of FM 101-10 incorporated data obtained from World War II experience.[5] While it also noted that the 1932 Battle Casualties table might not be applicable, the experiences of the U.S. II Corps in North Africa and one division in Italy were found to be in agreement with the table’s division and corps loss rates.
FM 101-10 (1944) included another new table, Estimate of Battle Losses for a Front-Line Division (in % of Actual Strength), meaning that it now provided three distinct methods for estimating battle casualties.
Estimate of Battle Losses for a Front-Line Division (in % of Actual Strength), FM 101-10 (1944)
Like the 1941 Estimated Daily Losses in Campaign table, the sources for this new table were not provided, and the text contained no guidance as to how or when it should be used. The rates it contained fell roughly within the span for daily rates for severe (6-8%) to maximum (12%) combat listed in the 1932 Battle Casualty table, but would produce vastly higher overall rates if applied consistently, much higher than the 1932 table’s 1% daily average.
FM 101-10 (1944) included a table showing the distribution of losses by branch for the theater based on experience to that date, except for combat in the Philippine Islands. The new chart was used in conjunction with the 1944 Estimate of Battle Losses for a Front-Line Division table to determine daily casualty distribution.
Distribution of Battle Losses–Theater of Operations, FM 101-10 (1944)
The final World War II version of FM 101-10 issued in August 1945[6] contained no new casualty rate tables, nor any revisions to the existing figures. It did finally effectively invalidate the 1932 Battle Casualties table by noting that “the following table has been developed from American experience in active operations and, of course, may not be applicable to a particular situation.” (original emphasis)
NOTES
[1] Albert G. Love, War Casualties, The Army Medical Bulletin, No. 24, (Carlisle Barracks, PA: 1931)
[2] This post is adapted from TDI, Casualty Estimation Methodologies Study, Interim Report (May 2005) (Altarum) (pp. 314-317).
[3] U.S. War Department, Staff Officer’s Field Manual, Part Two: Technical and Logistical Data (Government Printing Office, Washington, D.C., 1932)
[4] U.S. War Department, FM 101-10, Staff Officer’s Field Manual: Organization, Technical and Logistical Data (Washington, D.C., June 15, 1941)
[5] U.S. War Department, FM 101-10, Staff Officer’s Field Manual: Organization, Technical and Logistical Data (Washington, D.C., October 12, 1944)
[6] U.S. War Department, FM 101-10 Staff Officer’s Field Manual: Organization, Technical and Logistical Data (Washington, D.C., August 1, 1945)
Stretcher bearers of the East Surrey Regiment, with a Churchill tank of the North Irish Horse in the background, during the attack on Longstop Hill, Tunisia, 23 April 1943. [Imperial War Museum/Wikimedia]
British Army staff officers during World War II and the 1950s used a set of look-up tables which listed expected monthly losses in percentage of strength for various arms under various combat conditions. The origin of the tables is not known, but they were officially updated twice, in 1942 by a committee chaired by Major General Evett, and in 1951-1955 by the Army Operations Research Group (AORG).[2]
The methodology was based on staff predictions of one of three levels of operational activity, “Intense,” “Normal,” and “Quiet.” These could be applied to an entire theater, or to individual divisions. The three levels were defined the same way for both the Evett Committee and AORG rates:
The rates were broken down by arm and rank, and included battle and nonbattle casualties.
Rates of Personnel Wastage Including Both Battle and Non-battle Casualties According to the Evett Committee of 1942. (Percent per 30 days).
The Evett Committee rates were criticized during and after the war. After British forces suffered twice the anticipated casualties at Anzio, the British 21st Army Group applied a “double intense rate” which was twice the Evett Committee figure and intended to apply to assaults. When this led to overestimates of casualties in Normandy, the double intense rate was discarded.
From 1951 to 1955, AORG undertook a study of casualty rates in World War II. Its analysis was based on casualty data from the following campaigns:
Northwest Europe, 1944
6-30 June – Beachhead offensive
1 July-1 September – Containment and breakout
1 October-30 December – Semi-static phase
9 February to 6 May – Rhine crossing and final phase
Italy, 1944
January to December – Fighting a relatively equal enemy in difficult country. Warfare often static.
January to February (Anzio) – Beachhead held against severe and well-conducted enemy counter-attacks.
North Africa, 1943
14 March-13 May – final assault
Northwest Europe, 1940
10 May-2 June – Withdrawal of BEF
Burma, 1944-45
From the first four cases, the AORG study calculated two sets of battle casualty rates as percentage of strength per 30 days. “Overall” rates included KIA, WIA, C/MIA. “Apparent rates” included these categories but subtracted troops returning to duty. AORG recommended that “overall” rates be used for the first three months of a campaign.
The Burma campaign data was evaluated differently. The analysts defined a “force wastage” category which included KIA, C/MIA, evacuees from outside the force operating area and base hospitals, and DNBI deaths. “Dead wastage” included KIA, C/MIA, DNBI dead, and those discharged from the Army as a result of injuries.
The AORG study concluded that the Evett Committee underestimated intense loss rates for infantry and armor during periods of very hard fighting and overestimated casualty rates for other arms. It recommended that if only one brigade in a division was engaged, two-thirds of the intense rate should be applied, if two brigades were engaged the intense rate should be applied, and if all brigades were engaged then the intense rate should be doubled. It also recommended that 2% extra casualties per month should be added to all the rates for all activities should the forces encounter heavy enemy air activity.[1]
The AORG study rates were as follows:
Recommended AORG Rates of Personnel Wastage. (Percent per 30 days).
If anyone has further details on the origins and activities of the Evett Committee and AORG, we would be very interested in finding out more on this subject.
NOTES
[1] This post is adapted from The Dupuy Institute, Casualty Estimation Methodologies Study, Interim Report (May 2005) (Altarum) (pp. 51-53).
[2] Rowland Goodman and Hugh Richardson. “Casualty Estimation in Open and Guerrilla Warfare.” (London: Directorate of Science (Land), U.K. Ministry of Defence, June 1995.), Appendix A.
Technology and the Human Factor in War by Trevor N. Dupuy
The Debate
It has become evident to many military theorists that technology has become increasingly important in war. In fact (even though many soldiers would not like to admit it) most such theorists believe that technology has actually reduced the significance of the human factor in war, In other words, the more advanced our military technology, these “technocrats” believe, the less we need to worry about the professional capability and competence of generals, admirals, soldiers, sailors, and airmen.
The technocrats believe that the results of the Kuwait, or Gulf, War of 1991 have confirmed their conviction. They cite the contribution to those results of the U.N. (mainly U.S.) command of the air, stealth aircraft, sophisticated guided missiles, and general electronic superiority, They believe that it was technology which simply made irrelevant the recent combat experience of the Iraqis in their long war with Iran.
Yet there are a few humanist military theorists who believe that the technocrats have totally misread the lessons of this century‘s wars! They agree that, while technology was important in the overwhelming U.N. victory, the principal reason for the tremendous margin of U.N. superiority was the better training, skill, and dedication of U.N. forces (again, mainly U.S.).
And so the debate rests. Both sides believe that the result of the Kuwait War favors their point of view, Nevertheless, an objective assessment of the literature in professional military journals, of doctrinal trends in the U.S. services, and (above all) of trends in the U.S. defense budget, suggest that the technocrats have stronger arguments than the humanists—or at least have been more convincing in presenting their arguments.
I suggest, however, that a completely impartial comparison of the Kuwait War results with those of other recent wars, and with some of the phenomena of World War II, shows that the humanists should not yet concede the debate.
I am a humanist, who is also convinced that technology is as important today in war as it ever was (and it has always been important), and that any national or military leader who neglects military technology does so to his peril and that of his country, But, paradoxically, perhaps to an extent even greater than ever before, the quality of military men is what wins wars and preserves nations.
To elevate the debate beyond generalities, and demonstrate convincingly that the human factor is at least as important as technology in war, I shall review eight instances in this past century when a military force has been successful because of the quality if its people, even though the other side was at least equal or superior in the technological sophistication of its weapons. The examples I shall use are:
Germany vs. the USSR in World War II
Germany vs. the West in World War II
Israel vs. Arabs in 1948, 1956, 1967, 1973 and 1982
The Vietnam War, 1965-1973
Britain vs. Argentina in the Falklands 1982
South Africans vs. Angolans and Cubans, 1987-88
The U.S. vs. Iraq, 1991
The demonstration will be based upon a marshaling of historical facts, then analyzing those facts by means of a little simple arithmetic.
Relative Combat Effectiveness Value (CEV)
The purpose of the arithmetic is to calculate relative combat effectiveness values (CEVs) of two opposing military forces. Let me digress to set up the arithmetic. Although some people who hail from south of the Mason-Dixon Line may be reluctant to accept the fact, statistics prove that the fighting quality of Northern soldiers and Southern soldiers was virtually equal in the American Civil War. (I invite those who might disagree to look at Livermore’s Numbers and Losses in the Civil War). That assumption of equality of the opposing troop quality in the Civil War enables me to assert that the successful side in every important battle in the Civil War was successful either because of numerical superiority or superior generalship. Three of Lee’s battles make the point:
Despite being outnumbered, Lee won at Antietam. (Though Antietam is sometimes claimed as a Union victory, Lee, the defender, held the battlefield; McClellan, the attacker, was repulsed.) The main reason for Lee’s success was that on a scale of leadership his generalship was worth 10, while McClellan was barely a 6.
Despite being outnumbered, Lee won at Chancellorsville because he was a 10 to Hooker’s 5.
Lee lost at Gettysburg mainly because he was outnumbered. Also relevant: Meade did not lose his nerve (like McClellan and Hooker) with generalship worth 8 to match Lee’s 8.
Let me use Antietam to show the arithmetic involved in those simple analyses of a rather complex subject:
The numerical strength of McClellan’s army was 89,000; Lee’s army was only 39,000 strong, but had the multiplier benefit of defensive posture. This enables us to calculate the theoretical combat power ratio of the Union Army to the Confederate Army as 1.4:1.0. In other words, with substantial preponderance of force, the Union Army should have been successful. (The combat power ratio of Confederates to Northerners, of course, was the reciprocal, or 0.71:1.04)
However, Lee held the battlefield, and a calculation of the actual combat power ratio of the two sides (based on accomplishment of mission, gaining or holding ground, and casualties) was a scant, but clear cut: 1.16:1.0 in favor of the Confederates. A ratio of the actual combat power ratio of the Confederate/Union armies (1.16) to their theoretical combat power (0.71) gives us a value of 1.63. This is the relative combat effectiveness of the Lee’s army to McClellan’s army on that bloody day. But, if we agree that the quality of the troops was the same, then the differential must essentially be in the quality of the opposing generals. Thus, Lee was a 10 to McClellan‘s 6.
The simple arithmetic equation[1] on which the above analysis was based is as follows:
CEV = (R/R)/(P/P)
When:
CEV is relative Combat Effectiveness Value
R/R is the actual combat power ratio
P/P is the theoretical combat power ratio.
At Antietam the equation was: 1.63 = 1.16/0.71.
We’ll be revisiting that equation in connection with each of our examples of the relative importance of technology and human factors.
Air Power and Technology
However, one more digression is required before we look at the examples. Air power was important in all eight of the 20th Century examples listed above. Offhand it would seem that the exercise of air superiority by one side or the other is a manifestation of technological superiority. Nevertheless, there are a few examples of an air force gaining air superiority with equivalent, or even inferior aircraft (in quality or numbers) because of the skill of the pilots.
However, the instances of such a phenomenon are rare. It can be safely asserted that, in the examples used in the following comparisons, the ability to exercise air superiority was essentially a technological superiority (even though in some instances it was magnified by human quality superiority). The one possible exception might be the Eastern Front in World War II, where a slight German technological superiority in the air was offset by larger numbers of Soviet aircraft, thanks in large part to Lend-Lease assistance from the United States and Great Britain.
The Battle of Kursk, 5-18 July, 1943
Following the surrender of the German Sixth Army at Stalingrad, on 2 February, 1943, the Soviets mounted a major winter offensive in south-central Russia and Ukraine which reconquered large areas which the Germans had overrun in 1941 and 1942. A brilliant counteroffensive by German Marshal Erich von Manstein‘s Army Group South halted the Soviet advance, and recaptured the city of Kharkov in mid-March. The end of these operations left the Soviets holding a huge bulge, or salient, jutting westward around the Russian city of Kursk, northwest of Kharkov.
The Germans promptly prepared a new offensive to cut off the Kursk salient, The Soviets energetically built field fortifications to defend the salient against expected German attacks. The German plan was for simultaneous offensives against the northern and southern shoulders of the base of the Kursk salient, Field Marshal Gunther von K1uge’s Army Group Center, would drive south from the vicinity of Orel, while Manstein’s Army Group South pushed north from the Kharkov area, The offensive was originally scheduled for early May, but postponements by Hitler, to equip his forces with new tanks, delayed the operation for two months, The Soviets took advantage of the delays to further improve their already formidable defenses.
The German attacks finally began on 5 July. In the north General Walter Model’s German Ninth Army was soon halted by Marshal Konstantin Rokossovski’s Army Group Center. In the south, however, German General Hermann Hoth’s Fourth Panzer Army and a provisional army commanded by General Werner Kempf, were more successful against the Voronezh Army Group of General Nikolai Vatutin. For more than a week the XLVIII Panzer Corps advanced steadily toward Oboyan and Kursk through the most heavily fortified region since the Western Front of 1918. While the Germans suffered severe casualties, they inflicted horrible losses on the defending Soviets. Advancing similarly further east, the II SS Panzer Corps, in the largest tank battle in history, repulsed a vigorous Soviet armored counterattack at Prokhorovka on July 12-13, but was unable to continue to advance.
The principal reason for the German halt was the fact that the Soviets had thrown into the battle General Ivan Konev’s Steppe Army Group, which had been in reserve. The exhausted, heavily outnumbered Germans had no comparable reserves to commit to reinvigorate their offensive.
A comparison of forces and losses of the Soviet Voronezh Army Group and German Army Group South on the south face of the Kursk Salient is shown below. The strengths are averages over the 12 days of the battle, taking into consideration initial strengths, losses, and reinforcements.
A comparison of the casualty tradeoff can be found by dividing Soviet casualties by German strength, and German losses by Soviet strength. On that basis, 100 Germans inflicted 5.8 casualties per day on the Soviets, while 100 Soviets inflicted 1.2 casualties per day on the Germans, a tradeoff of 4.9 to 1.0
The statistics for the 8-day offensive of the German XLVIII Panzer Corps toward Oboyan are shown below. Also shown is the relative combat effectiveness value (CEV) of Germans and Soviets, as calculated by the TNDM. As was the case for the Battle of Antietam, this is derived from a mathematical comparison of the theoretical combat power ratio of the two forces (simply considering numbers and weapons characteristics), and the actual combat power ratios reflected by the battle results:
The calculated CEVs suggest that 100 German troops were the combat equivalent of 240 Soviet troops, comparably equipped. The casualty tradeoff in this battle shows that 100 Germans inflicted 5.15 casualties per day on the Soviets, while 100 Soviets inflicted 1.11 casualties per day on the Germans, a tradeoff of4.64. It is a rule of thumb that the casualty tradeoff is usually about the square of the CEV.
A similar comparison can be made of the two-day battle of Prokhorovka. Soviet accounts of that battle have claimed this as a great victory by the Soviet Fifth Guards Tank Army over the German II SS Panzer Corps. In fact, since the German advance was halted, the outcome was close to a draw, but with the advantage clearly in favor of the Germans.
The casualty tradeoff shows that 100 Germans inflicted 7.7 casualties per on the Soviets, while 100 Soviets inflicted 1.0 casualties per day on the Germans, for a tradeoff value of 7.7.
When the German offensive began, they had a slight degree of local air superiority. This was soon reversed by German and Soviet shifts of air elements, and during most of the offensive, the Soviets had a slender margin of air superiority. In terms of technology, the Germans probably had a slight overall advantage. However, the Soviets had more tanks and, furthermore, their T-34 was superior to any tank the Germans had available at the time. The CEV calculations demonstrate that the Germans had a great qualitative superiority over the Russians, despite near-equality in technology, and despite Soviet air superiority. The Germans lost the battle, but only because they were overwhelmed by Soviet numbers.
German Performance, Western Europe, 1943-1945
Beginning with operations between Salerno and Naples in September, 1943, through engagements in the closing days of the Battle of the Bulge in January, 1945, the pattern of German performance against the Western Allies was consistent. Some German units were better than others, and a few Allied units were as good as the best of the Germans. But on the average, German performance, as measured by CEV and casualty tradeoff, was better than the Western allies by a CEV factor averaging about 1.2, and a casualty tradeoff factor averaging about 1.5. Listed below are ten engagements from Italy and Northwest Europe during that 1944.
Technologically, German forces and those of the Western Allies were comparable. The Germans had a higher proportion of armored combat vehicles, and their best tanks were considerably better than the best American and British tanks, but the advantages were at least offset by the greater quantity of Allied armor, and greater sophistication of much of the Allied equipment. The Allies were increasingly able to achieve and maintain air superiority during this period of slightly less than two years.
The combination of vast superiority in numbers of troops and equipment, and in increasing Allied air superiority, enabled the Allies to fight their way slowly up the Italian boot, and between June and December, 1944, to drive from the Normandy beaches to the frontier of Germany. Yet the presence or absence of Allied air support made little difference in terms of either CEVs or casualty tradeoff values. Despite the defeats inflicted on them by the numerically superior Allies during the latter part of 1944, in December the Germans were able to mount a major offensive that nearly destroyed an American army corps, and threatened to drive at least a portion of the Allied armies into the sea.
Clearly, in their battles against the Soviets and the Western Allies, the Germans demonstrated that quality of combat troops was able consistently to overcome Allied technological and air superiority. It was Allied numbers, not technology, that defeated the quantitatively superior Germans.
The Six-Day War, 1967
The remarkable Israeli victories over far more numerous Arab opponents—Egyptian, Jordanian, and Syrian—in June, 1967 revealed an Israeli combat superiority that had not been suspected in the United States, the Soviet Union or Western Europe. This superiority was equally awesome on the ground as in the air. (By beginning the war with a surprise attack which almost wiped out the Egyptian Air Force, the Israelis avoided a serious contest with the one Arab air force large enough, and possibly effective enough, to challenge them.) The results of the three brief campaigns are summarized in the table below:
It should be noted that some Israelis who fought against the Egyptians and Jordanians also fought against the Syrians. Thus, the overall Arab numerical superiority was greater than would be suggested by adding the above strength figures, and was approximately 328,000 to 200,000.
It should also be noted that the technological sophistication of the Israeli and Arab ground forces was comparable. The only significant technological advantage of the Israelis was their unchallenged command of the air. (In terms of battle outcomes, it was irrelevant how they had achieved air superiority.) In fact this was a very significant advantage, the full import of which would not be realized until the next Arab-Israeli war.
The results of the Six Day War do not provide an unequivocal basis for determining the relative importance of human factors and technological superiority (as evidenced in the air). Clearly a major factor in the Israeli victories was the superior performance of their ground forces due mainly to human factors. At least as important in those victories was Israeli command of the air, in which both technology and human factors both played a part.
The October War, 1973
A better basis for comparing the relative importance of human factors and technology is provided by the results of the October War of 1973 (known to Arabs as the War of Ramadan, and to Israelis as the Yom Kippur War). In this war the Israeli unquestioned superiority in the air was largely offset by the Arabs possession of highly sophisticated Soviet air defense weapons.
One important lesson of this war was a reassessment of Israeli contempt for the fighting quality of Arab ground forces (which had stemmed from the ease with which they had won their ground victories in 1967). When Arab ground troops were protected from Israeli air superiority by their air defense weapons, they fought well and bravely, demonstrating that Israeli control of the air had been even more significant in 1967 than anyone had then recognized.
It should be noted that the total Arab (and Israeli) forces are those shown in the first two comparisons, above. A Jordanian brigade and two Iraqi divisions formed relatively minor elements of the forces under Syrian command (although their presence on the ground was significant in enabling the Syrians to maintain a defensive line when the Israelis threatened a breakthrough around 20 October). For the comparison of Jordanians and Iraqis the total strength is the total of the forces in the battles (two each) on which these comparisons are based.
One other thing to note is how the Israelis, possibly unconsciously, confirmed that validity of their CEVs with respect to Egyptians and Syrians by the numerical strengths of their deployments to the two fronts. Since the war ended up in a virtual stalemate on both fronts, the overall strength figures suggest rough equivalence of combat capability.
The CEV values shown in the above table are very significant in relation to the debate about human factors and technology, There was little if anything to choose between the technological sophistication of the two sides. The Arabs had more tanks than the Israelis, but (as Israeli General Avraham Adan once told the author) there was little difference in the quality of the tanks. The Israelis again had command of the air, but this was neutralized immediately over the battlefields by the Soviet air defense equipment effectively manned by the Arabs. Thus, while technology was of the utmost importance to both sides, enabling each side to prevent the enemy from gaining a significant advantage, the true determinant of battlefield outcomes was the fighting quality of the troops, And, while the Arabs fought bravely, the Israelis fought much more effectively. Human factors made the difference.
Israeli Invasion of Lebanon, 1982
In terms of the debate about the relative importance of human factors and technology, there are two significant aspects to this small war, in which Syrians forces and PLO guerrillas were the Arab participants. In the first place, the Israelis showed that their air technology was superior to the Syrian air defense technology, As a result, they regained complete control of the skies over the battlefields. Secondly, it provides an opportunity to include a highly relevant quotation.
The statistical comparison shows the results of the two major battles fought between Syrians and Israelis:
In assessing the above statistics, a quotation from the Israeli Chief of Staff, General Rafael Eytan, is relevant.
In late 1982 a group of retired American generals visited Israel and the battlefields in Lebanon. Just before they left for home, they had a meeting with General Eytan. One of the American generals asked Eytan the following question: “Since the Syrians were equipped with Soviet weapons, and your troops were equipped with American (or American-type) weapons, isn’t the overwhelming Israeli victory an indication of the superiority of American weapons technology over Soviet weapons technology?”
Eytan’s reply was classic: “If we had had their weapons, and they had had ours, the result would have been absolutely the same.”
One need not question how the Israeli Chief of Staff assessed the relative importance of the technology and human factors.
Falkland Islands War, 1982
It is difficult to get reliable data on the Falkland Islands War of 1982. Furthermore, the author of this article had not undertaken the kind of detailed analysis of such data as is available. However, it is evident from the information that is available about that war that its results were consistent with those of the other examples examined in this article.
The total strength of Argentine forces in the Falklands at the time of the British counter-invasion was slightly more than 13,000. The British appear to have landed close to 6,400 troops, although it may have been fewer. In any event, it is evident that not more than 50% of the total forces available to both sides were actually committed to battle. The Argentine surrender came 27 days after the British landings, but there were probably no more than six days of actual combat. During these battles the British performed admirably, the Argentinians performed miserably. (Save for their Air Force, which seems to have fought with considerable gallantry and effectiveness, at the extreme limit of its range.) The British CEV in ground combat was probably between 2.5 and 4.0. The statistics were at least close to those presented below:
It is evident from published sources that the British had no technological advantage over the Argentinians; thus the one-sided results of the ground battles were due entirely to British skill (derived from training and doctrine) and determination.
South African Operations in Angola, 1987-1988
Neither the political reasons for, nor political results of, the South African military interventions in Angola in the 1970s, and again in the late 1980s, need concern us in our consideration of the relative significance of technology and of human factors. The combat results of those interventions, particularly in 1987-1988 are, however, very relevant.
The operations between elements of the South African Defense Force (SADF) and forces of the Popular Movement for the Liberation of Angola (FAPLA) took place in southeast Angola, generally in the region east of the city of Cuito-Cuanavale. Operating with the SADF units were a few small units of Jonas Savimbi’s National Union for the Total Independence of Angola (UNITA). To provide air support to the SADF and UNITA ground forces, it would have been necessary for the South Africans to establish air bases either in Botswana, Southwest Africa (Namibia), or in Angola itself. For reasons that were largely political, they decided not to do that, and thus operated under conditions of FAPLA air supremacy. This led them, despite terrain generally unsuited for armored warfare, to use a high proportion of armored vehicles (mostly light armored cars) to provide their ground troops with some protection from air attack.
Summarized below are the results of three battles east of Cuito-Cuanavale in late 1987 and early 1988. Included with FAPLA forces are a few Cubans (mostly in armored units); included with the SADF forces are a few UNITA units (all infantry).
FAPLA had complete command of air, and substantial numbers of MiG-21 and MiG-23 sorties were flown against the South Africans in all of these battles. This technological superiority was probably partly offset by greater South African EW (electronic warfare) capability. The ability of the South Africans to operate effectively despite hostile air superiority was reminiscent of that of the Germans in World War II. It was a further demonstration that, no matter how important technology may be, the fighting quality of the troops is even more important.
The tank figures include armored cars. In the first of the three battles considered, FAPLA had by far the more powerful and more numerous medium tanks (20 to 0). In the other two, SADF had a slight or significant advantage in medium tank numbers and quality. But it didn’t seem to make much difference in the outcomes.
Kuwait War, 1991
The previous seven examples permit us to examine the results of Kuwait (or Second Gulf) War with more objectivity than might otherwise have possible. First, let’s look at the statistics. Note that the comparison shown below is for four days of ground combat, February 24-28, and shows only operations of U.S. forces against the Iraqis.
There can be no question that the single most important contribution to the overwhelming victory of U.S. and other U.N. forces was the air war that preceded, and accompanied, the ground operations. But two comments are in order. The air war alone could not have forced the Iraqis to surrender. On the other hand, it is evident that, even without the air war, U.S. forces would have readily overwhelmed the Iraqis, probably in more than four days, and with more than 285 casualties. But the outcome would have been hardly less one-sided.
The Vietnam War, 1965-1973
It is impossible to make the kind of mathematical analysis for the Vietnam War as has been done in the examples considered above. The reason is that we don’t have any good data on the Vietcong—North Vietnamese forces,
However, such quantitative analysis really isn’t necessary There can be no doubt that one of the opponents was a superpower, the most technologically advanced nation on earth, while the other side was what Lyndon Johnson called a “raggedy-ass little nation,” a typical representative of “the third world.“
Furthermore, even if we were able to make the analyses, they would very possibly be misinterpreted. It can be argued (possibly with some exaggeration) that the Americans won all of the battles. The detailed engagement analyses could only confirm this fact. Yet it is unquestionable that the United States, despite airpower and all other manifestations of technological superiority, lost the war. The human factor—as represented by the quality of American political (and to a lesser extent military) leadership on the one side, and the determination of the North Vietnamese on the other side—was responsible for this defeat.
Conclusion
In a recent article in the Armed Forces Journal International Col. Philip S. Neilinger, USAF, wrote: “Military operations are extremely difficult, if not impossible, for the side that doesn’t control the sky.” From what we have seen, this is only partly true. And while there can be no question that operations will always be difficult to some extent for the side that doesn’t control the sky, the degree of difficulty depends to a great degree upon the training and determination of the troops.
What we have seen above also enables us to view with a better perspective Colonel Neilinger’s subsequent quote from British Field Marshal Montgomery: “If we lose the war in the air, we lose the war and we lose it quickly.” That statement was true for Montgomery, and for the Allied troops in World War II. But it was emphatically not true for the Germans.
The examples we have seen from relatively recent wars, therefore, enable us to establish priorities on assuring readiness for war. It is without question important for us to equip our troops with weapons and other materiel which can match, or come close to matching, the technological quality of the opposition’s materiel. We must realize that we cannot—as some people seem to think—buy good forces, by technology alone. Even more important is to assure the fighting quality of the troops. That must be, by far, our first priority in peacetime budgets and in peacetime military activities of all sorts.
NOTES
[1] This calculation is automatic in analyses of historical battles by the Tactical Numerical Deterministic Model (TNDM).
[2] The initial tank strength of the Voronezh Army Group was about 1,100 tanks. About 3,000 additional Soviet tanks joined the battle between 6 and 12 July. At the end of the battle there were about 1,800 Soviet tanks operational in the battle area; at the same time there were about 1,000 German tanks still operational.
[3] The relative combat effectiveness value of each force is calculated in comparison to 1.0. Thus the CEV of the Germans is 2.40:1.0, while that of the Soviets is 0.42: 1.0. The opposing CEVs are always the reciprocals of each other.
The first was chosen to provide a historical context for the 3:1 rule of thumb. The second was chosen so as to examine how this rule applies to modern combat data.
We decided that this should be tested to the RAND version of the 3:1 rule as documented by RAND in 1992 and used in JICM [Joint Integrated Contingency Model] (with SFS [Situational Force Scoring]) and other models. This rule, as presented by RAND, states: “[T]he famous ‘3:1 rule,’ according to which the attacker and defender suffer equal fractional loss rates at a 3:1 force ratio if the battle is in mixed terrain and the defender enjoys ‘prepared’ defenses…”
Therefore, we selected out all those engagements from these two databases that ranged from force ratios of 2.5 to 1 to 3.5 to 1 (inclusive). It was then a simple matter to map those to a chart that looked at attackers losses compared to defender losses. In the case of the pre-1904 cases, even with a large database (243 cases), there were only 12 cases of combat in that range, hardly statistically significant. That was because most of the combat was at odds ratios in the range of .50-to-1 to 2.00-to-one.
The count of number of engagements by odds in the pre-1904 cases:
As the database is one of battles, then usually these are only joined at reasonably favorable odds, as shown by the fact that 88 percent of the battles occur between 0.40 and 2.50 to 1 odds. The twelve pre-1904 cases in the range of 2.50 to 3.50 are shown in Table 1.
If the RAND version of the 3:1 rule was valid, one would expect that the “Percent per Day Loss Ratio” (the last column) would hover around 1.00, as this is the ratio of attacker percent loss rate to the defender percent loss rate. As it is, 9 of the 12 data points are noticeably below 1 (below 0.40 or a 1 to 2.50 exchange rate). This leaves only three cases (25%) with an exchange rate that would support such a “rule.”
If we look at the simple ratio of actual losses (vice percent losses), then the numbers comes much closer to parity, but this is not the RAND interpretation of the 3:1 rule. Six of the twelve numbers “hover” around an even exchange ratio, with six other sets of data being widely off that central point. “Hover” for the rest of this discussion means that the exchange ratio ranges from 0.50-to-1 to 2.00-to 1.
Still, this is early modern linear combat, and is not always representative of modern war. Instead, we will examine 634 cases in the Division-level Database (which consists of 675 cases) where we have worked out the force ratios. While this database covers from 1904 to 1991, most of the cases are from WWII (1939- 1945). Just to compare:
As such, 87% of the cases are from WWII data and 10% of the cases are from post-WWII data. The engagements without force ratios are those that we are still working on as The Dupuy Institute is always expanding the DLEDB as a matter of routine. The specific cases, where the force ratios are between 2.50 and 3.50 to 1 (inclusive) are shown in Table 2:
This is a total of 98 engagements at force ratios of 2.50 to 3.50 to 1. It is 15 percent of the 634 engagements for which we had force ratios. With this fairly significant representation of the overall population, we are still getting no indication that the 3:1 rule, as RAND postulates it applies to casualties, does indeed fit the data at all. Of the 98 engagements, only 19 of them demonstrate a percent per day loss ratio (casualty exchange ratio) between 0.50-to-1 and 2-to-1. This is only 19 percent of the engagements at roughly 3:1 force ratio. There were 72 percent (71 cases) of those engagements at lower figures (below 0.50-to-1) and only 8 percent (cases) are at a higher exchange ratio. The data clearly was not clustered around the area from 0.50-to- 1 to 2-to-1 range, but was well to the left (lower) of it.
Looking just at straight exchange ratios, we do get a better fit, with 31 percent (30 cases) of the figure ranging between 0.50 to 1 and 2 to 1. Still, this figure exchange might not be the norm with 45 percent (44 cases) lower and 24 percent (24 cases) higher. By definition, this fit is 1/3rd the losses for the attacker as postulated in the RAND version of the 3:1 rule. This is effectively an order of magnitude difference, and it clearly does not represent the norm or the center case.
The percent per day loss exchange ratio ranges from 0.00 to 5.71. The data tends to be clustered at the lower values, so the high values are very much outliers. The highest percent exchange ratio is 5.71, the second highest is 4.41, the third highest is 2.92. At the other end of the spectrum, there are four cases where no losses were suffered by one side and seven where the exchange ratio was .01 or less. Ignoring the “N/A” (no losses suffered by one side) and the two high “outliers (5.71 and 4.41), leaves a range of values from 0.00 to 2.92 across 92 cases. With an even distribution across that range, one would expect that 51 percent of them would be in the range of 0.50-to-1 and 2.00-to-1. With only 19 percent of the cases being in that range, one is left to conclude that there is no clear correlation here. In fact, it clearly is the opposite effect, which is that there is a negative relationship. Not only is the RAND construct unsupported, it is clearly and soundly contradicted with this data. Furthermore, the RAND construct is theoretically a worse predictor of casualty rates than if one randomly selected a value for the percentile exchange rates between the range of 0 and 2.92. We do believe this data is appropriate and accurate for such a test.
As there are only 19 cases of 3:1 attacks falling in the even percentile exchange rate range, then we should probably look at these cases for a moment:
One will note, in these 19 cases, that the average attacker casualties are way out of line with the average for the entire data set (3.20 versus 1.39 or 3.20 versus 0.63 with pre-1943 and Soviet-doctrine attackers removed). The reverse is the case for the defenders (3.12 versus 6.08 or 3.12 versus 5.83 with pre-1943 and Soviet-doctrine attackers removed). Of course, of the 19 cases, 2 are pre-1943 cases and 7 are cases of Soviet-doctrine attackers (in fact, 8 of the 14 cases of the Soviet-doctrine attackers are in this selection of 19 cases). This leaves 10 other cases from the Mediterranean and ETO (Northwest Europe 1944). These are clearly the unusual cases, outliers, etc. While the RAND 3:1 rule may be applicable for the Soviet-doctrine offensives (as it applies to 8 of the 14 such cases we have), it does not appear to be applicable to anything else. By the same token, it also does not appear to apply to virtually any cases of post-WWII combat. This all strongly argues that not only is the RAND construct not proven, but it is indeed clearly not correct.
The fact that this construct also appears in Soviet literature, but nowhere else in US literature, indicates that this is indeed where the rule was drawn from. One must consider the original scenarios run for the RSAC [RAND Strategy Assessment Center] wargame were “Fulda Gap” and Korean War scenarios. As such, they were regularly conducting battles with Soviet attackers versus Allied defenders. It would appear that the 3:1 rule that they used more closely reflected the experiences of the Soviet attackers in WWII than anything else. Therefore, it may have been a fine representation for those scenarios as long as there was no US counterattacking or US offensives (and assuming that the Soviet Army of the 1980s performed at the same level as in did in the 1940s).
There was a clear relative performance difference between the Soviet Army and the German Army in World War II (see our Capture Rate Study Phase I & II and Measuring Human Factors in Combat for a detailed analysis of this).[1] It was roughly in the order of a 3-to-1-casualty exchange ratio. Therefore, it is not surprising that Soviet writers would create analytical tables based upon an equal percentage exchange of losses when attacking at 3:1. What is surprising, is that such a table would be used in the US to represent US forces now. This is clearly not a correct application.
Therefore, RAND’s SFS, as currently constructed, is calibrated to, and should only be used to represent, a Soviet-doctrine attack on first world forces where the Soviet-style attacker is clearly not properly trained and where the degree of performance difference is similar to that between the Germans and Soviets in 1942-44. It should not be used for US counterattacks, US attacks, or for any forces of roughly comparable ability (regardless of whether Soviet-style doctrine or not). Furthermore, it should not be used for US attacks against forces of inferior training, motivation and cohesiveness. If it is, then any such tables should be expected to produce incorrect results, with attacker losses being far too high relative to the defender. In effect, the tables unrealistically penalize the attacker.
As JICM with SFS is now being used for a wide variety of scenarios, then it should not be used at all until this fundamental error is corrected, even if that use is only for training. With combat tables keyed to a result that is clearly off by an order of magnitude, then the danger of negative training is high.
Christopher A. Lawrence, War by Numbers: Understanding Conventional Combat (Lincoln, NE: Potomac Books, 2017) 390 pages, $39.95
War by Numbers assesses the nature of conventional warfare through the analysis of historical combat. Christopher A. Lawrence (President and Executive Director of The Dupuy Institute) establishes what we know about conventional combat and why we know it. By demonstrating the impact a variety of factors have on combat he moves such analysis beyond the work of Carl von Clausewitz and into modern data and interpretation.
Using vast data sets, Lawrence examines force ratios, the human factor in case studies from World War II and beyond, the combat value of superior situational awareness, and the effects of dispersion, among other elements. Lawrence challenges existing interpretations of conventional warfare and shows how such combat should be conducted in the future, simultaneously broadening our understanding of what it means to fight wars by the numbers.
The book is available in paperback directly from Potomac Books and in paperback and Kindle from Amazon.
Last autumn, U.S. Army Chief of Staff General Mark Milley asserted that “we are on the cusp of a fundamental change in the character of warfare, and specifically ground warfare. It will be highly lethal, very highly lethal, unlike anything our Army has experienced, at least since World War II.” He made these comments while describing the Army’s evolving Multi-Domain Battle concept for waging future combat against peer or near-peer adversaries.
It is possible that ground combat attrition in the future between peer or near-peer combatants may be comparable to the U.S. experience in World War II (although there were considerable differences between the experiences of the various belligerents). Combat losses could be heavier. It certainly seems likely that they would be higher than those experienced by U.S. forces in recent counterinsurgency operations.
Dupuy documented a clear relationship over time between increasing weapon lethality, greater battlefield dispersion, and declining casualty rates in conventional combat. Even as weapons became more lethal, greater dispersal in frontage and depth among ground forces led daily personnel loss rates in battle to decrease.
The average daily battle casualty rate in combat has been declining since 1600 as a consequence. Since battlefield weapons continue to increase in lethality and troops continue to disperse in response, it seems logical to presume the trend in loss rates continues to decline, although this may not necessarily be the case. There were two instances in the 19th century where daily battle casualty rates increased—during the Napoleonic Wars and the American Civil War—before declining again. Dupuy noted that combat casualty rates in the 1973 Arab-Israeli War remained roughly the same as those in World War II (1939-45), almost thirty years earlier. Further research is needed to determine if average daily personnel loss rates have indeed continued to decrease into the 21st century.
Dupuy also discovered that, as with battle outcomes, casualty rates are influenced by the circumstantial variables of combat. Posture, weather, terrain, season, time of day, surprise, fatigue, level of fortification, and “all out” efforts affect loss rates. (The combat loss rates of armored vehicles, artillery, and other other weapons systems are directly related to personnel loss rates, and are affected by many of the same factors.) Consequently, yet counterintuitively, he could find no direct relationship between numerical force ratios and combat casualty rates. Combat power ratios which take into account the circumstances of combat do affect casualty rates; forces with greater combat power inflict higher rates of casualties than less powerful forces do.
Winning forces suffer lower rates of combat losses than losing forces do, whether attacking or defending. (It should be noted that there is a difference between combat loss rates and numbers of losses. Depending on the circumstances, Dupuy found that the numerical losses of the winning and losing forces may often be similar, even if the winner’s casualty rate is lower.)
Dupuy’s research confirmed the fact that the combat loss rates of smaller forces is higher than that of larger forces. This is in part due to the fact that smaller forces have a larger proportion of their troops exposed to enemy weapons; combat casualties tend to concentrated in the forward-deployed combat and combat support elements. Dupuy also surmised that Prussian military theorist Carl von Clausewitz’s concept of friction plays a role in this. The complexity of interactions between increasing numbers of troops and weapons simply diminishes the lethal effects of weapons systems on real world battlefields.
Somewhat unsurprisingly, higher quality forces (that better manage the ambient effects of friction in combat) inflict casualties at higher rates than those with less effectiveness. This can be seen clearly in the disparities in casualties between German and Soviet forces during World War II, Israeli and Arab combatants in 1973, and U.S. and coalition forces and the Iraqis in 1991 and 2003.
Combat Loss Rates on Future Battlefields
What do Dupuy’s combat attrition verities imply about casualties in future battles? As a baseline, he found that the average daily combat casualty rate in Western Europe during World War II for divisional-level engagements was 1-2% for winning forces and 2-3% for losing ones. For a divisional slice of 15,000 personnel, this meant daily combat losses of 150-450 troops, concentrated in the maneuver battalions (The ratio of wounded to killed in modern combat has been found to be consistently about 4:1. 20% are killed in action; the other 80% include mortally wounded/wounded in action, missing, and captured).
It seems reasonable to conclude that future battlefields will be less densely occupied. Brigades, battalions, and companies will be fighting in spaces formerly filled with armies, corps, and divisions. Fewer troops mean fewer overall casualties, but the daily casualty rates of individual smaller units may well exceed those of WWII divisions. Smaller forces experience significant variation in daily casualties, but Dupuy established average daily rates for them as shown below.
For example, based on Dupuy’s methodology, the average daily loss rate unmodified by combat variables for brigade combat teams would be 1.8% per day, battalions would be 8% per day, and companies 21% per day. For a brigade of 4,500, that would result in 81 battle casualties per day, a battalion of 800 would suffer 64 casualties, and a company of 120 would lose 27 troops. These rates would then be modified by the circumstances of each particular engagement.
Several factors could push daily casualty rates down. Milley envisions that U.S. units engaged in an anti-access/area denial environment will be constantly moving. A low density, highly mobile battlefield with fluid lines would be expected to reduce casualty rates for all sides. High mobility might also limit opportunities for infantry assaults and close quarters combat. The high operational tempo will be exhausting, according to Milley. This could also lower loss rates, as the casualty inflicting capabilities of combat units decline with each successive day in battle.
It is not immediately clear how cyberwarfare and information operations might influence casualty rates. One combat variable they might directly impact would be surprise. Dupuy identified surprise as one of the most potent combat power multipliers. A surprised force suffers a higher casualty rate and surprisers enjoy lower loss rates. Russian combat doctrine emphasizes using cyber and information operations to achieve it and forces with degraded situational awareness are highly susceptible to it. As Zelenopillya demonstrated, surprise attacks with modern weapons can be devastating.
Some factors could push combat loss rates up. Long-range precision weapons could expose greater numbers of troops to enemy fires, which would drive casualties up among combat support and combat service support elements. Casualty rates historically drop during night time hours, although modern night-vision technology and persistent drone reconnaissance might will likely enable continuous night and day battle, which could result in higher losses.
Drawing solid conclusions is difficult but the question of future battlefield attrition is far too important not to be studied with greater urgency. Current policy debates over whether or not the draft should be reinstated and the proper size and distribution of manpower in active and reserve components of the Army hinge on getting this right. The trend away from mass on the battlefield means that there may not be a large margin of error should future combat forces suffer higher combat casualties than expected.
Informal portrait of Charles E. W. Bean working on official files in his Victoria Barracks office during the writing of the Official History of Australia in the War of 1914-1918. The files on his desk are probably the Operations Files, 1914-18 War, that were prepared by the army between 1925 and 1930 and are now held by the Australian War Memorial as AWM 26. Courtesy of the Australian War Memorial. [Defence in Depth]
Although the posts are a couple of years old now, Dr. Robert T. Foley of the Defence Studies Department at King’s College London has provided a wonderful compilation of links to digital holdings and resources documenting the experiences of many of the many belligerents in the First World War. The links include digitized archival holdings and electronic copies of often hard-to-find official histories of ground, sea, and air operations.
For TDI, the availability of such materials greatly broadens potential sources for research on historical combat. For example, TDI made use of German regional archival holdings for to compile data on the use of chemical weapons in urban environments from the separate state armies that formed part of the Imperial German Army in the First World War. Although much of the German Army’s historical archives were destroyed by Allied bombing at the end of the Second World War, a great deal of material survived in regional state archives and in other places, as Dr. Foley shows. Access to the highly detailed official histories is another boon for such research.
The Digital Era hints at unprecedented access to historical resources and more materials are being added all the time. Current historians should benefit greatly. Future historians, alas, are not as likely to be so fortunate when it comes time to craft histories of the the current era.
Today’s edition of TDI Friday Read asks the question, how do we know if the theories and concepts we use to understand and explain war and warfare accurately depict reality? There is certainly no shortage of explanatory theories available, starting with Sun Tzu in the 6th century BCE and running to the present. As I have mentioned before, all combat models and simulations are theories about how combat works. Military doctrine is also a functional theory of warfare. But how do we know if any of these theories are actually true?
Well, one simple way to find out if a particular theory is valid is to use it to predict the outcome of the phenomenon it purports to explain. Testing theory through prediction is a fundamental aspect of the philosophy of science. If a theory is accurate, it should be able to produce a reasonable accurate prediction of future behavior.
In his 2016 article, “Can We Predict Politics? Toward What End?” Michael D. Ward, a Professor of Political Science at Duke University, made a case for a robust effort for using prediction as a way of evaluating the thicket of theory populating security and strategic studies. Dropping invalid theories and concepts is important, but there is probably more value in figuring out how and why they are wrong.
Trevor Dupuy and TDI publicly put their theories to the test in the form of combat casualty estimates for the 1991 Gulf Way, the U.S. intervention in Bosnia, and the Iraqi insurgency. How well did they do?
Dupuy himself argued passionately for independent testing of combat models against real-world data, a process known as validation. This is actually seldom done in the U.S. military operations research community.
However, TDI has done validation testing of Dupuy’s Quantified Judgement Model (QJM) and Tactical Numerical Deterministic Model (TNDM). The results are available for all to judge.
I will conclude this post on a dissenting note. Trevor Dupuy spent decades arguing for more rigor in the development of combat models and analysis, with only modest success. In fact, he encountered significant skepticism and resistance to his ideas and proposals. To this day, the U.S. Defense Department seems relatively uninterested in evidence-based research on this subject. Why?
David Wilkinson, Editor-in-Chief of the Oxford Review, wrote a fascinating blog post looking at why practitioners seem to have little actual interest in evidence-based practice.
The problem with evidence based practice is that outside of areas like health care and aviation/technology is that most people in organisations don’t care about having research evidence for almost anything they do. That doesn’t mean they are not interesting in research but they are just not that interested in using the research to change how they do things – period.
His explanation for why this is and what might be done to remedy the situation is quite interesting.
Due to their elegant simplicity, U.S. military operations researchers nevertheless began incorporating the Lanchester equations into their land warfare computer combat models and simulations in the 1950s and 60s. The equations are the basis for many models and simulations used throughout the U.S. defense community today.
The problem with using Lanchester’s equations is that, despite numerous efforts, no one has been able to demonstrate that they accurately represent real-world combat.
Trevor Dupuy was critical of combat models based on the Lanchester equations because they cannot account for the role behavioral and moral (i.e. human) factors play in combat.
He was also critical of models and simulations that had not been tested to see whether they could reliably represent real-world combat experience. In the modeling and simulation community, this sort of testing is known as validation.
The use of unvalidated concepts, like the Lanchester equations, and unvalidated combat models and simulations persists. Critics have dubbed this the “base of sand” problem, and it continues to affect not only models and simulations, but all abstract theories of combat, including those represented in military doctrine.
The constituents of combat power as described in current U.S. military doctrine. [The Lightning Press]
One of the fundamental concepts of U.S. warfighting doctrine is combat power. The current U.S. Army definition is “the total means of destructive, constructive, and information capabilities that a military unit or formation can apply at a given time. (ADRP 3-0).” It is the construct commanders and staffs are taught to use to assess the relative effectiveness of combat forces and is woven deeply throughout all aspects of U.S. operational thinking.
To execute operations, commanders conceptualize capabilities in terms of combat power. Combat power has eight elements: leadership, information, mission command, movement and maneuver, intelligence, fires, sustainment, and protection. The Army collectively describes the last six elements as the warfighting functions. Commanders apply combat power through the warfighting functions using leadership and information. [ADP 3-0, Operations]
Yet, there is no formal method in U.S. doctrine for estimating combat power. The existing process is intentionally subjective and largely left up to judgment. This is problematic, given that assessing the relative combat power of friendly and opposing forces on the battlefield is the first step in Course of Action (COA) development, which is at the heart of the U.S. Military Decision-Making Process (MDMP). Estimates of combat power also figure heavily in determining the outcomes of wargames evaluating proposed COAs.
The Existing Process
The Army’s current approach to combat power estimation is outlined in Field Manual (FM) 6-0 Commander and Staff Organization and Operations (2014). Planners are instructed to “make a rough estimate of force ratios of maneuver units two levels below their echelon.” They are then directed to “compare friendly strengths against enemy weaknesses, and vice versa, for each element of combat power.” It is “by analyzing force ratios and determining and comparing each force’s strengths and weaknesses as a function of combat power” that planners gain insight into tactical and operational capabilities, perspectives, vulnerabilities, and required resources.
That is it. Planners are told that “although the process uses some numerical relationships, the estimate is largely subjective. Assessing combat power requires assessing both tangible and intangible factors, such as morale and levels of training.” There is no guidance as to how to determine force ratios [numbers of troops or weapons systems?]. Nor is there any description of how to relate force calculations to combat power. Should force strengths be used somehow to determine a combat power value? Who knows? No additional doctrinal or planning references are provided.
Planners then use these subjective combat power assessments as they shape potential COAs and test them through wargaming. Although explicitly warned not to “develop and recommend COAs based solely on mathematical analysis of force ratios,” they are invited at this stage to consult a table of “minimum historical planning ratios as a starting point.” The table is clearly derived from the ubiquitous 3-1 rule of combat. Contrary to what FM 6-0 claims, neither the 3-1 rule nor the table have a clear historical provenance or any sort of empirical substantiation. There is no proven validity to any of the values cited. It is not even clear whether the “historical planning ratios” apply to manpower, firepower, or combat power.
During this phase, planners are advised to account for “factors that are difficult to gauge, such as impact of past engagements, quality of leaders, morale, maintenance of equipment, and time in position. Levels of electronic warfare support, fire support, close air support, civilian support, and many other factors also affect arraying forces.” FM 6-0 offers no detail as to how these factors should be measured or applied, however.
FM 6-0 also addresses combat power assessment for stability and civil support operations through troop-to-task analysis. Force requirements are to be based on an estimate of troop density, a “ratio of security forces (including host-nation military and police forces as well as foreign counterinsurgents) to inhabitants.” The manual advises that most “most density recommendations fall within a range of 20 to 25 counterinsurgents for every 1,000 residents in an area of operations. A ratio of twenty counterinsurgents per 1,000 residents is often considered the minimum troop density required for effective counterinsurgency operations.”
The Army Has Known About The Problem For A Long Time
The Army has tried several solutions to the problem of combat power estimation over the years. In the early 1970s, the U.S. Army Center for Army Analysis (CAA; known then as the U.S. Army Concepts & Analysis Agency) developed the Weighted Equipment Indices/Weighted Unit Value (WEI/WUV or “wee‑wuv”) methodology for calculating the relative firepower of different combat units. While WEI/WUV’s were soon adopted throughout the Defense Department, the subjective nature of the method gradually led it to be abandoned for official use.
In the 1980s and 1990s, the U.S. Army Command & General Staff College (CGSC) published the ST 100-9 and ST 100-3 student workbooks that contained tables of planning factors that became the informal basis for calculating combat power in staff practice. The STs were revised regularly and then adapted into spreadsheet format in the late 1990s. The 1999 iteration employed WEI/WEVs as the basis for calculating firepower scores used to estimate force ratios. CGSC stopped updating the STs in the early 2000s, as the Army focused on irregular warfare.
With the recently renewed focus on conventional conflict, Army staff planners are starting to realize that their planning factors are out of date. In an attempt to fill this gap, CGSC developed a new spreadsheet tool in 2012 called the Correlation of Forces (COF) calculator. It apparently drew upon analysis done by the U.S. Army Training and Doctrine Command Analysis Center (TRAC) in 2004 to establish new combat unit firepower scores. (TRAC’s methodology is not clear, but if it is based on this 2007 ISMOR presentation, the scores are derived from runs by an unspecified combat model modified by factors derived from the Army’s unit readiness methodology. If described accurately, this would not be an improvement over WEI/WUVs.)
The COF calculator continues to use the 3-1 force ratio tables. It also incorporates a table for estimating combat losses based on force ratios (this despite ample empirical historical analysis showing that there is no correlation between force ratios and casualty rates).
While the COF calculator is not yet an official doctrinal product, CGSC plans to add Marine Corps forces to it for use as a joint planning tool and to incorporate it into the Army’s Command Post of the Future (CPOF). TRAC is developing a stand-alone version for use by force developers.
The incorporation of unsubstantiated and unvalidated concepts into Army doctrine has been a long standing problem. In 1976, Huba Wass de Czege, then an Army major, took both “loosely structured and unscientific analysis” based on intuition and experience and simple counts of gross numbers to task as insufficient “for a clear and rigorous understanding of combat power in a modern context.” He proposed replacing it with a analytical framework for analyzing combat power that accounted for both measurable and intangible factors. Adopting a scrupulous method and language would overcome the simplistic tactical analysis then being taught. While some of the essence of Wass de Czege’s approach has found its way into doctrinal thinking, his criticism of the lack of objective and thorough analysis continues to echo (here, here, and here, for example).
Despite dissatisfaction with the existing methods, little has changed. The problem with this should be self-evident, but I will give the U.S. Naval War College the final word here:
Fundamentally, all of our approaches to force-on-force analysis are underpinned by theories of combat that include both how combat works and what matters most in determining the outcomes of engagements, battles, campaigns, and wars. The various analytical methods we use can shed light on the performance of the force alternatives only to the extent our theories of combat are valid. If our theories are flawed, our analytical results are likely to be equally wrong.
The same friend of TDI who asked about ‘Evett’s Rates,” the British casualty estimation methodology during World War II, also mentioned that the work of Albert G. Love III was now available on-line. Rick Atkinson also referenced “Love’s Tables” in The Guns At Last Light.
During this phase, planners are advised to account for “factors that are difficult to gauge, such as impact of past engagements, quality of leaders, morale, maintenance of equipment, and time in position. Levels of electronic warfare support, fire support, close air support, civilian support, and many other factors also affect arraying forces.” FM 6-0 offers no detail as to how these factors should be measured or applied, however.