Hopefully this is my last post on the subject (but I suspect not, as I expect a public response from the three TRADOC authors). This is in response to the article in the December 2018 issue of the Phalanxby Alt, Morey and Larimer (see Part 1, Part 2, Part 3, Part 4, Part 5, Part 6). The issue here is the “Base of Sand” problem, which is what the original blog post that “inspired” their article was about:
While the first paragraph of their article addressed this blog post and they reference Paul Davis’ 1992 Base of Sand paper in their footnotes (but not John Stockfish’s paper, which is an equally valid criticism), they then do not discuss the “Base of Sand” problem further. They do not actually state whether this is a problem or not a problem. I gather by this notable omission that in fact they do understand that it is a problem, but being employees of TRADOC they are limited as to what they can publicly say. I am not.
I do address the “Base of Sand” problem in my book War by Numbers, Chapter 18. It has also been addressed in a few other posts on this blog. We are critics because we do not see significant improvement in the industry. In some cases, we are seeing regression.
In the end, I think the best solution for the DOD modeling and simulation community is not to “circle the wagons” and defend what they are currently doing, but instead acknowledge the limitations and problems they have and undertake a corrective action program. This corrective action program would involve: 1) Properly addressing how to measure and quantify certain aspects of combat (for example: Breakpoints) and 2) Validating these aspects and the combat models these aspects are part of by using real-world combat data. This would be an iterative process, as you develop and then test the model, then further develop it, and then test it again. This moves us forward. It is a more valued approach than just “circling the wagons.” As these models and simulations are being used to analyze processes that may or may not make us fight better, and may or may not save American service members lives, then I think it is important enough to do right. That is what we need to be focused on, not squabbling over a blog post (or seven).
As Chris Lawrence mentioned yesterday, retired Brigadier General John Hanley’s review of America’s Modern Wars in the current edition of Military Review concluded by pointing out the importance of a solid empirical basis for staff planning support for reliable military decision-making. This notion seems so obvious as to be a truism, but in reality, the U.S. Army has demonstrated no serious interest in remedying the weaknesses or gaps in the base of knowledge underpinning its basic concepts and doctrine.
In 2012, Major James A. Zanella published a monograph for the School of Advanced Military Studies of the U.S. Army Command and General Staff College (graduates of which are known informally as “Jedi Knights”), which examined problems the Army has had with estimating force requirements, particularly in recent stability and counterinsurgency efforts.
Historically, the United States military has had difficulty articulating and justifying force requirements to civilian decision makers. Since at least 1975, governmental officials and civilian analysts have consistently criticized the military for inadequate planning and execution. Most recently, the wars in Afghanistan and Iraq reinvigorated the debate over the proper identification of force requirements…Because Army planners have failed numerous times to provide force estimates acceptable to the President, the question arises, why are the planning methods inadequate and why have they not been improved?[1]
Zanella surveyed the various available Army planning tools and methodologies for determining force requirements, but found them all either inappropriate or only marginally applicable, or unsupported by any real-world data. He concluded
Considering the limitations of Army force planning methods, it is fair to conclude that Army force estimates have failed to persuade civilian decision-makers because the advice is not supported by a consistent valid method for estimating the force requirements… What is clear is that the current methods have utility when dealing with military situations that mirror the conditions represented by each model. In the contemporary military operating environment, the doctrinal models no longer fit.[2]
Zanella did identify the existence of recent, relevant empirical studies on manpower and counterinsurgency. He noted that “the existing doctrine on force requirements does not benefit from recent research” but suggested optimistically that it could provide “the Army with new tools to reinvigorate the discussion of troops-to-task calculations.”[3] Even before Zanella published his monograph, however, the Defense Department began removing any detailed reference or discussion about force requirements in counterinsurgency from Army and Joint doctrinal publications.
As Zanella discussed, there is a body of recent empirical research on manpower and counterinsurgency that contains a variety of valid and useful insights, but as I recently discussed, it does not yet offer definitive conclusions. Much more research and analysis is needed before the conclusions can be counted on as a valid and justifiably reliable basis for life and death decision-making. Yet, the last of these government sponsored studies was completed in 2010. Neither the Army nor any other organization in the U.S. government has funded any follow-on work on this subject and none appears forthcoming. This boom-or-bust pattern is nothing new, but the failure to do anything about it is becoming less and less understandable.
NOTES
[1] Major James A. Zanella, “Combat Power Analysis is Combat Power Density” (Ft. Leavenworth, KS: School of Advanced Military Studies, U.S. Army Command and General Staff College, 2012), pp. 1-2.
The ground forces were the last branch of the Army to incorporate OR into their efforts during World War II, lagging behind the Army Air Forces, the technical services, and the Navy. Where the Army was a step ahead, however, was in creating a robust wartime historical field history documentation program. (After the war, this enabled the publication of the U.S. Army in World War II series, known as the “Green Books,” which set a new standard for government sponsored military histories.)
As Shrader related, the first OR personnel the Army deployed forward in 1944-45 often crossed paths with War Department General Staff Historical Branch field historian detachments. They both engaged in similar activities: collecting data on real-world combat operations, which was then analyzed and used for studies and reports written for the use of the commands to which they were assigned. The only significant difference was in their respective methodologies, with the historians using historical methods and the OR analysts using mathematical and scientific tools.
History and OR after World War II
The usefulness of historical approaches to collecting operational data did not go unnoticed by the OR practitioners, according to Shrader. When the Army established the Operations Research Office (ORO) in 1948, it hired a contingent of historians specifically for the purpose of facilitating research and analysis using WWII Army records, “the most likely source for data on operational matters.”
When the Korean War broke out in 1950, ORO sent eight multi-disciplinary teams, including the historians, to collect operational data and provide analytical support for U.S. By 1953, half of ORO’s personnel had spent time in combat zones. Throughout the 1950s, about 40-43% of ORO’s staff was comprised of specialists in the social sciences, history, business, literature, and law. Shrader quoted one leading ORO analyst as noting that, “there is reason to believe that the lawyer, social scientist or historian is better equipped professionally to evaluate evidence which is derived from the mind and experience of the human species.”
Among the notable historians who worked at or with ORO was Dr. Hugh M. Cole, an Army officer who had served as a staff historian for General George Patton during World War II. Cole rose to become a senior manager at ORO and later served as vice-president and president of ORO’s successor, the Research Analysis Corporation (RAC). Cole brought in WWII colleague Forrest C. Pogue (best known as the biographer of General George C. Marshall) and Charles B. MacDonald. ORO also employed another WWII field historian, the controversial S. L. A. Marshall, as a consultant during the Korean War. Dorothy Kneeland Clark did pioneering historical analysis on combat phenomena while at ORO.
The Demise of ORO…and Historical Combat Analysis?
By the late 1950s, considerable institutional friction had developed between ORO, the Johns Hopkins University (JHU)—ORO’s institutional owner—and the Army. According to Shrader,
Continued distrust of operations analysts by Army personnel, questions about the timeliness and focus of ORO studies, the ever-expanding scope of ORO interests, and, above all, [ORO director] Ellis Johnson’s irascible personality caused tensions that led in August 1961 to the cancellation of the Army’s contract with JHU and the replacement of ORO with a new, independent research organization, the Research Analysis Corporation [RAC].
RAC inherited ORO’s research agenda and most of its personnel, but changing events and circumstances led Army OR to shift its priorities away from field collection and empirical research on operational combat data in favor of the use of modeling and wargaming in its analyses. As Chris Lawrence described in his history of federally-funded Defense Department “think tanks,” the rise and fall of scientific management in DOD, the Vietnam War, social and congressional criticism, and an unhappiness by the military services with the analysis led to retrenchment in military OR by the end of the 60s. The Army sold RAC and created its own in-house Concepts Analysis Agency (CAA; now known as the Center for Army Analysis).
By the early 1970s, analysts, such as RAND’s Martin Shubik and Gary Brewer, and John Stockfisch, began to note that the relationships and processes being modeled in the Army’s combat simulations were not based on real-world data and that empirical research on combat phenomena by the Army OR community had languished. In 1991, Paul Davis and Donald Blumenthal gave this problem a name: the “Base of Sand.”
On the first page (page 28) in the third column they make the statement that:
Models of complex systems, especially those that incorporate human behavior, such as that demonstrated in combat, do not often lend themselves to empirical validation of output measures, such as attrition.
Really? Why can’t you? If fact, isn’t that exactly the model you should be validating?
More to the point, people have validated attrition models. Let me list a few cases (this list is not exhaustive):
1. Done by Center for Army Analysis (CAA) for the CEM (Concepts Evaluation Model) using Ardennes Campaign Simulation Study (ARCAS) data. Take a look at this study done for Stochastic CEM (STOCEM): https://apps.dtic.mil/dtic/tr/fulltext/u2/a489349.pdf
2. Done in 2005 by The Dupuy Institute for six different casualty estimation methodologies as part of Casualty Estimation Methodologies Studies. This was work done for the Army Medical Department and funded by DUSA (OR). It is listed here as report CE-1: http://www.dupuyinstitute.org/tdipub3.htm
3. Done in 2006 by The Dupuy Institute for the TNDM (Tactical Numerical Deterministic Model) using Corps and Division-level data. This effort was funded by Boeing, not the U.S. government. This is discussed in depth in Chapter 19 of my book War by Numbers (pages 299-324) where we show 20 charts from such an effort. Let me show you one from page 315:
So, this is something that multiple people have done on multiple occasions. It is not so difficult that The Dupuy Institute was not able to do it. TRADOC is an organization with around 38,000 military and civilian employees, plus who knows how many contractors. I think this is something they could also do if they had the desire.
On the first page (page 28) top of the third column they make the rather declarative statement that:
The combat simulations used by military operations research and analysis agencies adhere to strict standards established by the DoD regarding verification, validation and accreditation (Department of Defense, 2009).
Now, I have not reviewed what has been done on verification, validation and accreditation since 2009, but I did do a few fairly exhaustive reviews before then. One such review is written up in depth in The International TNDM Newsletter. It is Volume 1, No. 4 (February 1997). You can find it here:
The newsletter includes a letter dated 21 January 1997 from the Scientific Advisor to the CG (Commanding General) at TRADOC (Training and Doctrine Command). This is the same organization that the three gentlemen who wrote the article in the Phalanx work for. The Scientific Advisor sent a letter out to multiple commands to try to flag the issue of validation (letter is on page 6 of the newsletter). My understanding is that he received few responses (I saw only one, it was from Leavenworth). After that, I gather there was no further action taken. This was a while back, so maybe everything has changed, as I gather they are claiming with that declarative statement. I doubt it.
This issue to me is validation. Verification is often done. Actual validations are a lot rarer. In 1997, this was my list of combat models in the industry that had been validated (the list is on page 7 of the newsletter):
1. Atlas (using 1940 Campaign in the West)
2. Vector (using undocumented turning runs)
3. QJM (by HERO using WWII and Middle-East data)
4. CEM (by CAA using Ardennes Data Base)
5. SIMNET/JANUS (by IDA using 73 Easting data)
Now, in 2005 we did a report on Casualty Estimation Methodologies (it is report CE-1 list here: http://www.dupuyinstitute.org/tdipub3.htm). We reviewed the listing of validation efforts, and from 1997 to 2005…nothing new had been done (except for a battalion-level validation we had done for the TNDM). So am I now to believe that since 2009, they have actively and aggressively pursued validation? Especially as most of this time was in a period of severely declining budgets, I doubt it. One of the arguments against validation made in meetings I attended in 1987 was that they did not have the time or budget to spend on validating. The budget during the Cold War was luxurious by today’s standards.
If there have been meaningful validations done, I would love to see the validation reports. The proof is in the pudding…..send me the validation reports that will resolve all doubts.
The Military Operations Research Society (MORS) publishes a periodical journal called the Phalanx. In the December 2018 issue was an article that referenced one of our blog posts. This took us by surprise. We only found out about thanks to one of the viewers of this blog. We are not members of MORS. The article is paywalled and cannot be easily accessed if you are not a member.
It is titled “Perspectives on Combat Modeling” (page 28) and is written by Jonathan K. Alt, U.S. Army TRADOC Analysis Center, Monterey, CA.; Christopher Morey, PhD, Training and Doctrine Command Analysis Center, Ft. Leavenworth, Kansas; and Larry Larimer, Training and Doctrine Command Analysis Center, White Sands, New Mexico. I am not familiar with any of these three gentlemen.
The blog post that appears to be generating this article is this one:
Simply by coincidence, Shawn Woodford recently re-posted this in January. It was originally published on 10 April 2017 and was written by Shawn.
The opening two sentences of the article in the Phalanx reads:
Periodically, within the Department of Defense (DoD) analytic community, questions will arise regarding the validity of the combat models and simulations used to support analysis. Many attempts (sic) to resurrect the argument that models, simulations, and wargames “are built on the thin foundation of empirical knowledge about the phenomenon of combat.” (Woodford, 2017).
It is nice to be acknowledged, although it this case, it appears that we are being acknowledged because they disagree with what we are saying.
Probably the word that gets my attention is “resurrect.” It is an interesting word, that implies that this is an old argument that has somehow or the other been put to bed. Granted it is an old argument. On the other hand, it has not been put to bed. If a problem has been identified and not corrected, then it is still a problem. Age has nothing to do with it.
On the other hand, maybe they are using the word “resurrect” because recent developments in modeling and validation have changed the environment significantly enough that these arguments no longer apply. If so, I would be interested in what those changes are. The last time I checked, the modeling and simulation industry was using many of the same models they had used for decades. In some cases, were going back to using simpler hex-games for their modeling and wargaming efforts. We have blogged a couple of times about these efforts. So, in the world of modeling, unless there have been earthshaking and universal changes made in the last five years that have completely revamped the landscape….then the decades old problems still apply to the decades old models and simulations.
More to come (this is the first of at least 7 posts on this subject).
The President of Afghanistan, Ashraf Ghani, speaking with CNN’s Farid Zakiria, at the World Economic Forum in Davos, Switzerland, 25 January 2019. [Office of the President, Islamic Republic of Afghanistan]
This revised figure casts significant doubt on the validity of analysis based on the previous reporting. Correcting it will be difficult. At the request of the Afghan government in May 2017, the U.S. military has treated security forces attrition and loss data as classified and has withheld it from public release.
Source: David A. Shlapak and Michael Johnson. Reinforcing Deterrence on NATO’s Eastern Flank: Wargaming the Defense of the Baltics. Santa Monica, CA: RAND Corporation, 2016.
[UPDATE] We had several readers recommend games they have used or would be suitable for simulating Multi-Domain Battle and Operations (MDB/MDO) concepts. These include several classic campaign-level board wargames:
Chris Lawrence recently looked at C-WAM and found that it uses a lot of traditional board wargaming elements, including methodologies for determining combat results, casualties, and breakpoints that have been found unable to replicate real-world outcomes (aka “The Base of Sand” problem).
What other wargames, models, and simulations are there being used out there? Are there any commercial wargames incorporating MDB/MDO elements into their gameplay? What methodologies are being used to portray MDB/MDO effects?
[This piece was originally posted on 27 June 2016.]
Previous posts have detailed casualty estimates by Trevor Dupuy or The Dupuy Institute (TDI) for the 1990-91 Gulf War and the 1995 intervention in Bosnia. Today I will detail TDI’s 2004 forecast for U.S. casualties in the Iraqi insurgency that began in 2003.
In April 2004, as simultaneous Sunni and Shi’a uprisings dramatically expanded the nascent insurgency in Iraq, the U.S. Army Center for Army Analysis (CAA) accepted an unsolicited proposal from TDI President and Executive Director Christopher Lawrence to estimate likely American casualties in the conflict. A four-month contract was finalized in August.
The methodology TDI adopted for the estimate was a comparative case study analysis based on a major data collection effort on insurgencies. 28 cases were selected for analysis based on five criteria:
The conflict had to be post-World War II to facilitate data collection;
It had to have lasted more than a year (as was already the case in Iraq);
It had to be a developed nation intervening in a developing nation;
The intervening nation had to have provided military forces to support or establish an indigenous government; and
There had to be an indigenous guerilla movement (although it could have received outside help).
Extensive data was collected from these 28 cases, including the following ten factors used in the estimate:
Country Area
Orderliness
Population
Intervening force size
Border Length
Insurgency force size
Outside support
Casualty rate
Political concept
Force ratios
Initial analysis compared this data to insurgency outcomes, which revealed some startlingly clear patterns suggesting cause and effect relationships. From this analysis, TDI drew the following conclusions:
It is difficult to control large countries.
It is difficult to control large populations.
It is difficult to control an extended land border.
Limited outside support does not doom an insurgency.
“Disorderly” insurgencies are very intractable and often successful insurgencies.
Insurgencies with large intervening third-party counterinsurgent forces (above 95,000) often succeed.
Higher combat intensities do not doom an insurgency.
In all, TDI assessed that the Iraqi insurgency fell into the worst category in nine of the ten factors analyzed. The outcome would hinge on one fundamental question: was the U.S. facing a regional, factional insurgency in Iraq or a widespread anti-intervention insurgency? Based on the data, if the insurgency was factional or regional, it would fail. If it became a nationalist revolt against a foreign power, it would succeed.
Based on the data and its analytical conclusions, TDI provided CAA with an initial estimate in December 2004, and a final version in January 2005:
Insurgent force strength is probably between 20,000–60,000.
This is a major insurgency.
It is of medium intensity.
It is a regional or factionalized insurgency and must remain that way.
U.S. commitment can be expected to be relatively steady throughout this insurgency and will not be quickly replaced by indigenous forces.
It will last around 10 or so years.
It may cost the U.S. 5,000 to 10,000 killed.
It may be higher.
This assumes no major new problems in the Shiite majority areas.
When TDI made its estimate in December 2004, the conflict had already lasted 21 months, and U.S. casualties were 1,335 killed, 1,038 of them in combat.
When U.S. forces withdrew from Iraq in December 2011, the war had gone on for 105 months (8.7 years), and U.S. casualties had risen to 4,485 fatalities—3,436 in combat. The United Kingdom lost 180 troops killed and Coalition allies lost 139. There were at least 468 contractor deaths from a mix of nationalities. The Iraqi Army and police suffered at least 10,125 deaths. Total counterinsurgent fatalities numbered at least 15,397.
As of this date, the conflict in Iraq that began in 2003 remains ongoing.
A great deal of importance has been placed on the knowledge derived from these activities. As the U.S. Army Training and Doctrine Command recently stated,
Concept analysis informed by joint and multinational learning events…will yield the capabilities required of multi-domain battle. Resulting doctrine, organization, training, materiel, leadership, personnel and facilities solutions will increase the capacity and capability of the future force while incorporating new formations and organizations.
There is, however, a problem afflicting the Defense Department’s wargames, of which the military operations research and models and simulations communities have long been aware, but have been slow to address: their models are built on a thin foundation of empirical knowledge about the phenomenon of combat. None have proven the ability to replicate real-world battle experience. This is known as the “base of sand” problem.
A Brief History of The Base of Sand
All combat models and simulations are abstracted theories of how combat works. Combat modeling in the United States began in the early 1950s as an extension of military operations research that began during World War II. Early model designers did not have large base of empirical combat data from which to derive their models. Although a start had been made during World War II and the Korean War to collect real-world battlefield data from observation and military unit records, an effort that provided useful initial insights, no systematic effort has ever been made to identify and assemble such information. In the absence of extensive empirical combat data, model designers turned instead to concepts of combat drawn from official military doctrine (usually of uncertain provenance), subject matter expertise, historians and theorists, the physical sciences, or their own best guesses.
As the U.S. government’s interest in scientific management methods blossomed in the late 1950s and 1960s, the Defense Department’s support for operations research and use of combat modeling in planning and analysis grew as well. By the early 1970s, it became evident that basic research on combat had not kept pace. A survey of existing combat models by Gary Shubik and Martin Brewer for RAND in 1972 concluded that
Basic research and knowledge is lacking. The majority of the MSGs [models, simulations and games] sampled are living off a very slender intellectual investment in fundamental knowledge…. [T]he need for basic research is so critical that if no other funding were available we would favor a plan to reduce by a significant proportion all current expenditures for MSGs and to use the saving for basic research.
The [Defense Department]is becoming critically dependent on combat models (including simulations and war games)—even more dependent than in the past. There is considerable activity to improve model interoperability and capabilities for distributed war gaming. In contrast to this interest in model-related technology, there has been far too little interest in the substance of the models and the validity of the lessons learned from using them. In our view, the DoD does not appreciate that in many cases the models are built on a base of sand…
[T]he DoD’s approach in developing and using combat models, including simulations and war games, is fatally flawed—so flawed that it cannot be corrected with anything less than structural changes in management and concept. [Original emphasis]
As a remedy, the authors recommended that the Defense Department create an office to stimulate a national military science program. This Office of Military Science would promote and sponsor basic research on war and warfare while still relying on the military services and other agencies for most research and analysis.
Davis and Blumenthal initially drafted their white paper before the 1991 Gulf War, but the performance of the Defense Department’s models and simulations in that conflict underscored the very problems they described. Defense Department wargames during initial planning for the conflict reportedly predicted tens of thousands of U.S. combat casualties. These simulations were said to have led to major changes in U.S. Central Command’s operational plan. When the casualty estimates leaked, they caused great public consternation and inevitable Congressional hearings.
The Defense Department’s current generation of models and simulations harbor the same weaknesses as the ones in use in the 1990s. Some are new iterations of old models with updated graphics and code, but using the same theoretical assumptions about combat. In most cases, no one other than the designers knows exactly what data and concepts the models are based upon. This practice is known in the technology world as black boxing. While black boxing may be an essential business practice in the competitive world of government consulting, it makes independently evaluating the validity of combat models and simulations nearly impossible. This should be of major concern because many models and simulations in use today contain known flaws.
Others, such as the Joint Conflict And Tactical Simulation (JCATS), MAGTF Tactical Warfare System (MTWS), and Warfighters’ Simulation (WARSIM) adjudicate ground combat using probability of hit/probability of kill (pH/pK) algorithms. Corps Battle Simulation (CBS) uses pH/pK for direct fire attrition and a modified version of Lanchester for indirect fire. While these probabilities are developed from real-world weapon system proving ground data, their application in the models is combined with inputs from subjective sources, such as outputs from other combat models, which are likely not based on real-world data. Multiplying an empirically-derived figure by a judgement-based coefficient results in a judgement-based estimate, which might be accurate or it might not. No one really knows.
This state of affairs seems remarkable given the enormous stakes that are being placed on the output of the Defense Department’s modeling and simulation activities. After decades of neglect, remedying this would require a dedicated commitment to sustained basic research on the military science of combat and warfare, with no promise of a tangible short-term return on investment. Yet, as Biddle pointed out, “With so much at stake, we surely must do better.”
[NOTE: The attrition methodologies used in CBS and WARSIM have been corrected since this post was originally published per comments provided by their developers.]
While perusing Charles Shrader’s fascinating 
