Mystics & Statistics

A blog on quantitative historical analysis hosted by The Dupuy Institute

Engaging the Phalanx (part 7 of 7)

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 Phalanx by 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:

Wargaming Multi-Domain Battle: The Base Of Sand Problem

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).

Has The Army Given Up On Counterinsurgency Research, Again?

Mind-the-Gap

[In light of the U.S. Army’s recent publication of a history of it’s involvement in Iraq from 2003 to 2011, it may be relevant to re-post this piece from from 29 June 2016.]

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.

[2] Ibid, 50.

[3] Ibid, 47.

Historians and the Early Era of U.S. Army Operations Research

While perusing Charles Shrader’s fascinating history of the U.S. Army’s experience with operations research (OR), I came across several references to the part played by historians and historical analysis in early era of that effort.

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.”

SMEs

Continuing my comments on the article in the December 2018 issue of the Phalanx by Alt, Morey and Larimer (this is part 6 of 7; see Part 1, Part 2, Part 3, Part 4, Part 5).

SMEs….is a truly odd sounding acronym that means Subject Matter Experts. They talk about it extensively in their article, and this I have no problem with. I do want to make three points related to that:

  1. A SME is not a substitution for validation.
  2. In some respects, the QJM (Quantified Judgment Model) is a quantified and validated SME.
  3. How do you know that the SME is right?

If you can substitute a SME for a proper validation effort, then perhaps you could just substitute the SME for the model. This would save time and money. If your SME is knowledgable enough to sprinkle holy water on the model and bless its results, why not just skip the model and ask the SME. We could certainly simplify and speed up analysis by removing the models and just asking our favorite SME. The weaknesses of this approach are obvious.

Then there is Trevor N. Dupuy’s Quantified Judgment Model (QJM) and Quantified Judgment Method of Analysis (QJMA). This is, in some respects, a SME quantified. Actually it was a board of SMEs, who working with a series of historical studies (the list of studies starts here: http://www.dupuyinstitute.org/tdipubs.htm ). These SMEs developed a set of values for different situations, and then insert them into a model. They then validated the model to historical data (also known as real-world combat data). While the QJM has come under considerable criticism from elements of the Operations Research community…..if you are using SMEs, then in fact, you are using something akin, but less rigorous, than Trevor Dupuy’s Quantified Judgment Method of Analysis.

This last point, how do we know that the SME is right, is significant. How do you test your SMEs to ensure that what they are saying is correct? Another SME, a board of SMEs? Maybe a BOGSAT? Can you validate SMEs? There are limits to SME’s. In the end, you need a validated model.

 

Historical Demonstrations?

Photo from the 1941 Louisiana Maneuvers

Continuing my comments on the article in the December 2018 issue of the Phalanx by Alt, Morey and Larimer (this is part 5 of 7; see Part 1, Part 2, Part 3, Part 4).

The authors of the Phalanx article then make the snarky statement that:

Combat simulations have been successfully used to replicate historical battles as a demonstration, but this is not a requirement or their primary intended use.

So, they say in three sentences that combat models using human factors are difficult to validate, they then say that physics-based models are validated, and then they say that running a battle through a model is a demonstration. Really?

Does such a demonstration show that the model works or does not work? Does such a demonstration show that they can get a reasonable outcome when using real-world data? The definition of validation that they gave on the first page of their article is:

The process of determining the degree to which a model or simulation with its associated data is an accurate representation of the real world from the perspective of its intended use is referred to as validation.

This is a perfectly good definition of validation. So where does one get that real-world data? If you are using the model to measure combat effects (as opposed to physical affects) then you probably need to validate it to real-world combat data. This means historical combat data, whether it is from 3,400 years ago or 1 second ago. You need to assemble the data from a (preferably recent) combat situation and run it through the model.

This has been done. The Dupuy Institute does not exist in a vacuum. We have assembled four sets of combat data bases for use in validation. They are:

  1. The Ardennes Campaign Simulation Data Base
  2.  The Kursk Data Base
  3. The Battle of Britain Data Base
  4. Our various division-level, battalion-level and company-level engagement database bases.

Now, the reason we have mostly used World War II data is that you can get detailed data from the unit records of both sides. To date….this is not possible for almost any war since 1945. But, if your high-tech model cannot predict lower-tech combat….then you probably also have a problem modeling high-tech combat. So, it is certainly a good starting point.

More to the point, this was work that was funded in part by the Center for Army Analysis, the Deputy Secretary of the Army (Operations Research) and Office of Secretary of Defense, Planning, Analysis and Evaluation. Hundreds of thousands of dollars were spent developing some of these databases. This was not done just for “demonstration.” This was not done as a hobby. If their sentence was meant to be-little the work of TDI, which is how I do interpret that sentence, then is also belittles the work of CAA, DUSA(OR) and OSD PA&E. I am not sure that is the three author’s intent.

Physics-based Aspects of Combat

Continuing my comments on the article in the December 2018 issue of the Phalanx by Alt, Morey and Larimer (this is part 4 of 7; see Part 1, Part 2, Part 3).

The next sentence in the article is interesting. After saying that validating models incorporating human behavior is difficult (and therefore should not be done?) they then say:

In combat simulations, those model components that lend themselves to empirical validation, such as the physics-based aspects of combat, are developed, validated, and verified using data from an accredited source.

This is good. But, the problem lies that it limits one to only validating models that do not include humans. If one is comparing a weapon system to a weapon system, as they discuss later, this is fine. On the other hand, if one is comparing units in combat to units in combat…then there are invariably humans involved. Even if you are comparing weapon systems versus weapon systems in an operational environment, there are humans involved. Therefore, you have to address human factors. Once you have gone beyond simple weapon versus weapon comparisons, you need to use models that are gaming situations that involved humans. I gather from the previous sentence (see part 3 of 7) and this sentence, that means that they are using un-validated models. Their extended discussions of SMEs (Subject Matter Experts) that follows just reinforces that impression.

But, TRADOC is the training and doctrine command. They are clearly modeling something other than just the “physics-based aspect of combat.”

Validating Attrition

Continuing to comment on the article in the December 2018 issue of the Phalanx by Alt, Morey and Larimer (this is part 3 of 7; see Part 1, Part 2)

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.

 

Validation

Continuing to comment on the article in the December 2018 issue of the Phalanx by Jonathan Alt, Christopher Morey and Larry Larimer (this is part 2 of 7; see part 1 here).

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:

http://www.dupuyinstitute.org/tdipub4.htm

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.

Engaging the Phalanx

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:

Wargaming Multi-Domain Battle: The Base Of Sand Problem

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).

Afghan Security Forces Deaths Top 45,000 Since 2014

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]

Last Friday, at the World Economic Forum in Davos, Switzerland, Afghan President Ashraf Ghani admitted that his country’s security forces had suffered over 45,000 fatalities since he took office in September 2014. This total far exceeds the total of 28,000 killed since 2015 that Ghani had previously announced in November 2018. Ghani’s cryptic comment in Davos did not indicate how the newly revealed total relates to previously released figures, whether it was based on new accounting, a sharp increase in recent casualties, or more forthrightness.

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.

If Ghani’s figure is, in fact, accurate, then it reinforces the observation that the course of the conflict is tilting increasingly against the Afghan government.