This was the first virtual presentation of the conference. It happened after lunch, so we had resolved some of our earlier issues. Not only was Dr. David Kirkpatrick (University College London) able to give a virtual presentation, but Dr. Robert Helmbold was able to attend virtually and discuss the briefing with him. This is kind of how these things are supposed to work.
There is an earlier version on the channel that is 1:10 longer. That was uploaded first, but I decided to edit out a small section of the presentation.
The briefing ends at 40:20 and discussion continues for 12 minutes afterwards.
Fitting Lanchester Equations by Dr. Thomas Lucas (NPS) has now been posted to our YouTube channel. It was his presentation given at the 21st HAAC in September 2022. The briefing runs 54:20 with a few minutes of questions and discussion afterwards: (5) Fitting Lanchester Equations: Lucas – YouTube
We have also done a few blog posts on Lanchester equations:
F.W. Lanchester famously reduced the mutual erosion of attrition warfare to simple mathematical form, resulting in his famous “Square Law,” and also the “Linear Law.” Followers have sought to fit real-world data to Lanchester’s equations, and/or to elaborate them in order to capture more aspects of reality. In Beyond Lanchester, Brian McCue–author of the similarly quantitative U-Boats In The Bay Of Biscay–focusses on a neglected shortcoming of Lanchester’s work: its determinism. He shows that the mathematics of the Square Law contain instability, so that the end-state it predicts is actually one of the least likely outcomes. This mathematical truth is connected to the real world via examples drawn from United States Marine Corps exercises, Lanchester’s original Trafalgar example, predator-prey experiments done by the early ecologist G.F. Gause, and, of course the war against German U-boats
This is an in-depth discussion of the subject of the use Lanchester equations by Dr. Brian McCue, previously of CNA (Center for Naval Analysis) and OTA (Congressional Office of Technology Assistance). We have also posted and written before about Lanchester (see War by Numbers). Some of our old blog posts on Lanchester are here:
As I stated in a previous post, I am not aware of any other major validation efforts done in the last 25 years other than what we have done. Still, there is one other effort that needs to be mentioned. This is described in a 2017 report: Using Combat Adjudication to Aid in Training for Campaign Planning.pdf
I gather this was work by J-7 of the Joint Staff to develop Joint Training Tools (JTT) using the Combat Adjudication Service (CAS) model. There are a few lines in the report that warm my heart:
“It [JTT] is based on and expanded from Dupuy’s Quantified Judgement Method of Analysis (QJMA) and Tactical Deterministic Model.”
“The CAS design used Dupuy’s data tables in whole or in part (e.g. terrain, weather, water obstacles, and advance rates).”
“Non-combat power variables describing the combat environment and other situational information are listed in Table 1, and are a subset of variables (Dupuy, 1985).”
“The authors would like to acknowledge COL Trevor N. Dupuy for getting Michael Robel interested in combat modeling in 1979.”
Now, there is a section labeled verification and validation. Let me quote from that:
CAS results have been “Face validated” against the following use cases:
The 3:1 rules. The rule of thumb postulating an attacking force must have at least three times the combat power of the defending force to be successful.
1st (US) Infantry Divison vers 26th (IQ) Infantry Division during Desert Storm
The Battle of 73 Easting: 2nd ACR versus elements of the Iraqi Republican Guards
3rd (US) Infantry Division’s first five days of combat during Operation Iraqi Freedom (OIF)
Each engagement is conducted with several different terrain and weather conditions, varying strength percentages and progresses from a ground only engagement to multi-service engagements to test the effect of CASP [Close Air Support] and interdiction on the ground campaign. Several shortcomings have been detected, but thus far ground and CASP match historical results. However, modeling of air interdiction could not be validated.
So, this is a face validation based upon three cases. This is more than what I have seen anyone else do in the last 25 years.
What we have listed in the previous articles is what we consider the six best databases to use for validation. The Ardennes Campaign Simulation Data Base (ACSDB) was used for a validation effort by CAA (Center for Army Analysis). The Kursk Data Base (KDB) was never used for a validation effort but was used, along with Ardennes, to test Lanchester equations (they failed).
The Battle of Britain Data Base to date has not been used for anything that we are aware of. As the program we were supporting was classified, then they may have done some work with it that we are not aware of, but I do not think that is the case.
Our three battles databases, the division-level data base, the battalion-level data base and the company-level data base, have all be used for validating our own TNDM (Tactical Numerical Deterministic Model). These efforts have been written up in our newsletters (here: http://www.dupuyinstitute.org/tdipub4.htm) and briefly discussed in Chapter 19 of War by Numbers. These are very good databases to use for validation of a combat model or testing a casualty estimation methodology. We have also used them for a number of other studies (Capture Rate, Urban Warfare, Lighter-Weight Armor, Situational Awareness, Casualty Estimation Methodologies, etc.). They are extremely useful tools analyzing the nature of conflict and how it impacts certain aspects. They are, of course, unique to The Dupuy Institute and for obvious business reasons, we do keep them close hold.
We do have a number of other database that have not been used as much. There is a list of 793 conflicts from 1898-1998 that we have yet to use for anything (the WACCO – Warfare, Armed Conflict and Contingency Operations database). There is the Campaign Data Base (CaDB) of 196 cases from 1904 to 1991, which was used for the Lighter Weight Armor study. There are three databases that are mostly made of cases from the original Land Warfare Data Base (LWDB) that did not fit into our division-level, battalion-level, and company-level data bases. They are the Large Action Data Base (LADB) of 55 cases from 1912-1973, the Small Action Data Base (SADB) of 5 cases and the Battles Data Base (BaDB) of 243 cases from 1600-1900. We have not used these three database for any studies, although the BaDB is used for analysis in War by Numbers.
Finally, there are three databases on insurgencies, interventions and peacekeeping operations that we have developed. This first was the Modern Contingency Operations Data Base (MCODB) that we developed to use for Bosnia estimate that we did for the Joint Staff in 1995. This is discussed in Appendix II of America’s Modern Wars. It then morphed into the Small Scale Contingency Operations (SSCO) database which we used for the Lighter Weight Army study. We then did the Iraq Casualty Estimate in 2004 and significant part of the SSCO database was then used to create the Modern Insurgency Spread Sheets (MISS). This is all discussed in some depth in my book America’s Modern Wars.
None of these, except the Campaign Data Base and the Battles Data Base (1600-1900), are good for use in a model validation effort. The use of the Campaign Data Base should be supplementary to validation by another database, much like we used it in the Lighter Weight Armor study.
Now, there have been three other major historical validation efforts done that we were not involved in. I will discuss their supporting data on my next post on this subject.
The two large campaign data bases, the Ardennes Campaign Simulation Data Base (ACSDB) and the Kursk Data Base (KDB) were designed to use for validation. Some of the data requirements, like mix of personnel in each division and the types of ammunition used, were set up to match exactly the categories used in the Center for Army Analysis’s (CAA) FORCEM campaign combat model. Dr. Ralph E. Johnson, the program manager for FORCEM was also the initial contract manager for the ACSDB.
FORCEM was never completed. It was intended to be an improvement to CAA’s Concepts Evaluation Model (CEM) which dated back to the early 1970s. So far back that my father had worked with it. CAA ended up reverting back to CEM in the 1990s.
They did validate the CEM using the ACSDB. Some of their reports are here (I do not have the link to the initial report by the industrious Walt Bauman):
It is one of the few actual validations ever done, outside of TDI’s (The Dupuy Institute) work. CEM is no longer used by CAA. The Kursk Data Base has never used for validation. Instead they tested Lanchester equations to the ACSDB and KDB. They failed.
But the KDB became the darling for people working on their master’s thesis for the Naval Post-Graduate School. Much of this was under the direction of Dr. Tom Lucas. Some of their reports are listed here:
Both the ACSDB and KDB had a significant air component. The air battle over the just the German offensive around Belgorod to the south of Kursk was larger than the Battle of Britain. The Ardennes data base had 1,705 air files. The Kursk data base had 753. One record, from the old Dbase IV version of the Kursk data base, is the picture that starts this blog post. These files basically track every mission for every day, to whatever level of detail the unit records allowed (which were lacking). The air campaign part of these data bases have never been used for any analytical purpose except our preliminary work on creating the Dupuy Air Campaign Model (DACM).
There are a few comments from Dr. Paul Davis (RAND) starting on page 13 that are worth quoting:
I was struck through the workshop by a schism among attendees. One group believes, intuitively and viscerally, that human gaming–although quite powerful–is just a subset of modeling general. The other group believes, just as intuitively and viscerally, that human gaming is very different….
The impression had deep roots. Writings in the 1950s about defense modeling and systems analysis emphasized being scientific, rigorous, quantitative, and tied to mathematics. This was to be an antidote for hand-waving subjective assertions. That desire translated into an emphasis on “closed” models with no human interactions, which allowed reproducibility. Most DoD-level models have often been at theater or campaign level (e.g., IDAGAM, TACWAR, JICM, Thunder, and Storm). Many represent combat as akin to huge armies grinding each other down, as in the European theaters of World Wars I and II. such models are quite large, requiring considerable expertise and experience to understand.
Another development was standardized scenarios and date set with the term “data” referring to everything from facts to highly uncertain assumptions about scenario, commander decisions, and battle outcomes. Standardization allowed common baselines, which assured that policymakers would receive reports with common assumptions rather than diverse hidden assumptions chosen to favor advocates’ programs. The baselines also promoted joint thinking and assured a level playing field for joint analysis. Such reasons were prominent in DoD’s Analytic Agenda (later called Support for Strategic Analysis). Not surprisingly, however, the tendency was often to be disdainful of such other forms of modeling as the history-base formula models of Trevor Dupuy and the commercial board games of Jim Dunnigan and Mark Herman. These alternative approaches seen as somehow “lesser,” because they were allegedly less rigorous and scientific. Uncertainty analysis has been seriously inadequate. I have demurred on these matters for many years, as in the “Base of Sand” paper in 1993 and more recent monographs available on the RAND website….
The quantitative/qualitative split is a bugaboo. Many “soft” phenomena can be characterized with meaningful, albeit imprecise, numbers.
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.
[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.]
