Systems Thinking: Explaining Security Force Assistance in Complex Adaptive Systems

Abstract

This article explores how concepts central to systems thinking better explain how the relationships between advisor and partner force matter in developing and maturing critical capabilities and capacity in the latter thus deemphasizing a foolish consistency to conflate advising with training. Understanding how well a partner force absorbs or does not absorb capacity requires an understanding of systems thinking and this article explores three interconnected themes that are informed by systems thinking: complex adaptive systems; self-similarity; and unintended consequences. Recognizing that the partner force and its institutions function as complex adaptive systems, while understanding how self-similarity in our partner forces may have unintended consequences is the desired outcome that illuminates why advising allies and partners remains important to U.S. strategy.

Introduction

The U.S. Army seems to have an institutional bias against security force assistance (SFA), and this had been made clear recently with the announcement of the reduction of two of its six purpose-built security force assistance brigades (SFABs). This represents a decrease in approximately 33% of the current SFA-related conventional capabilities theater armies have available to support geographic combatant command campaign plans. Yet, the purpose of this article is not to dispute the decision to divest from SFA, but to frame a discussion on understanding the advising mission through a curated review of systems thinking. The discussion will provide an alternative explanation to how we should understand, and thus resource and employ, advisor teams during competition, crisis below the threshold of armed conflict, and armed conflict. That said, this article explores how concepts central to systems thinking better explain how the relationships between advisor and partner force matter in developing and maturing critical capabilities and capacity in the latter thus deemphasizing a foolish consistency to conflate advising with training.

In a simple term, systems thinking is exploring and developing effective solutions by looking at connected wholes, rather than as individual parts separated from the whole, such as in the Iceberg Model. In military parlance, a whole can be thought of as a system containing numerous interrelated actors, such as a foreign government whose ministry of defense has the responsibility for absorbing SFA as part of a wider U.S. foreign internal defense plan. In this case, relationships between civil and military authorities matter as should the relationship between the advisor team and the partner force. This is not because building trust has its own importance, but because of how intersubjectivity, or shared meanings constructed through interactions with each other, defines the desired outcome of the advising mission: whether a partner force is or is not capable of absorbing SFA so that the partner becomes more interoperable with U.S. forces, especially during armed conflict.

Understanding how well a partner force absorbs or does not absorb capacity, as absorptive capacity, requires an understanding of systems thinking and this article explores three interconnected themes that are informed by systems thinking: complex adaptive systems; self-similarity; and unintended consequences. In concluding this exploration, this article will examine a vignette on how systems thinking best explains why U.S. security assistance provided to Colombia, under Plan Colombia, was far more effective that it was in Afghanistan and Iraq, all three of whom experienced insurgencies at the same time.

It is worth mentioning that Plan Colombia, or those components within the Plan that impact the security sector, had been looked at as an exportable model to rebuild the security forces in other failing or failed states, such as in Mexico, where similar conditions of instability exist, and in Afghanistan and Iraq, where the conditions are less similar, but where resources to address instability are in abundance. This initiative, however, would not achieve the desired effects in Mexico, as they would not be achieved in neither Afghanistan nor Iraq, because despite the mixed-results, Mexico is its own non-linear system and the actors within this system respond differently as they would in Afghanistan and Iraq, also non-linear systems. Stated differently, replicating security force assistance activities in countries which tend to exhibit similar characteristics or instabilities exhibited in Colombia ignores the sensitivity to initial conditions that lie underneath, as the Iceberg Model identifies.

Complex Adaptive Systems: Advising in Non-Linear Systems

It is important to restate that the purpose of this article is to review systems thinking as it applies to SFA and not to delve too deeply into interdisciplinary theories, most of which are better understood by those with a mathematical background. Rather, systems thinking is useful in terms of assessing the capability shortfalls in a partner force and this is best framed as understanding the partner force as its own complex adaptive system. Complex adaptive systems consists of actors who interact with each other thus amplifying unpredictability in their behavior over time, which leads to emergence, or how behaviors in these agents are derived from wider interaction among these agents.

Stated differently, a complex adaptive system is really a dynamic network of interrelated agents, in this case, the partner force and its institutions. It is complex because the system is non-deterministic and dynamic, meaning that change among all actors within the system will occur. It is adaptive because these actors, over time, change their behavior based upon their interactions with each other and these behaviors cannot be predicted. Thus, in terms of explaining SFA in complex adaptive systems, the partner force changes its behavior, desired or otherwise, based on its interactions with the advisor team, and its institutions. In some cases, other threat actors that may exist within the system, such as an insurgency or a trans-national criminal organization.

The Army is good at establishing cause-and-effect relationships, often relying on narratives to explain these relationships, but not all causes will produce the same effects and that is why understanding complex adaptive systems matters in SFA. This is apparent in designing significant security cooperation initiatives, which are supposed to tie in SFA efforts into campaign plans. Despite following a logic tree and identifying what inputs achieve desired outputs, the outcomes are not always achieved. This is because there is an assumption, a bias, that certain inputs will achieve a desired output, such as better rifle marksmanship or better rifles will produce a competent security force. This is not to say that better training and equipment eventually produce a competent partner, but the point is that this approach long has followed the narrative that all partner forces require U.S.-led tactics training. Yet, it did achieve desired results in Colombia, but not in Afghanistan and Iraq. This is because each actor is their own complex adaptive system, having their own unique sensitivity to initial conditions. This will be explored further in the Plan Colombia vignette featured later in this article.

It is worth noting that complex adaptive systems are non-linear systems, which means that outputs within these systems are not proportional to the inputs. In military planning parlance the term understanding second and third ordered effects represents non-linear planning considerations. Understanding non-linear systems is useful, especially when tying SFA into strategic security cooperation initiatives, which identify and define specific inputs, outputs, and outcomes as part of geographic combatant command campaign plans. Yet, if systems are non-linear, then so too is the behavior of the partner force.

Finally, no description of complex adaptive systems would be complete without mentioning feedback loops, which is how these systems self-regulate. In SFA, these feedback loops will indicate when and where changes in the partner force needs to occur, but these are not often observed correctly. The formal Department of Defense (DOD) approach to understanding this feedback loop is though their assessment, monitoring, and evaluation (AME) efforts. Yet, AME has not always produced timely or accurate assessments of whether the capabilities in the partner force and their institutions have or have not been developed sufficiently to meet desired outcomes often stated in geographic combatant command campaign plans. This is because AME is an artificial process that does not account for adaptivity in the partner force and is also why system thinking needs to be part of this process. This brings us to the topic of self-similarity, which can be used to explain why or why not partner security forces look or behave the same as their U.S. counterparts.

Self-Similarity: Recognizing Fractals and Avoiding the Fabergé Egg Army

In mathematics, fractals are geometric shapes that contained detailed structure at smaller scales, but appear similar at larger scales, such as frost crystalizing naturally on a cold, glass pane forms fractal patterns. This is an indicator of how similar characteristics appear to be present from afar, but upon closer inspection these characteristics are, in fact, not similar at all. In SFA, however, fractals, as a display of self-similarity, are also found within the partner force, especially when a partner force is trained and equipped based on a U.S. model which has proven, at least in Afghanistan and Iraq, to be unsuitable to U.S. policy objectives. That is, when viewed from afar, Afghan security forces, for example, appeared to mirror its U.S. counterpart in uniform, equipment, and tactics, thus appearing to be a capable security force, but when viewed up close, the shortfalls in capability and capacity became evident.

In Afghanistan, this phenomenon is captured in a metaphor known as the Fabergé Egg Army, where the U.S. and NATO built a modern and well-equipped Afghan military, one that looked elaborate and expensive, but lacked resiliency and shattered under the slightest pressure from the Taliban after U.S. forces left Afghanistan. This happened because the U.S. did not apply systems thinking in assessing absorptive capacity of the Afghan forces. For example, the will to fight is a key fractal that informs the absorptive capacity of a partner. Overlooking this, or numerous other systematic characteristics, demonstrates the importance of systemic thinking over photocopying only a few easy to replicate outputs. It is important to see the fractals – not just the big picture.

It may be fair to say that getting decades of assessments of Afghan forces wrong is perhaps why the U.S. seems to be divesting itself of its SFA capabilities. It may also be fair to say that the U.S. is willing to assume risk with advising missions, preferring instead to surge this capability when needed, but this is flawed thinking. It is flawed because advising, more so than training, requires relationships and intersubjectivity to recognize the fractals for what they are, which leads to more accurate assessments of a partner force thus avoiding the repeated mistake of building a Fabergé Egg Army.

Unintended Consequences: Flawed Thinking Has Far-Reaching Effects

The concept of unintended consequences is not new, but consequence can be misleading in context. Consequence is simply a result or an effect of an action or condition. Yet, it is often quoted that actions will have consequences, which, while being true, tends to evoke a negative connotation. Rather, the meaning of unintended consequences in systems thinking implies neither good nor bad outcomes, as good and bad are artificial social constructs, but simply an effect of an input. For example, at Bagram Air Base in 2012, copies of the Koran were mistakenly burned, which led to violent protests throughout Afghanistan and ultimately required a public apology from then-President Barrack Obama to off-ramp hostilities. Stated differently, the routine of burning trash one morning in February 2012 had considerable far-reaching effects for the U.S. relationship with Afghanistan, which by this time was in decline.

For SFA, unintended consequences tend to be less dramatic, but still highly amplifiable if sensitivity to initial conditions are not considered by theater army planners or advisor teams. In some cases, as was the case in both Afghanistan and Iraq, training the partner force as an input will not always produce the desired output, which could alter the timeline to achieving the desired strategic outcome. This is why systems thinking in the SFA enterprise needs to become ubiquitous and why it is now appropriate to map systems thinking in terms of Plan Colombia and its outcomes.

Explaining Plan Colombia Through Systems Thinking

Plan Colombia was a strategy that was originally introduced in 1999 by Colombian President Andrés Pastrana to end cocaine production and insurgency in Colombia. The Plan had ten components, which addressed different sectors of governance, such as military capacity building, justice and social reforms, and regional economic resurgence. The Plan called for up to $7.5 billion dollars over a six-year period to reach its stated objectives found in each of the ten parts of the Plan. Yet, the cost was much higher and the timeline to reach some of the stated objectives took at least two to three times as long to meet, giving pause for analysts to determine that the Plan had only achieved mixed results. By 2016, insurgents largely demobilized and rejoined civil society, but some hard-liners remained in protest to the Santos government. Despite the dismantling of insurgent groups, a decrease in violence, and human rights violations, Plan Colombia is a non-exportable strategy. Stated differently, in some sectors U.S. assistance was able to achieve desired outcomes, but Plan Colombia is largely a strategy that would not work in nearby Mexico, where similar conditions exists, or in other contested countries such as Afghanistan and Iraq, where conditions were seemingly similar, but quite different once encountered.

Systems thinking would arrive at similar, if not the same, conclusions. The systems thinking concept of self-similarity led to a failed understanding of why increased homicide rates occurred in Columbia post plan implementation. The breakup of the Medellín and Carli cartels in the mid-1990s altered the status quo conditions in Colombia which dissipated the drug trade into smaller and less powerful actors. Actors adapted to the absence of a hierarchy by understanding the sensitivities of initial conditions of this system, its place within the international drug trade, and the balance of power in the drug trade. This created the conditions for Pablo Escobar and Gilberto José Rodríguez Orejuela to gain influence. This self-similarity and had an amplifiable unintended consequence of an increase in homicide rates in Colombia, peaking around the time the Plan was implemented. Because the drug trade exists as a non-deterministic system, this behavior could not be predicted, meaning conversely that a cause-and-effect explanation is inadequate. Escobar’s death would mean an increase in homicides in Colombia requiring U.S. military assistance. Thinking purely in terms of cause and effect was not sufficient because the indicators within this system were, at that time, less understood.

Failing by thinking in terms of cause-and-effect, rather than in in terms of a dynamic ever-changing systems also led to inadequate assistance following the collapse of the Soviet Union. The insurgency in Colombia had been more mature than those found in Afghanistan and Iraq. Since the mid-1960s, left-wing insurgent groups in Colombia had enjoyed Soviet patronage, but what is most interesting to observe is that the Soviet Union collapsed around the time the Colombian cartels became toothless. Some analysts would argue that this was a victory for the U.S., but they would miss the point that the international system became imbalanced and the actors within this system altered their behavior to change the system back towards status quo. In Colombia, this meant that communist-inspired insurgent groups like the Revolutionary Armed Forces of Colombia and the National Liberation Army needed a new source of funding and without hierarchy, the drug trade needed new leadership that only armed groups could provide. It is possible that analysts could have predicted this behavior, as cause-and-effect, but it is more likely that this prediction would have been dismissed because drug use and production, the thinking goes, would have been counter to a Marxist ideology found widely among Colombian insurgent groups.

Finally, systems thinking explains the Plan in terms of non-exportability. The sensitivity to the initial conditions found in Colombia are unique only to Colombia. Yet, the U.S. tried to model its counterinsurgency efforts from Colombia in Afghanistan and Iraq but achieved less than optimal results. This is because each state, failing or failed, is still its own complex adaptive system and the actors within each system behave according to their own needs, which is to say that what motivates al-Qaeda in Afghanistan is not the same motivation as al-Qaeda in Iraq, which systems thinking would assign them as two separate actors. Had the two-part Plan worked in Afghanistan or in Iraq, it still would not have worked in Mexico, despite the assumption from then-Homeland Security Secretary John Kelly. Mexico has a lot of issues with instability, but an insurgency is not one of them.

Conclusion

This article reviewed concepts of systems thinking and will now make recommendations for the Army and the DOD to consider. Recognizing that the partner force and its institutions function as complex adaptive systems, while understanding how self-similarity in our partner forces may have unintended consequences is the desired outcome that clarifies why advising allies and partners remains important to U.S. strategy. If the four remaining SFABs are expected to do more capability and capacity development with partner forces and with less resources, the Army will need to encourage systems thinking in its institutions and across its operational force. Below are three recommendations to provoke and drive Army change:

• Systems thinking as a heuristic decision-making model should be expanded into Army Professional Military Education. The intent is not to replace the Military Decision Making Process or the Army Design Methodology, but to add into planning a more disciplined approach that looks at the connections between the actors within any given system. If implemented, for example, recent staff college graduates newly assigned to theater armies will have learned non-linear perspectives and will have advanced their problem-solving skills beyond predictive analysis because they can now understand that simple cause-and-effect in non-deterministic systems is difficult to predict without understanding the relationship between the cause and the effect. There is a similar recommendation made on institutionalizing systems thinking in Chapter 4, page 21, of the Center for Army Lessons Learned (CALL) handbook Understanding Irregular Warfare.

• Systems thinking needs to be applied to current and future AME efforts. Despite being identified as a requirement in DOD policy, AME efforts in geographic combatant command campaign plans have been largely underreported. Yet, in recent reporting from the DOD Office of Inspector General, it has been observed that even the purpose-built SFABs have not done enough to tie their advising missions into campaign plans. To be fair, not all advising missions have a reporting requirement that necessitates this requirement, but if the 33% reduction in the SFABs is an indicator of their measures of performance or effectiveness, both SFABs and their theater armies will need to adapt to a formal, structured assessment framework. Systems thinking, when applied to AME, supports the current process because of its focus on how indicators best predict behaviors in the system, meaning that without understanding the relationship between the input and the output, only chance or randomness determine if the output is indeed desired. Stated differently, systems thinking provides a more effective assessment framework in determining if a partner nation is absorbing the capacity that the U.S. attempts to build in partner forces and their institutions. This all said, AME is an important function in security cooperation and CALL’s handbook on Understanding Security Cooperation discusses this process in its own stand-alone chapter.

• Similar to AME, systems thinking needs to be applied to institutional capacity building (ICB) efforts. ICB efforts are Congressionally mandated to be part of §333 capacity building efforts in the partner force. This is rational because the failures in the partner forces in Afghanistan and Iraq were largely institutional, meaning that no matter how much capability is developed, a partner force that lacks the capacity to absorb these capabilities will neither mature nor endure. Because ICB is tied into campaigning, it is crucial to show the relationship between inputs and outputs. That said, hosting a block of instruction on human rights and rule of law does not, and should not, equate to an increase in institutional resiliencies. More indicators are needed, and systems thinking encourages mapping beyond simple cause-and-effect linkages or narratives.

Final Thought

Systems thinking is not easy to comprehend, at least initially, but when the core concepts become clearer then unbiased discussions on how to rethink the U.S. approach to security force assistance may begin. If the three recommendations are feasible, then it is logical to believe that systems thinking can be implemented across the DOD hierarchy, which is to further say because the DOD is itself a highly complex adaptive system. Now is not the time to reduce SFA capabilities, but it is the time to rethink in systems how the U.S. better employs these capabilities in non-linear systems.