Devolving command decisions in complex operations


This note is a shortened and simplified version of an article in the Journal of the Operational Research Society (2013) 64, 17-33, written L Dodd and J Q Smith. For full details, including contact details and references, please see the full article.

Abstract

In contemporary military endeavours, Command and Control (C2) arrangements generally aim to ensure an appropriate regulation of command-decision autonomy such that decision makers are able to act in a way that is consistent with the overall set of commanders’ intents and according to the nature of the unfolding situation. This can be a challenge, especially in situations with increasing degrees of uncertainty, ambiguity and complexity, also where individual commanders are faced with conflicting objectives. Increasingly, it seems that command decisions are being taken under conditions of internal command contention; for example, when the likely successful outcome of a tactical mission can often be at odds with the overall strategic and political aims of the campaign. The work in the paper builds on our previous research in decision making under uncertainty and conflicting objectives, where we analysed the responses of military commanders in decision experiments. We demonstrated how multi-attribute utility theory could be used to represent and understand the effects of uncertainty and conflicting objectives on a particular commander's choices. In this paper, we further develop and generalize the theory to show that the geometrical forms of expected utilities, which arise from the assumption of commander rationality, are qualitatively stable in a wide range of scenarios. This opens out into further analysis linking to Catastrophe Theory as it relates to C2 regulatory frameworks for devolving command decision freedoms. We demonstrate how an appreciation of this geometry can aid understanding of the relationship between socially complex operational environments and the prevailing C2, which can also inform selection and training of personnel, to address issues of devolving command decision-rights, as appropriate for the endeavour as a whole. The theory presented in the paper, therefore, provides a means to explore and gain insight into different approaches to regulation of C2 decision making aimed ultimately at achieving C2 agility, or at least at a conceptual language to allow its formal representation. C2 regulatory agents are discussed in terms of detailed functions for moderating command decision making, as appropriate for the degrees of uncertainty and goal contention being faced. The work also begins to address implications of any lack of experience and any differences in personality-type of the individual commanders with respect to risk-taking, open-mindedness and creativity.

1. Introduction and background

The background for the theoretical work in this paper is an ongoing study of decision making under conditions of internal command contention and situational uncertainty, applied to the domain of military command and control (C2). The theory provides a foundation for the understanding of C2 agility. Therefore, the theory goes further than other military command decision studies, which treat C2 as a process or model the commander as a player in a two-sided game. Nevertheless, the theory has been developed alongside a series of studies and has been supported, hence partially validated, by command decision-making experiments using UK Battle Group (BG) commanders. The experiments presented BG commanders with situations of uncertainty and command contention, such that their courses of action, when seen from a tactical viewpoint, were potentially at odds with the broader campaign objectives. The experiments showed there were several ways in which the commanders dealt with the internal decision conflict:

  • ignore the higher-level command objective completely;
  • explicitly place little or no weight to the higher-level command objective;
  • explicitly place all or very great weight on the higher-level command objective at the expense of risking severe tactical losses;
  • focus attention only on the attributes of the situation that give weight to the course of action that feels most comfortable;
  • create a novel course of action that they hope might satisfy both objectives and might also ‘hedge’ against the uncertainty.

The particular concept around which the theory is set is drawn from UK defence doctrine, which introduced the concept of a C2. As such, the C2 rheostat can be set to impose a top-down form of C2 at one extreme and a totally distributed form of C2 at the other extreme. Mission Command, generally adopted and used by the British military, lies at a mid-position and assumes that command intents are cascaded (usually downwards from strategic to operational to tactical) in a nested set of mission statements. For example, ‘Search and clear area ALPHA and secure roads Y and Z in order to allow safe passage of civilians and humanitarian supplies in order to restore stability in the region’. Such orders are usually limited to stating only the intents of command levels that are two (and at most three) levels apart. It is for this reason that the theory developed here begins with an abstracted two-level problem, simplified to having two C2 agents, one whose role is to meet campaign objectives and the other whose role is to meet tactical objectives.

It follows then that the theory assumes there is a C2 regulatory ‘arbiter’ whose purpose is to determine the level to which decisions can be devolved (eg, decisions can be made without explicit reference back-up the command levels for authority to choose and carry out a tactical course of action). An extreme form of such devolved decision making has been simulated previously for the US Department of Defense and was called an Edge Organization; because all forms of regulatory function and also all decision-rights were unilaterally devolved right down to the fighting elements at the edge). The key function of a C2 regulatory arbiter agent, therefore, is to determine the nature of the conditions (across the situation as a whole) under which decisions are being faced and then to moderate the devolution of decision making appropriately.

2. Introduction to the military problem

The premise for this paper is that military C2 decisions can be devolved to varying levels of decision maker, as appropriate for the prevailing operating conditions. For example, in the United Kingdom through Mission Command it has proved effective to communicate mission orders in broad terms only, and to devolve real-time tactical decision making to an experienced commander who is best placed and well able to appreciate and respond to what is happening on the ground.

This paper addresses the concept of a C2 regulatory agent whose purpose is to understand the implications of devolving decision making given the specific characteristics of the operational context and the conditions under which the decisions are being made. The C2 regulatory agent and the fielded commanders are therefore players in a collaborative game. The responsibility of the regulation of C2 decision making and the devolution of decisions usually resides within the role of a high level of command. (This is so, usually for good reason due to a real need for human judgement based on experience.) Such a C2 regulatory function is traditionally placed at a high level, and often remote position, of command. As such, only some aspects of the geometry of any particular commander's belief and utility functions are known. The work presented in this paper will make explicit what such a C2 regulatory function needs if it is to determine when to devolve decision making (ie, assuming that such discretionary trust can be granted to those who are in closest touch with ongoing events) and when to communicate orders more prescriptively (ie, adopting ‘top-down’ or centralized C2).

In this paper we develop a more formal framework within which the degree of decision ‘autonomy’ can be related, via commanders’ capabilities, to the specific demands of the operational context. We focus on those scenarios that are most difficult to manage: that is, those where there is goal contention (ie, current tactical objectives conflict with broader campaign objectives) and situational uncertainty. This should help to form a basis for development of agents that can perform the C2 arbiter role and it will also provide a formal understanding of what is required to achieve C2 agility.

C2 decision regulation should generally aim to preserve coherence through contiguity; that is, encourage commanders of different battle groups within geographic or operational proximity to choose actions that are tactically and operationally coherent. For example, to try to avoid one commander retreating, while another is carrying out a hasty attack, with potentially chaotic and counter-productive consequences. C2 decision regulation should also strive to minimize command contradiction; that is, to avoid having to face a complete turnaround in a previously made decision

UK military commanders, generally speaking, are expected to act rationally and accountably, within the context of their training and experience. Here, we interpret this expectation in a Bayesian way: commanders should choose a course of action that maximizes their expected utility (or at least tries to minimize their likelihood of loss). Explicitly, we assume that commanders choose a decisive action dD from the potentially infinite set of decision options D available, so as to maximize the expectation of their utility function U. However, it would not be reasonable for a higher command to expect its personnel to try to evaluate and take into account the potential acts of all other contiguous commanders. Therefore, each commander will be treated as if they were an agent within a C2 regulatory framework.

The simplest way to capture the conflict scenario described above is to assume that each commander's utility function U(d, x1) has two value independent attributes x=(x1, x2) with parameter vector λ1, which captures the overall shapes of the commanders’ functions representing their beliefs and preferences related to outcomes. The first attribute measures the ongoing outcome-state of the current (tactical) mission. The second measures the extent to which the integrity of an overall campaign is preserved. The two sets of outcome measures may or may not have common elements; although variables such as number of casualties may be found in both sets of measures but then could be at differing levels of granularity. Under this assumption, for all decisions dD and xiχi, where χi is the sample space of the attribute i (i=1, 2) the commander's utility function has the form

Diagram

where each marginal utility Ui(d, xi1) is a function of its arguments only and the criteria weights ki(λ1) satisfy ki(λ1) 0, i=1, 2, k11)+k11)=1. The rational commander then chooses a decision option d*(λ)∈D—called a Bayes decision—to maximize the expected utility

Diagram

where λ=(λ1, λ2)∈Λ—its possible set of values—and

Diagram

The known vector λ2 will be a function of the hyperparameters defining the commander's subjective posterior distribution—here defined by pi(xi|λ2) of attribute xi, i=1, 2.

We now investigate the extent to which a C2 regulatory agent can ensure that the commander's marginal utilities and criteria weights appropriately address the C2 regulatory principles of retaining contiguity and avoiding—as far as is possible—commander contradiction (and so maintaining overall coherence and balance).

The commander has a free choice of how to set (and adapt) the parameters λ1. However, the observed and appraised commander will have a utility function, which will reflect their understanding of the situation, their mission and campaign objectives. Qualitatively, a commander's courses of action can be classified into three broad categories, attempting to achieve simultaneously—at least partially—both the tactical objective and the broader campaign objectives. Henceforth, we will call this type of decision a compromise. On the other hand, in a scenario where no course of action is likely to attain satisfactory resolution of either the mission or campaign objectives simultaneously, a compromise will be perceived as futile. Rational choice will then need to focus on finding a combative action most likely to achieve the tactical mission objective while ignoring the broader campaign objectives or alternatively choosing a circumspect action—focusing on avoiding jeopardizing the campaign while potentially aborting the tactical mission

3. Rational decisions for competing objectives

3.1 A probabilistic formulation

The commander's decision space D will consist of an open set of possible courses of action but will typically be constrained by many situational factors; for example, the available resources and the rules of engagement of the mission. However, for a wide class of scenarios we will be able to express any course of action d=(d, d1, d2)∈D=D × D1 × D2 where D is a subset of the real line. In this paper, the component d will be a proxy measure for the intensity of the engagement associated with the chosen action. We assume that increasing the intensity of engagement does not reduce the commander's probability of successfully completing the tactical mission but is likely to have a potentially negative effect on the campaign (particularly now that military are involved mostly in stabilization operations). Thus, it is not unusual for a mission to be successfully addressed by engaging tactically with a large and sharp response. However, the intensity of the engagement increases the potential for casualties, both the commander's own unit and to the local civilian population. It is also likely to be increasingly politically deleterious and thus be increasingly to the detriment of the campaign objectives.

For a chosen level of engagement intensity d, a commander will choose, to the best of their ability, between other courses of action d1(d) associated with satisfying the tactical mission objectives given d and between other courses of action d2(d) associated with preserving the integrity of the campaign. Usually, d1 encodes specific tactics involved in achieving the current tactical mission. On the other hand, the decision d2 encodes the judgements involved in securing best use of human resources, preservation of life and retaining political integrity. Both d1(d) and d2(d) will usually be decided by the commander in the field and in response to the developing situation, although informed by protocol, rules of engagement and training. For the rest of this paper, we now assume that it is possible to define the engagement intensity d in such a way that these two subsequent choices do not impinge on one another. Formally, this will mean that a commander's expected marginal utility is a function only of (d, di, λ), (d, di)D × Di, i=1, 2, where . λ is an index that represents the personal, institutional or conditional aspects, such as personal daring, preference, politics, etc.

Now let d1*(d), (d2*(d)) denote, respectively, a choice with the ‘best’ likelihood of attaining the tactical mission objectives and campaign objectives (respectively) for a given intensity d. The assumption above makes it possible to characterize behaviour in terms of a one-dimensional decision space (see below). Figure 1 shows this dimension going from totally benign to super aggressive and also gives an illustration of a typical value plot.

Diagram

Figure 1 Illustrative shape of V values as a function of engagement intensity (d).

3.2 Resolvability

Ideally, a C2 regulatory agent should be adaptive enough to alternate between devolving decision making to the commander in the field and taking a top-down approach prescribing that each commander focus on carrying out actions to achieve one or other of the objectives. There are two scenarios where it is straightforward for a C2 regulatory agent to decide between full-scale devolution and a top-down C2 approach. The first occurs when b1(λ′) a2(λ′). Typically, in such conditions there is no overwhelming drive to be aggressive or purely combative.

We henceforth call this scenario resolvable for λ′∈Λ′ .

3.3 Daring and intensity of action

Fix the value of λ′ and suppress this index. (This is representative of the regulatory agent being aware that it has only what it has in terms of the commanders’ capacities for perceiving and understanding the situation, and this is fixed.) Then, for each d>d ′, d, d ′∈I+(λ′) with the property that P2(d)>0, there exists a large negative ρ such that

 

Diagram

Thus, in this sense as ρ −∞ the rational, accountable commander will choose a decision increasingly close to pure circumspection a2. Such a condition may arise if there is great political pressure being brought to bear on the campaign and the eyes of the world's media are focused upon the decision makers.

On the other hand, for all fixed λ′ for each d<d ′, d, d ′∈I+(λ′) with the property that P1(d)>0, there exists a large negative ρ such that

Diagram

Therefore, as the daring parameter ρ ∞ becomes large and positive, the rational, accountable commander will choose a decision increasingly close to pure combat b1. Such a condition may arise if there is great need for personal daring when a situation demands great courage, for example, to rescue an injured comrade in the heat of combat, irrespective of danger to the decision maker, the mission or the campaign.

4. Discussion

There are several conclusions, concerning C2 regulation, that can be drawn from this analysis about how to organize, train and communicate intent and freedoms for decision making to commanders; indeed, a number of these conclusions are already being accepted as good practice under the principles of command agility. Here, we will assume that commanders face a scenario where both P1 and P2 are twice differentiable and unimodal.

  1. Whenever appropriate and possible, mission statements and campaign objectives should be stated in such a way that they are resolvable so that well-trained rational commanders can acknowledge and safely achieve compromise.

  2. When a situation cannot be presented or acknowledged as resolvable, then, within agile planning to devolve decision making, commanders should be presented with a pseudo-resolvable scenario. The first of two conditions required for this is that the scenario is primal. This means that the commander can perfectly address the campaign objectives while still having some possibility of completing the tactical mission to some degree of success and there is a level of intensity appropriate for attaining the tactical mission objectives, which also can be expected not to totally jeopardize the campaign. It will often be possible to make a scenario primal simply by the way the two objectives are communicated to the commander, although it may involve some innovative option-making. The second requirement is to control the modes of the mission and campaign points so that the intensity with the greatest incremental improvement on mission success occurs at a value ensuring maximal campaign integrity also that the greatest incremental improvement on campaign success occurs at a value ensuring maximal mission. A rational commander will then choose to compromise between the two objectives. The actual compromise point will depend on each commander's individual training, personality and emotional history, but the careful matching of contiguous commanders should help to ensure coherence.

  3. When neither of the two scenarios described above are achievable, then in most cases, provided the mission point is lower than the campaign point, the devolved commander can still be expected to compromise and not to be faced with contradiction. In this case, a C2 regulatory agent must be prepared to expect lower levels of contiguity but coherence can still be managed by carefully considering the commanders’ capacity to deal with stresses. In particular to encourage compromise, mission statements must allow for there to be an option that scores at least half as well as the best option for mission and at least half as well for campaign objectives. Note that if it is made clear that partially achieved success in the two objectives is more highly rated, then the likelihood of compromise is increased.

  4. Problems of lack of contiguity and contradiction can be expected to occur if the mission point is much higher than the campaign point. If a C2 regulatory agent still plans to devolve in these cases, then it must endeavour to keep the distance between the mission and campaign points as small as possible, since this will limit the extent of the discontinuity and contradiction (see the analysis of the last section).

  5. The most undesirable scenarios are those that are unresolvable or pseudo-unresolvable. In these cases, the focus falls on ρ and therefore, unless the intensity associated with pure combat is close to that for pure circumspection, the training, deployment and personality of individual commanders will become crucial. The C2 settings are then most stable if a top-down style is adopted.

5. Further application outside military domain

This work has an experimental foundation in military command decision studies, but it is not limited to situations of military hierarchy and mission command. Indeed, the findings can be applied to any situations where there may be uncertainty and where there is potential for contention in management objectives. Such conditions are common within many organizations today as they struggle to balance risks against a need to expand into new uncertain markets. The two key principles, which underlie the theory, of maintenance of contiguity and avoidance of contradiction are as relevant to management as they are to military C2. Appropriate placing of decision authorities and responsibilities within organizations, according to the prevailing circumstances as a whole, could determine the difference between commercial success and failure.

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