Air power represents the abilities of a nation to project military force in the third dimension. Traditionally this ability has centred on an air force, although such an emphasis does not preclude augmentation by specialist capabilities which could include naval and army air arms, civil aviation capabilities and space based systems.
In Australia, air power is generated in three air arms, viz, the Royal Australian Air Force (RAAF), the Fleet Air Arm and Army Aviation. Development of capabilities for these arms follows a structured five step process:
- capability planning;
- authorisation of capabilities;
- introduction of new capabilities (including modification of existing capabilities);
- operational employment of extant capabilities; and
- withdrawal of redundant capabilities.
Activities a to c and e comprise a set of complex, interactive planning and management processes which cannot be optimised using conventional staff procedures. Similarly, performance evaluation and control of item d have been the subject of study for several years but have not been formalised satisfactorily. A methodology is required which would optimise the development of air capabilities across all air arms.
Terms of Reference. Chief of Air Staff (CAS) directed that Air Power Studies Centre (APSC) study the generation of air capabilities by the Australian Defence Force (ADF); the terms of reference for the study are at Annex A.
Ultimately, this and subsequent studies should lead to a system specification for development of a predictive model of the capabilities development process; the model is needed to provide a vehicle for the embodiment of all knowledge and experience relevant to air power generation. Codification of that knowledge in a form which reflects strategic environments, national objectives and command systems would then afford better control of the process that produces air capabilities.
Capability Defined. The ADF defines five terms of immediate relevance to the development of air capabilities; they are military capability, force structure, preparedness, operational readiness and sustainability. The ADF defines military capability (MC) as the composite of force structure (FS) and preparedness (P) through which a nation exercises combat power. Symbolically:
MC = FS + P (1)
Force structure is defined as:
‘military disposition, strength and physical, operational and technical characteristics’; and
‘either the force in being or that planned component of military capability’.
Preparedness is the composite of operational readiness (OR) and sustainability (SB) which ‘taken together [are a measure of] the ability of a given force structure to generate and maintain combat power for a designated period’:
P = OR + SB (2)
Consequently: MC = FS + OR + SB (3)
Operational readiness is defined as the states of a designated force (e.g. a force element group, a force element) [i.e. force structure] with reference to its operational level of capability and notice for operations and comprises:
equipment on hand, including weapon systems, [i.e. force structure] expendable supplies and materials, and other stores;
equipment condition, with respect to its technical serviceability and state of maintenance;
During the training phase, considerations of operation readiness are only as useful as the relevance of the latter’s measurement. Consequently, measures of operational readiness should be based on the strategic objectives that are developed and authorised during the planning phase. A feedback system which communicates measures of operational readiness from the employment level to the planning level is required.
Sustainability is defined by the ADF as ‘the ability of the support system to satisfy for a designated period the operational demand arising from the usage if ammunition, spares, etc, and from the attrition of equipment and personnel in the exercise of combat power’. Sustainability is determined by the capacity of the sustainment functions.
Optimisation of Resource Allocation. Relationship 3 above indicates the three principal elements between which resources must be allocated to ensure balanced development of military capabilities. A similar relationship exists for air capabilities. Optimising this resource allocation is the principal task of the force development process; a predictive model of air capabilities should facilitate that optimisation.
The need to align strategic objectives with resources optimisation, operational metrics, and appropriate feedback mechanisms largely dictates the approach to be adopted in developing the model. In particular, the method by which an air capability is generated should be separated from the feedback mechanism to allow a clear structure to be developed. Planning of the generation of air capabilities would then focus on the integration of force structure with sustainment functions (as illustrated at Annex B) and on the balance to be struck between those elements and preparedness. The feedback process (which would communicate measures of operational readiness to the planning function) would be a product of the command and control arrangements for the employment of air capabilities.
Nature of Command. Command is the legal authority accorded an executive to facilitate his control of air power assets in the pursuit of military objectives. In this context control is the art of steersmanship and has historically been exercised largely on the basis of expert judgment.
Nature of Control. Control of a system may be defined closely as the regulation of system performance using formal mathematical or algorithmic descriptions which may permit automation trough the medium of a computer. For those systems which are complex and as yet are not amenable to formal description, control may be exercised informally through management. In the intervening field between formal control and management lies the judgement of experts.
Control of the development of air power capabilities is amenable in part to formal description and in greater measure to expert judgement. The aim of this paper is to determine how expert judgement and formal descriptions may be brought together through the medium of models, automated tools and appropriate command structures to provide better control of the air power development and employment processes.
DEVELOPMENT OF CAPABILITES
Planning New Air Capabilities
Strategic Background. Strategic planning frequently takes as its foundation expressions of the national interest and proceeds linearly to develop grand strategy, Defence policy and air power. Implicit in this approach is a need to account for a wide range of possible future environments, for the impact which present decisions could have on those environments, and to provide for outcomes which are beyond Australia’s influence. Possible futures have two elements in common: there are usually features (core features) common to each of the environments, and some other elements which are susceptible to influence by Australia. The balance of futures consists of exogenous contingencies (Annex C).
The core features are the environmental stabilities, which give rise to a core strategy (Defence in Depth). The core strategy is supplemented by an environment shaping strategy which aims to shape the security environment in beneficial ways (Strategy of Influence). The environmental strategy alone is not capable of completely shaping the future environment; consequently less suitable contingencies could arise. To handle the more probably of these contingencies a hedging strategy is required. The hedging strategy copes with external contingencies in so far as the core and environmental strategies cannot control them.
Implementation of an environmental strategy reduces risk through the reduced range of possible future environment which result. Similarly, preparation of a hedging strategy greatly reduces risks from sources which otherwise would be little understood and the consequences of which would not otherwise have been considered. To a certain extent hedging strategies which are manifest as contingency plans, can substitute for environmental strategies, but the former are based on hypothetical incidents. Consequently, although contingency plans can be large in number they are likely not to be knit together by an overarching theme as in an environmental strategy.
In summary, the elements of Grand Strategy which are needed to inform Defence Policy and subsequent development of military capabilities are:
a core strategy;
an environmental strategy; and
a hedging strategy.
Defence Policy. Defence Policy is authorised at the Grand Strategic level and focuses on those elements of the three component strategies of direct relevance to the armed forces. The guidance provided by Defence Policy is necessarily broad, informing as it does the entire Australian polity. Cost-effective development of military capabilities requires endorsement of more detailed policy which takes Defence Policy as its framework and produces a plan which matches means to ends, i.e. a military strategy. Within Department of Defence such endorsed policy does not exist; rather, Defence Policy is interpreted through Strategic Guidance, single Service doctrines, a set of Operational Concepts for each principal defence environment and a Concept for Operations for each Force Element Group within each environment (Annex C).
Operational Concepts. An Operational Concept is defined as the method of achieving the aim in a defined area of operations, covering the types of forces and their equipment required, and determining where possible the force mix necessary for the conduct of operations. Operational Concepts are developed primarily for force development purposes and should be distinguished from:
Concepts of Operations which relate to an actual operation or series of operations by nominated forces; and
Contingency Plans developed by HQADF or subordinate commanders for the employment of the force-in-being on operations.
The objectives upon which the development of Operational Concepts are based include:
provision of an objective ADF basis for the examination and establishment of future force structure and equipment proposals;
provision or recommendation on key defence issues which will provide guidance for further development of the operational concepts work as part of a continuing process;
establishment of the requirement and provision of guidance for more specific work on particular aspects of force development; and
provision of the bridge between strategic assessment and force structure plans.
The current development process for Operational Concepts includes the following:
definition of the role to be performed;
specification of tasks within the role;
description of the conditions influencing performance of each task;
specification of the desired standards necessary to achieve tasks; and
a description of how tasks could be performed.
ADF Operational Concepts are produced within the constraints of strategic guidance i.e. against the characteristics of Australia’s geostrategic environment and within the bounds of credible contingencies. Nevertheless, development of Operational Concepts without the benefit of an endorsed overarching Military Strategy carries a risk that the concepts might not lead to suitable integrated capabilities.
Concepts of Operations. From the Operational Concepts are distilled the Concepts of Operations and the operational requirements of force elements. The statement of capability in each operational requirement should be directly traceable to military objectives.
Development of the concepts, operational requirements and operational readiness criteria is leavened by the force planner’s expert judgement and experience of military operations, i.e. by application of air power doctrine.
Air Power Doctrine. Experience gained in several wars has shown that certain principles should be observed to ensure successful use of air power. Thee principles have been codified in The Air Power Manual and may be summarised as follows:
Air power should be applied in three concurrent campaigns – control of the air, independent bombing, and support for combat forces.
Certain broad operational capabilities are required to effectively prosecute each of the campaigns. Within these capabilities specialised roles may be defined.
Continuing effective prosecuting of the campaigns requires that operational capabilities be supported by sustainment capabilities which consist of many supporting roles.
An air strategy (as a component of an overarching military strategy), requires that operational and sustainment capabilities be applied to the three campaigns and integrated matrix fashion as illustrated in Annex D. Application of these capabilities to three principal campaigns within the air strategy broadly follows the well established Principles of War. A graphical illustration of an application of the campaigns in a generic strategy is at Annex E.
Operational Tempo and Readiness. In any particular war strategy, the operational tempo required of each role during each campaign would be assigned to the appropriate cell of the campaign matrix in Annex D. In time of peace, training rates, operational tasking rates and sustainment effort for each of the roles would supplant wartime rate of effort, while the readiness for each role would be determined by the core, environmental and hedging strategies of National Security Policy (Grand Strategy) as amplified by Defence Policy and further interpreted by the iterative committee process. Readiness requirements would be specified in the Chief of the Defence Force’s Operational Readiness Directive (CORD).
The manner in which capabilities and sustainment functions are applied to each element of air strategy influences the force planner’s interpretation of strategic guidance and shapes operational concepts, concepts of operations, and operational requirements.
Current Capabilities Planning Procedures
The higher level inputs to the air power planning process are therefore, the three elements of what should be military strategy (the core, environmental and hedging strategies) as they are reflected in the operational concepts, concepts for operations for the air environment, and the forecast resource allocation of the FYDP and TYDP process. Planning for development of air power capabilities takes these inputs as its starting point, as shown in Annex F.
The first step is to determine whether a new capability is needed to satisfy the demands of the operational concepts. Should a new capability be needed, the next step would be to identify options which would provide an adequate capability. After selecting the most suitable option, an approximate representation of the new capability in its mature form would be prepared, and used to determine the sustainment functions and resources needed. The new capability and its sustainment needs would then be considered in the context of all other capabilities to determine:
the impact of the new capability on all sustainment functions;
the need to compromise existing capabilities to remain within prescribed resources (sustainment) constraints;
the potential to satisfy operational and other policy requirements;
the extent of additional resources needed to support the proposed and extant capabilities; and
the cost, including total cost and sustainment costs apportioned by individual sustainment function.
Requirement for Automated Planning Tools
Existing staff procedures allow preparation of approximate workable solutions which are developed in conjunction with relevant Service Offices and functional commands. This process produces, inter alia, estimated sustainment requirements but these usually do not reflect the internal dynamics of the sustainment and operational functions. The volume of information needed and the intensity of computation required does not at present permit determination of optimal plans. Consequently, when proposals for new capabilities are approved and implemented, dislocations in sustainment functions and concomitant cost overruns may occur. An unavoidable consequence of these dislocations is the development of either a lesser capability than planned, or an adequate capability at a higher cost. There is a need for some form of automated assistance for the force planning staff; that assistance could include a suite of computer based models of capabilities (force elements and sustainment functions), a high level project planning tool, an optimal resource allocation tool and supporting operations research methodologies.
The principal steps implied in the force development process outlined above are identification of shortcomings in capability and formulation of a proposed solution to the shortfall. A proposed solution requires a representation of the new capability in its mature form complete with doctrinal processes and command structures that would ensure its effective use. Development of an optimal form for the new capability demands analysis of the interaction between that capability and an appropriate range of operational environments and futures. Analysis on this scale cannot be achieved using conventional staff procedures but could be performed using a structured suite of models and automated tools.
When assessing the impact of new or changed capabilities, the force planner needs to determine the sustainment requirements of each proposed capability in the context of existing capabilities (Annex F). Also, the planner requires concurrent optimisation of planned and extant capabilities. To date no suitable automated tools have been available to the force planner.
The proposed models and automated tools should permit the following:
matching of proposed capabilities to military objectives;
representation of all planned and existing capabilities;
representation of all capabilities by sustainment requirements (inputs) and operational effectiveness (outputs);
representation of all available sustainment functions by functionality, resource availability and cost;
calculation of sustainment requirements of each capability (existing and proposed) by resource type and cost;
when necessary, reallocation of sustainment resources across all capabilities (proposed and existing) to ensure a prescribed balance of capabilities; and
assessment of the impact which a change of capability could have on the schedule of sustainment functions which support planned and existing activities.
Requirements a to e above might be satisfied by a resource scheduling tool. Item g appears to need a detailed simulation of some key sustainment processes.
In summary, the force planner requires a generic form of capability simulation and resource scheduling with which to test the consequences of each new capability, while simultaneously working with integrated (sustainment and effectiveness) simulations of existing capabilities.
Authorisation of New Capabilities
Authorisation of new capabilities is administered in accordance with Defence Instruction (General) 42-1 and will not be considered further here.
Introduction of New Capabilities
Once approved, new projects are implemented through special project offices, and, in the case of Air Force, when initial operational capability is deemed to have been reached the new air capability is transferred to Air Headquarters. Introduction of new capabilities draws mainly on conventional project management techniques for which adequate automated tools are readily available. Nevertheless, during the approach to initial operational capability, the new project will draw increasingly on sustainment functions which should be apportioned optimally across the entire force. Scheduling of the rate of increase of these functions in support of the new and existing capabilities would be determined during the planning phase, and updated progressively as the capability is introduced. Management of sustainment resources during this phase could require similar automated tools to those used in the planning process; these requirements need further study.
Employment of Capabilities
Effective employment of air capabilities is dominated by the command decision making process, by the strategy adopted in applying those capabilities, and by the efficacy with which sustainment functions are applied to elements of the force structure.
Command and Control of Air Capabilities. Commanders of air operations are charged with achievement of the air component of military objectives. In pursuing those objectives commanders compete with the capabilities of the enemy. In this competition the dominant factors are the rate at which effort can be generated and the accuracy with which that effort is focused. Two other factors are essential to success, they are adaptability and resilience of the command and control organisation. When designing command and control arrangements for air operation the aforementioned requirements must always dominate:
rate of capability generation, and
focus of air effort.
Optimising Adaptability and Resilience. Adaptability is defined as the capacity to reallocate resources and modify practices to ensure achievement of objectives. Resilience is defined as the ability to continue to attain objectives when part of an organisation has been disabled. Adaptability is an essential characteristic but is not inherent in every organisational structure. At Annex G the nature of organisations is examined from first principles and an underlying structure is deduced which should ensure adaptability under the most demanding conditions. The structure is termed cybernetic from the science upon which it is based.
The important considerations which the cybernetic approach identifies include:
Commanders at each level of an organisation must be provided with clear objectives, adequate resources and clear policy constraints.
The operation of each organisational unit, regardless of level, is based on a closed loop feedback process. Feedback consists of a measurement of achievement against objectives and of changes in the operational environment.
The objectives for each level of the organisation must be stated in terms which permit rapid and accurate assessment of operational performance against those objectives. Where possible the objectives should be stated in quantified terms. In peace time these objectives should relate directly to appropriate elements of the CORD.
The commander (controller) is an integral part of the control process in that he learns (adapts) as the unit works towards its goals.
The rate of effort of the unit does not of itself determine the eventual success (achievement of objectives) by the system; success is determined by the efficacy of the feedback network which includes the staff function (i.e. the function which determines the focus of the effort).
Information concerning the operational environment and task results must be obtained, correlated, analysed and forwarded to the staff function in a timely fashion.
The staff function must be capable of interpreting the significance of all divergences from objective criteria in terms of policy, sustainment requirements and rates and of effort.
All elements of the system (command, operational, staff and communications) must be capable of adaptation (learning) and the experience of adaptation must be retained as corporate (system) memory, lest the adaptation process be forever repeated.
Speed of communication within the system and to higher level systems will be determined by the dynamic nature of the operational environment; for most operational conditions this means near real time.
Lower level organisational elements are nested within higher level units; each unit being a self regulating system capable of autonomous operation should communication with higher level units be lost temporarily. Nesting affords organisational resilience.
A generic form of cybernetic command and control structure which should ensure optimal adaptability and resilience is at Annex H. The current command structure within Air Command provides a framework which reflects all of the salient principles of command of air forces as discerned from operational experience to date. Some minor modification of information and control procedures and of methods for retention of corporate memory should ensure the achievement of an adaptable and resilient system based on cybernetic principles. The issues which require further study in this regard are:
expression of objectives at all organisational levels, particularly peace time objectives;
development of performance metrics, including those needed for elements of preparedness as defined earlier;
collection, correlation and assessment of operational information;
retention of expertise i.e. or corporate memory; and
adequacy of communications in view of the requirement for near real time communication of a to c above.
Optimising the Decision Cycle. The decision cycle consists of information collection, correlation, assessment and planning of task details; the latter activity determines the focus and allocation of effort. Information collection starts with an accurate assessment of task achievement and integrates all relevant intelligence on the battlefield. The principal requirements of this task are accuracy and speed; in this regard considerable work remains to be done in providing for real time mission assessment (especially bomb damage assessment), integration of intelligence from divers sources and correlation and assessment of the composite information base. Particular requirements here are the need for standardised information formats for transmission between elements of the decision process. Standardisation is essential to minimisation of the time required to prepare information for input to automated decision aids such as expert systems, models, and sustainment and mission planning tools. Efficient planning aids would be of little use if time needed to prepare input information resulted in a decision cycle longer than that of the enemy.
Correlation of intelligence and mission information has long been the preserve of expert judgement. Although judgement cannot be dispensed with, there are opportunities for the development of automated systems which formalise expert knowledge and allow increased speed of intelligence processing in specific (usually narrow) knowledge domains. Application of improved communications, mission reporting, standardised information formats and automated information handling and knowledge based systems should allow achievement of effective information fusion for the decision making process. The study of fusion processes should be accorded a high priority.
Assessment of the rate of progress against assigned objectives and planning of operations will probably remain the province of expert judgement for some time. However, the hardware capability mow available for simulation of force engagements based on near real time intelligence information could enhance those judgements in terms of accuracy and timeliness. Essential prerequisites are high speed information input to the simulations, and automated tools which reduce the time and cost of developing simulations. High speed input should be possible given suitable standardisation of data formats between simulations and intelligence systems. Suitable automated tools already exist.
Determining an optimal allocation of effort during each decision cycle would require, inter alia, parametric modelling of a range of operational futures to determine a robust set of resource allocation priorities which could satisfy the objectives. Further study is required of simulation support to operational decision making. More generally, a study of the decision cycle as a system would illuminate more clearly the critical functions and support requirements.
Optimisation of the Mission Cycle. The mission cycle consists of mission planning, weapon system preparation and mission execution. The latter is not a variable which is easily reduced; consequently, the optimisation process simplifies to reduction of the time required for mission planning and weapons system preparation. Until recently mission planning has been based on expert judgement; however, it is a well defined information domain and therefore is amenable to automation through use of expert systems and similar tools. Given the complex nature of the modern battlefield, considerable reduction in the time required for planning could be achieved. Reduction in the planning load could release crews for higher mission rates thereby increasing the rate of effort available to the commander. Some examples of mission planning systems are available commercially. Further study of the trade off between planning systems, crew availability and crew proficiency is required.
Weapon system preparation consist of all functions necessary to support a task. The efficiency of this function depends on sustainment crew efficiency i.e. on the activity level and usage rates during peace time, and on the degree of sustainment which has been planned and provided to the unit. Similarly, weapon system crew proficiency depends on activity levels during training. Sustainment and training will have been accomplished during each time; all that may be optimised during the early stages of a conflict is the day-to-day employment of sustainment functions. Considerable scope exists for automating the resource scheduling and deployment requirements; further study of these functions as part of the operational sustainment system is required.
Withdrawal of Redundant Capabilities
When a capability is deemed redundant, its withdrawal from service would be balanced by a concomitant reduction in sustainment. In many cases there would be a parallel introduction of new capabilities taking place, and new forms of sustainment would be generated to support the new capability. These concurrent withdrawal and introduction processes would utilise similar tools.
MODELLING – FOUNDATIONS AND APPLICATION
So far reference has been made to the use of automated tools, simulations and models in support of planning and command processes. Before more detailed discussion of these applications is entertained an outline of the foundations of and constraints to the application of modelling is required. The aim of this section is to establish an appreciation of the potential of modelling to assist in the planning and employment phases of the air power development process. The outline examines fundamental concepts then addresses the demands of the modelling of complex systems such as air power generation. A brief history of the modelling of air power processes is then presented. The next section addresses the application of models of complex systems to the process of the latter’s control.
Foundations of Modelling
Definition of Modelling. Modelling is a way of manipulating things or situations that are too costly to deal with directly. Any model may be characterised by three essential attributes:
Objectivity – it is an abstraction of something (its object).
Purpose – it has an intended cognitive purpose with respect to its object.
Cost-effectiveness – it is more cost-effective to use the model for this purpose than to use the object itself.
A model then represents an object cost-effectively for a particular cognitive purpose.
Theoretical Considerations. Effective use of modelling requires thorough analysis of the system to be modelled and careful matching of the model to its purpose. Before proposing construction of a model of any type it is essential to understand the modelling process, to assess the advantages, disadvantages and limitations of its different forms, to establish the purpose of the proposed model, and to identify the most suitable class model for the present purpose.
Purpose of a Model. The object and purpose of a model must be well defined otherwise the design criteria could be inappropriate; also, the object of a model must be testable in order to serve as reality for the model. The purpose of a model may include comprehension or manipulation of its object, prediction, goal direction, definition and explanation of the interaction of the object with its environment:
Prediction. Prediction corresponds to asking questions of the form ‘What if…?’, where the user asks what would happen if the object began in some initial state and behaved as described by the model.
Goal Direction. Goal directed analysis is concerned with finding an initial condition of the object that can lead to a given result.
Definition. Definitive analysis determines whether certain states, conditions or actions are ever possible for the object.
Explanation. Explanatory analysis seeks to explain the behaviour of the object by showing how some state is reached.
Application of a Model. Intelligent use of a model is not possible unless its purpose, characteristics and constraints are fully understood. If a model is constructed without clearly specifying its intended purpose and limitations, the likelihood of its misuse is high. Such misuse could have dire consequences if decisions are based on false predictions or understanding.
Cost-effectiveness. Purpose is a necessary but insufficient definition of a model. A model must also be more cost-effective for the given purpose than its object, either because it is impossible to use the object directly or because using the object would be inconvenient, or more expensive in some relevant metric. The cost-effectiveness of a model must be known in order to judge the model’s value; judging cost-effectiveness requires answering the following:
Is the purpose of the model appropriate?
How will the purpose of the model evolve over its lifetime?
What is the cost of developing and maintaining the model throughout its life?
Will the model’s effectiveness pay for the cost of building and maintaining it?
Manifestations of Models. Models may be described in terms of their form although such classifications are subjective. For example, models may be described as physical or symbolic; physical models may be further classified as iconic or analog models, whereas symbolic models may be thought of either as strictly mathematical or conceptual. Mathematical models may themselves be classified as continuous versus discrete, and as deductive (proceeding from a prior knowledge or axioms), inductive (generalising from observed behaviour), or pragmatic (relying on a means-end oriented engineering approach). Analytic techniques (for which closed form solutions exist permitting optimisation) are sometimes contrasted to numerical (approximation) techniques. The formality of analytical techniques allows limited representation of the real world. Explicit computerised models (compared to implicit mental models) offer potential advantages including rigour, accessibility, comprehensiveness, logic and flexibility.
Functional Characterisation. The criteria of purpose and cost-effectiveness for that purpose together determine which features of the object must be modelled and with what accuracy, and which features can be ignored. These criteria provide a complete functional characterisation of a model. In addition, they determine a number of key characteristics such as who the intended users of the model are and how the results of using the model must be presented in order to be understandable by those users. For a model to fulfil its stated purpose cost-effectively, it must be appropriately useful to useable by its intended users.
Types of Models. There are many ways of modelling a given object. Any given model has strengths and weaknesses depending on its fidelity, utility, effort required to use the model, and pragmatic considerations including its suitability for various kinds of users and its maintainability. Although a given type of model may tend to have certain characteristics, there are no invariant rules about which types of model display particular strengths and weaknesses.
Broadly speaking, the ADF requirements for modelling the development of air power include comprehension, planning, prediction and manipulation. These requirements could be satisfied by interactive simulation and resource scheduling. Simulation is an active, behavioural analog of its object. The essence of simulation is what unfolds over time; it models sequences and possibly timings of events in the real world. Simulation is a process in which a model of any kind is used to imitate some aspect of the behaviour of its object. Simulation is a kind of modelling rather than a kind of model; it denotes a process rather than a thing and is generally used to answer what-if questions. It can also be used to answer questions of causality by generating a sequence of events from which one can infer cause and effect. Ideally, the simulation should be capable of generating as output a causal chain from any set of initial conditions and constraints. There may also be a requirement to determine from any hypothetical final state (air power capability), a set of initial conditions, relaxed constraints, resources and the intermediate causal chain needed to attain the capability. Such backward chaining could also be satisfied by simulation.
Modelling of Complex Systems
The foregoing discussion addressed models in so far as they represent well determined systems. The process of generating air capabilities on the other hand, is complex in that although precise algorithmic description is highly desirable, it is not feasible in every case. Features peculiar to complex systems include:
a need for but as yet an inability to develop a complete mathematical description;
intolerance of imposition of control;
irreproducibility of experiments.
Mathematical Description. A model of complex processes desirably should provide a precise mathematical description of the state of the system in terms of its controlled and uncontrolled inputs. However, a mathematical or algorithmic description of the air capabilities process in its entirety is not achievable because of the integral part which expert judgement and various random factors play in some elements of the process.
Stochastic Behaviour. Stochastic behaviour of complex systems results from their complexity and from the abundance of related processes which affect the system’s control including random factors within the system. Each of these random factors must be accounted for in any description of the system.
Intolerance to Imposition of Control. Intolerance to control may be the most vexing characteristic of a complex system. Initially, control is something external to the system itself and which disturbs the system’s otherwise independent activity; i.e. the function of control attempts to change the independent behaviour of the system and to render the system at least partly dependent upon the controller. The objectives of a complex system prior to imposition of control may not coincide with those of the controller and initially this variance produces apparently anomalous behaviour of the system.
Non-Stationarity. Non-stationarity is the drift of a system’s characteristics with time. The more complex the system, the faster it changes, the more salient this factor becomes, and the more difficult the task of developing a model capable of allowing adequate control of the system. Non-stationarity manifests itself in irreproducibility of behaviour.
Irreproducability. Irreproducability is the variation in the response of the object to the same control and environmental inputs at different times. A complex system evolves continuously, exhibits non-stationarity of characteristics and irreproducibility of behaviour. This must be accounted for when developing a model which is intended for control; a special correction may be used to account for irreproducibility. Two methods are commonly used; they are extrapolation of the system’s behaviour i.e. projection of its evolution, and reduction in the time cycle of control.
Summary of Characteristics. Absence of a complete mathematical description, stochastic behaviour, intolerance of control, non-stationarity and irreproducibility of behaviour are the principal vexing features of complex systems which must be accounted for in any model which is intended as a basis for control; also, the foregoing factors will largely determine the nature of the results. Unique optimal solutions will not be achievable; rather, wide parametric testing of present and future conditions should indicate a set of solutions which largely satisfy the objectives of control. This set is said to comprise a range of suitable choices and thereby to offer a robust solution to the problem of control in hand.
Modelling of Air Capabilities
History. Computer based mathematical modelling of air capabilities commenced during the 1950s and evolved in complexity and capability as technological capability permitted. Models were developed to meet the needs of individual programs, operations and plans and there appears to have been no overarching strategy which integrated the functionality of individual models.
Earlier models were constrained by limited machine capabilities; consequently, to obtain reasonable operating times it was necessary to use approximations of various interactions rather than representations of physical laws. These same machine constraints also led to the coding of extant doctrine as guidelines for tactical and strategic decision making and procedure; consequently, these early models were satisfactory in the role of familiarisation and training tools but were not suitable for the generation of new knowledge of battlefield interactions, or development of new doctrine.
Development of models into the 1980s used tools which were manpower intensive and represented large investments; consequently, many models were simply translations and migrations of existing models from one system to another with relatively minor modification to accommodate the new application. This practice has led to a proliferation of models which are not well matched to their applications.
Chief among these misapplications are adaptation of single environment models (land, sea or air operations in isolation) to joint operations. In most cases the adaptation contain limited representations of the new element(s). Also, because of the technological era in which the original model was developed, interactions are represented by approximations rather than physical laws. For reasons outlined previously, these joint models are in many cases less adequate for their tasks than their parents.
All of the foregoing factors are exacerbated in existing models used for development of capability proposals. Many of these models attempt to represent interactions on the battlefield from the highest decision making level to the lowest tactical manoeuvre. This span of representation necessitates an encyclopaedic input library and excessive running times. Also, although some of the representations may be useful for conceptual and operational development at lower levels, they may be so employed because of the monolithic nature of the models. This structural problem is symptomatic of a shortcoming of the current management process.
In most instances, specifications for models have been assigned to governmental or commercial research houses for development without provision of adequate guidance in the form of suitably qualified and experience military staff. Without those staff, modelling structures and representations may be employed which are suitable from a theoretical viewpoint but which do not produce results which relate directly to military objectives. This is characteristic of many models at all levels of representation. Experienced military staff must be available to guide modelling (and other research) of operations. Similarly, there must be sufficient scientifically qualified staff available to allow a comprehensive understanding of military operations. These two elements of military corporate memory from the Second World War appear to have been lost.
Catalogue of Simulations. The Force Structure, Resource and Assessment Directorate (J-8) of the US Joint Staff have produced (now in its eleventh edition) the Catalogue of Wargaming and Military Simulation Models which provides information on a number of models, simulations and war games currently in use or under development in the Defence establishments of USA, Australia, Canada, UK and FRG. A copy of the index and an example are included at Annex I to indicate the content and format of the catalogue.
Future Development. The historical development of operational models to date has produced a plethora of simulations none of which appear to be well matched to the force development process. This deficiency may be overcome by applying a disciplined structure and recent advances in software and hardware technology to the modelling process. Application of the proposed structure and new technologies should ensure greater ease of use and a marked reduction in development, operating and support costs.
Proposed Structure of Models. The proposed structure of models correlates directly to the hierarchy of strategic objectives, force development concepts and to appropriate levels of the command and control system to be used in the forces’ employment. The aim should be to create for each level a generic model or set of models into which may be set the parameters appropriate to the particular systems (actual or hypothesised) to be simulated. This approach is illustrated at Annex J; the following advantages accrue:
Simulations at each level relate directly to the military objectives and force development concepts at that level. The same models may be used to support conceptual and doctrinal development, preparation of force development concepts, and operational employment of capabilities thereby ensuring consistency of approach and economy of modelling effort.
Models are limited in complexity to representations at one level only; this constraint should result in reduced production, operation and maintenance costs.
The results at a lower level of simulation are integrated and used as input to the next level. This serves to reduce the scope of the modelling task at each level, to reduce the range of input data required and hence minimises set up, running and maintenance costs.
The model which would be employed for control of air power development process would consist of an integrated suite of each level of simulations shown at Annex J.
Use of generic simulations at each level would reduce the number of models required and hence their development and maintenance cost.
The essential underlying principle which allows parallel development of models for capabilities planning, control of capabilities, conceptual and doctrinal development, and operational employment is that activities at each level be tied directly to explicit statements of strategic objectives. These objectives are the same as those needed for performance measurement at each level of the operational command and control system.
APPLICATION OF MODELS TO THE CONTROL PROCESS
Effective control of air power generation requires a structured control process which draws on expert judgement, automated tools and models. The stages of the control process which are illustrated schematically at Annex K include the following:
determination of the objectives of control;
isolation of the object of control;
structural synthesis of the model;
identification of model parameters;
synthesis of control;
realisation of control; and
Determination of the Objectives of Control. This is the stage during which the set of objectives to be achieved by the process of control are determined. For air power generation, the set of objectives are the force element, group and theatre objectives which satisfy the air element of the military objectives.
Isolation of Object of Control. This stage determines that part of the military system that is to be modelled then controlled. This may not be a trivial task as many complex interactions may occur between the air capabilities, functions essential to their sustainment and policy constraints.
Structural Synthesis of the Model. Structural synthesis of the model equates to definition of those generic air and sustainment capabilities which have the potential to satisfy the military objectives. At this stage the precise structure and scale of forces is not defined. The structure takes the multi level form of the simulations at Annex J; each level represents capabilities the aim of which correlate directly to the relevant military objectives at that level.
Identification of Initial Parameters of the Model. This stage requires an initial estimate of the scale of air capabilities and their sustainment functions be made (these estimates are the result of expert judgement based, inter alia, on doctrine). Assigning numerical values to force structure and rates of effort together with regional location determines the required sustainment capabilities. The numerical values assigned to operational and sustainment capability comprise the initial parameters of the model; these initial parameters are based on expert judgement.
Optimisation of the Initial Model. During this stage are determined those parameters of the model which give an optimal satisfaction of military objectives. In this context, optimal connotes a range of parameters which together give a robust solution of the force requirements, rather than a unique set which would offer a single optimal result. The optimisation uses all levels of modelling indicated at Annex J. At this point a capabilities proposal is presented for authorisation.
Initial Synthesis of Control. This stage requires decisions on resource allocation which would ensure that the resulting capabilities (force elements and sustainment functions) would satisfy prescribed objectives. The resource decision would usually be based on the optimised model from the previous stage, the stated objectives, knowledge of the operational environment (as input to the model), and policy constraints on resources.
Realisation of Control. This stage requires implementation of the optimal solution (i.e. of the capabilities authorised during the preceding stage), which in the RAAF is the responsibility of Air Command. The implementation process is outlined in the earlier section titled Employment of Capabilities. The task is straightforward if knowledge of the strategic environment, the object and control objectives are accurate and unchanged. However, some or all may have changed and consequently objectives might not be met. This is to be expected since, apart from the factors mentioned previously, the object is complex, non-stationary and with internal noise; consequently a single control action (i.e. open or one way control) cannot be expected to achieve the desired goal and it will be necessary to return to one of the earlier phases of control (Annex K paths 2 to 5). Even the most favourable of circumstances would require a return to the stage of control synthesis to determine a new control reflecting the new conditions (Annex K path 1).
Correction. The requirement for correction results from the complexity of the object and its environment and involves a return to one of the preceding stages of control. All of the decisions taken at those preceding stages were based on outdated information and reflect the state of the object in the past. Correction may involve a number of stages. The most common requires adjustment of the model’s parameters such as force element numbers and rate of effort (see flow in Annex K). This correction is called adaption in Beer’s cybernetic model of control.
When the structure of the object has changed, the correction of parameters of the model may not be sufficient. A change to the structure of the model (force element types and organisational structure) may be required from time to time and correction may be needed to the boundary between the object and its environment. Also, there may be a number of reasons why the proposed system of control will not be able to fully achieve the desired objectives. There is then a need to correct the objectives of control, i.e. to determine a new set of objectives that can be achieved. This process enables the controller to learn the objectives that the control system can achieve within the stated resource and policy constraints.
Implementation of the foregoing procedures would create an adaptive control system that could adjust to the ever changing demands of the strategic and operational environments, air capabilities (the object) and military objectives. The control system would evolve along with the object and the environment so that the objectives of control should be realised. Whether the proposed control system could be implemented would depend, inter alia, on the relative cost of developing and maintaining the suite of models and automated tools upon which it is based vis-à-vis the accumulated benefit which the new control system could offer.
Costs of Models and Automated Tools
The life cycle cost of a suitable suite of models and automated tools should be determined by the effort required to:
prepare a workable system design;
assemble appropriate cost and performance data on existing capabilities and sustainment functions;
write, test and validate the models and tools; and
ensure future development and maintenance.
Usually, the greatest part of these costs lies in items b and c above. First steps in assessing the cost of developing automated tools should be:
preparing a high level system design of sufficient detail to allow assessment of an error budget across the entire simulation;
carrying out an error analysis to determine the accuracy with which the cost of sustainment function must be known in order to derive total capability costs of useful accuracy; and
assessment of the effort needed to compile in machine readable form cost data appropriate to each sustainment function.
When the high level systems design has been completed, a Departmental and market survey should be carried out in parallel with the remaining cost evaluation to find existing Defence, commercial or university based capabilities which satisfy or could be modified to satisfy the modelling requirement. Results of a preliminary market survey of high level software and resource allocation tools are outlined below. In the absence of suitable models, the cost of software development for a new suite of models should be determined.
Preliminary Market Survey
The author conducted a preliminary market survey to assess the scope of available products. The parameters used included:
capability for symbolic representation of systemic functions, information flows and qualitative dependencies;
automatic solution of mathematical relationships;
capability for sensitivity analyses and monte carlo representations;
optimal resource allocation across a large number of variables and constraints;
minimal requirement for hard coding;
efficient, easy-to-use human-machine interface;
minimal training required for numerate users;
low cost; and
suitable for operation on desk top computing machines.
No tool was found which would simultaneously satisfy requirement d and all others. Nevertheless, two tools when used in conjunction appear to provide all of the functionality required, they are a simulation tool called I Think by High Performance Systems Incorporated of Hanover NH, and a resource allocation tool Resource Manager by Shaw-White Pty Ltd of Mitchell ACT. I Think is an evolution of the previously successful product Stellar; its retail price is $1040 (Version 2). Shaw-White developed Resource Manager in conjunction with CSIRO and is presently negotiating intellectual property rights. Resource Manager has been used successfully on a number of large projects, and by invitation, Mr A. White demonstrated Resource Manager to this year’s meeting of the Defence Systems Management College in Paris during the week 15-19 July 1991. Marketing arrangements for Resource Manager have not yet been decided.
Defence Modelling Resources
Defence Research Centre Salisbusry (DRCS). During discussions with the staff of Weapon System Research Laboratory of DCRS the control paradigm and proposed structure of the suite of models was outlined and agreed to be appropriate and workable. DRCS has been active in simulation of military systems since the 1950s and has accumulated a wealth of experience in the representation of systems and of operations up to force element size. Although none of these has been specifically aimed at meeting the objectives outlined in this analysis, there may be scope for modifying some of the existing models to harmonise them with the paradigm proposed in this paper. Following analysis of this paper by the staff of the DRCS, further consultations will be required to scope the extent of the contribution which could be made by that organisation.
Aircraft Research Laboratories (ARL). Mathematical modelling at ARL has to some extent been a synergistic effort in concert with DRCS. The main thrust of modelling work at ARL has been aircraft and systems performance, flight dynamics and human factors. Many of the skills involved in developing these models could be profitably applied to the development of air capabilities models, other Defence priorities permitting. The extent to which ARL resources and models could be turned to assist development of a suite of models will require further discussion with the staff of DSTO.
The resources available within Department of Defence which are likely to be available for supporting the development of a modelling effort of this type are limited. Also, the marginal cost of increasing Departmental staff is high. Recently there has been evidence of increasing interest in simulation of military operations by some universities. These organisations could have lower cost structures and better responsiveness than the Department. Interaction with the public through universities could also afford wider exposure of Air Force purpose, doctrine and planning, There may be scope for contracting out some of the modelling effort to universities with appropriately qualified and equipped departments. Similarly, private research groups might be suitable sources of support for smaller tasks.
Some universities have already approached DTSO in search of modelling work. For example, the University of Newcastle which is strong in flight dynamics and is familiar with the work of ARL, tendered for, developed and delivered a flight dynamic situation for DSTO at a much lower price and in a much shorter time scale than could be contemplated using Departmental assets. The University of Queensland is another entrepreneurial organisation which has approached DSTO for modelling work and which is strong in ADA skills, DSTO is reserving its decision pending advice on funding.
Modelling support for military operations by universities and private research groups would carry the usual overhead of liaison, coordination and scientific management which might best be performed by relevant DSTO staff, and provision of expert judgement and experience of suitable Air Force personnel. An additional penalty of such an arrangement would be the cost of travel to the various campuses; this is expected to be small compared to the cost of using increased numbers of Departmental research personnel. Use of university and private research groups should be the subject of further analysis.
Cooperation with US and UK Efforts
During a recent visit by the author to RAND Santa Monica and Defence Operational Analysis Establishment, (DOAE), interest in the approach proposed in this paper was evinced. Further, the structure of the models and the general control paradigm correlates well with the new approaches to force development being implemented by the USAF, and could offer some assistance to the force development dilemma being faced by the RAF and Supreme Headquarters Allied Powers Europe (SHAPE). Cooperation with RAND and DOAE in the development of models and exchange of expertise could expedite development of the proposed suite of models and reduce development cost. Cooperation with overseas agencies should be subject of further investigation.
Coordination of the Modelling Effort
In the past, each modelling task has been managed as an isolated entity but in this case planning and coordination of the total modelling effort would be a significant project management task. Agreement to the modelling structure, characteristics and capabilities by each of the users and contributors would be essential. A project manager of appropriate rank who possesses relevant operational experience and who has appropriate qualifications in operations research and mathematical modelling is required to develop the project plan and guide development of the constituent models.
Recently, initiatives by Treasury and Department of Defence have focused on delegating financial responsibility to lower functional levels in order to effect more efficient use of resources. These initiatives, the Programme Management and Budgeting process (PMB) and Financial Management Improvement Program (FMIP) appear to impact force development largely through their administrative effect on the mechanics of the iterative committee process and on funding of the sustainment functions. Further study of PMB and FMIP should be undertaken to determine the extent to which procedures need to be included in a predictive model of air capabilities generation.
The process of air capabilities development is complex and its optimal control requires a structured approach which integrates the use of expert judgement and automated tools. Principal among the latter are mathematical models of air capabilities; the balance consists of project management, resource allocation and operations analysis tools.
Consistency between strategic guidance, modelling of capabilities, force development concepts and operational employment plans can be achieved provided that at every level each is focused on the appropriate military objective. A suite of models based on this hierarchy of objectives would provide a common set of tools which could inform force development concepts, force employment and capability planning. Consistency of objectives and models would ensure economies of model development and consistency throughout the air power development process.
The suite of objective based models would form the foundation of the air capabilities control process by acting as the predicative tool on which capabilities proposals are based and by affording an analytic method for assessing the impact of changes to the operational environment, objectives, resources and procedures.
The objective based structure and control methodology proposed here has not been implemented previously and would probably necessitate development of a new suite of models. Although a developmental task of this nature would be expensive using the tools of earlier technological generations, recent developments indicate that the task could be substantially reduced in scale provided new software and hardware technologies are employed and adherence to the proposed structure is observed.
More precise control of the air power development and employment processes is practicable through the integration of expert judgement with the use of mathematical models, automated tools and adaptive, resilient command structures. A paradigm for the control of the air power generation process has been proposed which could ensure the following:
military air capabilities would be related to the objectives, roles and tasks of the ADF;
appropriate types and levels of all ADF air capabilities would be derived;
the balance between force structure, modernisation, readiness and sustainability would be determined;
estimates of the cost of achieving alternative readiness levels would be ascertained; and
current doctrine could be included in the model or new doctrine could be developed through application of the model as required by changing circumstances.
The paradigm is a control process which should afford more precise generation and application of air capabilities to military objectives. Central to this process is the proposed suite of mathematical models.
Development and implementation of a predictive suite of mathematical models of the generation of air capabilities is practicable provided that the objectives at national, regional, operational, group and element level are harmonised with the objectives of strategic conceptual development and of each level of operational planning and employment. This alignment would ensure the following:
a common set of models would be available to inform force development concepts, capability planning and force employment;
consistency of objectives across all activities at each strategic level would ensure economies of model development;
harmonisation of objectives with elements of the suite of models would facilitate control of the air power development process; and
consistency of objectives at all levels would allow accurate measurement of operational achievement, would permit immediately relevant and accurate feedback and thereby facilitate more precise control of the application of air power.
Within Department of Defence resources exist which could be employed in the development of the suite of models. These resources include staff experienced in military operations research, and some of the models which have been constructed in support of military operations and programs. These resources are likely to remain limited and to be subject to demands from other requirements. Outside the Department suitable resources in the form of university and private research organisations may be utilised. Cooperative development with defence agencies in the USA, UK and Europe could be pursued.
The most effective organisational arrangement for implementing the new control paradigm is a structure based on cybernetic principles. All levels of this structure would be aligned to appropriate strategic objectives and would afford adaptability and resilience in the face of changing operational conditions.
The proposed control paradigm, model and command structures would align with the present conceptual framework for the development of air capabilities as implemented in HQADF, and all traditional command relationships would be preserved.
Implementation of the following is recommended:
a methodology for development of air capabilities which is aligned directly to statements of objectives at all levels;
preparation of statements of military objectives which can be made consistent with strategic guidance, concept development and force employment goals, and which would provide a sound basis for control of the air capabilities process;
the control paradigm outlined in this paper which takes as its focus a suite of predictive models of air capabilities (subject to a satisfactory outcome of cost and accumulated benefit analysis of the proposed control system);
development of a suite of models each element of which is aligned to a level of objectives;
adjustment of the existing command and control system to reflect the cybernetic principles outlined in this paper;
development of performance metrics including those needed for elements of preparedness as redefined in the Introduction to this paper;
a study of the operational decision cycle including processes for the collection, correlation, evaluation and distribution of operational information, and of optimal force allocation;
methods of ensuring retention of expertise, i.e. of corporate memory; and
a review of the adequacy of communications in view of the need for near real time communications in support of e and g above.
Contingent upon acceptance of recommendations a to d above, the following should be implemented:
selection of a long term project manager to ensure coherent development of the models and control processes;
assessment by modelling specialists of new hardware and software technologies appropriate to the modelling tasks;
assessment of the cost of a suitable suite of automated tools to support the planning and employment of air capabilities;
assessment of extant capabilities in Australia for development of suitable models, including capabilities of universities and similar non-Defence organisations;
exploration of possibilities for cooperative development of models with RAND, DOAE, and possibly with the Technical Centre of SHAPE;
preparation of a plan for the coordinated development of the suite of models including assessment of the specialist military staff needed to either manage or guide the developments at each location;
development of a master plan for the introduction of the control process and of the suite of predictive models upon which it is based; and
assessment of the impact of new administrative arrangements on the capabilities development process.
The views expressed are those of the author and do not necessarily reflect official policy or position of the Department of Defence, the Royal Australian Air Force or the Australian Government. This report is approved for public release; distribution unlimited.
Portions of this serial may be quoted or represented without permission, provided that a standard source credit is included.
The author gratefully acknowledges the assistance of many in Australia and abroad who contributed to this study. In the United States the assistance of Ben Lambeth in facilitating discussions with the staff of RAND Corporation (Santa Monica) is greatly appreciated. RAND staff included Milt Weiner and Dick Hillstead to whom thanks are due for their valuable insight f the application of air and joint force models, to Roy Gaites for his experience of the development of processes which support RAND’s modelling efforts, and to David Ochmanek for his advice of the relationship between strategies, tasks and modelling. The author is grateful to General Glenn A. Kent of RAND Corporation (Washington) for discussions of the force development process, of the relevance of modelling to those processes, and for sharing the experience and conceptual development which underpins his recent work A Framework for Defence Planning.
Thanks are due to the Director of the USAF Air Power Research Institute, Colonel Dennis Drew and to Lieutenant Colonel Charles Westenhoff for their assistance during a visit to the Institute. The author is indebted to Ken Lavoie, Technical Director of the USAF Wargaming Centre for his analysis of current simulations and for his thoughts on the way ahead in modelling of military capabilities.
At the Office of the Secretary of the Air Force, the author thanks Chris Bowie; in USAF Studies and Analysis, Colonel Tom Cardwell, Lieutenant Colonel Al Piotter and Major F.T. Case. Valuable assistance was given by Lieutenant Colonel Mike Nelson and Lieutenant Colonel Sky King of the USAF Checkmate Team. The author is very appreciative of the views offered by Colonel John Warden III, Colonel Coffman and Lieutenant Colonel Dan Kuele o the office of USAF Strategy, Doctrine and Plans.
To Alan Gropman of the National Defence University are due thanks for his kind support in facilitating discussions with NDU staff, including Colonel Tom Keaney, Colonel Cliff Kreiger, and Lieutenant Colonel Rick Baringer, and for his advice of the force development process.
In the United Kingdom several senior RAF officer gave generously of their time and experience during discussions at Ministry of Defence (UK). The author is grateful to Group Captain Peter Sturt for his advice and assistance in coordinating the discussions. Participating officers included Group Captains David Hamilton, Richard Howard, Gerry Gerard, John Evans, Mick White, Bill Hedges, Wing Commander Steve Jones and Wing Commander Bob Crane. Similarly, the author thanks Group Captains John Burns, Tim Willbond, Tug Wilson, Phil Roser and Gerry King for their helpful advice.
To the outgoing Director of Defence Studies at RAF Brachnell, Group Captain Andy Vallance and his successor Group Captain Neil Taylor the author extends his thanks for their views of air power doctrine.
Several staff of Defence Operational Analysis Establishment, West Byfleet shared their experience of war gaming and modelling in support of the Gulf War operations; staff included Group Captain Tony Stevens, Gavin Lidderdale, Mike Metcalf and Mike Head. The author thanks Gavin Lidderdale for his helpful explanation of the development of DOAE’s gaming and modelling techniques.
To Peter Preston and staff of Aircraft Systems Division of Aeronautical Research Laboratory, and to Max Possingham and staff of Combat Systems Division, DSTO Salisbury, the author is indebted for critical analysis of the proposed methodology, and recommendations for the way ahead. Air Commodore Brendan O’Loghlin and Air Commodore Errol McCormack of Headquarters Australian Defence Force provided advice on current force development processes.
Finally, the author wishes to thank the staff of the Air Power Studies Centre and RAAF Staff College for their support for, and critical comment on this report. Special appreciation is expressed to Air Commodore Ian Westmore, Group Captain Brent Espeland, Group Captain Jo Hamwood and Wing Commander Alan Stephens. To Wing Commander Gary Waters the author is indebted for many hours of stimulating discussion and assistance.
Notwithstanding the extensive assistance provided the author, he alone is responsible for any errors or omissions in this paper.
Terms of Reference for this study are contained in CAS 459/91 of 15 May 91 and APSC/31/Air(20).
Military capability connotes the sum of sea, land and air capabilities.
CDF, Chief of Defence Force Direction on ADF Operational Readiness (Issue 2), CDF Directive 11/90, 27 August 1990.
The symbolic relationships presented here are not intended as strict mathematical equations but as convenient summaries d the dependencies between those elements that constitute military capability.
The expendable supplies, stores and other material refer to here, are for operational convenience usually organic to the subject force element or group to ensure that the requirements for operational notice as specified in the Chief of Defence Force Operational Readiness Directive may be met. Although these stores are identified for use by the force element or group, provision of those stores is part of the sustainment function.
The distinction between sustainability (SB, the period for which the support system is capable of satisfying operational demand) and sustainment (S, the output rate of the totality of sustainment functions) should be carefully noted. Further, the sustainment functions act across the continuum of peace, war and post war activities whereas sustainability is the period for which war operations may be supported at a specified operational tempo; i.e. sustainability is a subset of sustainment.
AC = FS + OR + SB
A multidimensional trade-off is required: a balance must be struck between FS, OR and SB for each of the three arms (sea, land and air).
Although command is afforded in varying degrees, the increased complexity does not invalidate the following argument and will not be considered further here.
The approach to control adopted in this paper is based largely in L.A. Rastrigin, Contemporary Principles to Control Complex Objects, trans. Michael Burov (Moscow: Mir Publishers, 1983).
The following discussion is based on Paul Bracken, Strategic Planning for National Security: Lessons from Business Experience, N-3005-DAG/USDF (RAND, February 1990).
In this context, ‘area’ refers to a geographic region.
See also Ian O. Lesser, Interdiction and Conventional Strategy: Prevailing Perceptions, N-3097-AF, (RAND, June 1990) for an insightful analysis of air power doctrine and prognosis of its application to the recent Gulf War.
Air Power Studies Centre, The Air Power Manual (Canberra: Aristoc Offset, 1990).
The sequence in which concurrent air campaigns are emphasised may change depending upon operational conditions. For example, initially a heavy Control of the Air campaign could be inappropriate if the enemy possessed air defences which could exact a high loss rate without ensuring adequate control of the air. In such situations an emphasis on the Independent Bombing Campaign in the form of interdiction of advance-to-contact forces could afford better results at less cost while simultaneously diverting the enemy and seizing or retaining the initiative. The Control of the Air campaign would follow and would aim to draw the enemy’s air forces from his position of strength (behind effective defences) to fight on less favourable terms.
The force development process is defined in the Defence Instructions (General) 42-1; this paper is further qualified by discussion with the DGDFD (Air) and focuses on those elements of the process which immediately affect the planning of air capabilities rather than the administrative processing of capability proposals.
A new capability could be satisfied by modification of existing capabilities. The processes for implementing modifications would be similar to those applicable to new force structure elements.
In this paper the term ‘automated tools’ is defined to mean computer based methodologies other than mathematical models.
The rate of generation and focus of air operations are the dominant factors which determine the outcome of air campaigns. The metric by which forces are judged during the planning phase should be the accumulated achievement of objectives with time. This is a dynamic measure of direct relevance to the battlefield. Static measures such as cost-effectiveness may be used but decisions based on such criteria will necessarily result in prolonged and expensive campaigns. General Glenn L. Kent, RAND Corporation Washington DC, 16 August 1991, personal communication.
Retention of corporate memory is an important issue at all levels of control including Headquarters Australian Defence Force and Air Force Office.
Preparedness was defined in the Introduction to this paper to mean force structure, equipment condition, manpower, training and sustainability.
In situations of high traffic density the need to avoid confliction of operational traffic through a scheduling process could extend the planning period; difficulties of this type were experienced in planning the air missions of the Gulf War.
The need for thorough analysis of the system to be modelled prior to the commencement of modelling activity cannot be overemphasised.
This discussion draws heavily on Jeff Rothenberg, The Nature of Modelling, N-3027-DARPA (RAND, November 1989).
One simulation is known which contains optimal Orange force allocator (strategy generator) and hence is capable of generating new knowledge of interactions on the battlefield. The simulation was developed by Wilfred R. Goodson, Systems and Technology Research Corporation. This allocator has been refined by Dick Hillstead of RAND Santa Monica for inclusion in TAC SAGE.
Further limits to the utility of existing models of joint operations were evident during the Gulf War. None of the models available prior to the conflict reflected the effect of differences in national approach to conflict. Work at DOAE (UK) which incorporated the nationality factor in war games gave predictions which were acceptably close to reality.
New modelling technologies should help to make simulations more comprehensible by providing for intelligent exploration of processes and explanation of results; this may be achieved by allowing users to modify the model and the course of events in a simulation and by making the simulation explain its behaviour in useful ways. The modelling technology which could afford these capabilities is a blend of Artificial Intelligence and conventional modelling and is known as Knowledge Based Simulation; Rothenburg, p. 13.
Rastrigin, pp. 25–36; the proposed control mechanism uses a mathematical modelling process as the focus of a feedback network. The latter is similar in principle to the control process proposed by Stafford Beer, Brain of the Firm, (Bath: The Pitman Press, 1981), p. 32.
Recent work in sensitivity analysis at the RAND Corporation uses Artificial Intelligence techniques which avoid the need to recompute the sensitivity for every functional variation in a parametric analysis; Rothenberg, p. 12.
Discussions Possingham/Fogg/Thoms of 27 September 1991.
Gen Glenn A. Kent, A Framework for Defense Planning R-3721-AF/OSD (RAND, August 1989) and personal communication Kent/Thoms 16 August 1991.
Gavin Lidderdale, DOAE, personal communication 23 August 1991.