Abstract
Background. Modern Defence forces require adaptable training and simulation environments capable of responding rapidly to shifting operational and geopolitical demands. Legacy, sequential acquisition models often limit responsiveness. Simulation-enabled training, if delivered through agile, system-based practices, can improve readiness and interoperability across Defence domains.
Objective. This study examines how the integration of Team and Technical Agility (TTA) and Systems Thinking, operationalised through the Scaled Agile Framework (SAFe) and reinforced by generative leadership cultures, can enhance Defence simulation delivery and align capability outcomes with the Defence Strategic Review (DSR) and National Defence Strategy (NDS) imperatives.
Methods. Using practice-based qualitative analysis, experiential Defence case studies were synthesised and compared against criteria derived from open-source literature workflow efficiency, adaptability, and interoperability. Each case was evaluated to identify how organisational culture and leadership behaviours affected delivery outcomes.
Results. Case studies that embedded TTA within SAFe demonstrated faster integration cycles, improved reliability, and stronger cultural alignment with mission needs. Conversely, traditional sequential programs exhibited delays and reduced adaptability.
Conclusions. Empowered leadership, cadence-based planning, and DevSecOps-enabled workflows underpin the responsiveness required for future Defence simulation. Embedding technical agility and systems thinking transforms simulation from a support function into a mission-critical capability, enabling joint and coalition readiness.
Background
Australia’s evolving strategic environment demands that the Australian Defence Force (ADF) maintain readiness across all domains while adapting to rapid technological and geopolitical change. The Defence Strategic Review (DSR) (2023) calls for “an enhanced force-in-being” capable of preparedness across maritime, land, air, space, and cyber domains. Simulation-enabled training underpins this preparedness by allowing mission-realistic performance testing without operational risk.
In this context, simulation-supported training must become a core element of Defence capability, providing adaptable, relevant, and mission-focused learning environments that mirror the complexity and volatility of modern warfare. As General David Berger stated at the 2021 Interservice/Industry Training, Simulation and Education Conference (I/ITSEC), “We cannot be comfortable going at a comfortable, deliberate pace anymore. We’re driven by a pacing threat that’s driving us, which we haven’t had before” (Berger, 2021).
Defence training organisations often remain constrained by legacy acquisition and delivery models designed for predictability rather than agility. Traditional Waterfall frameworks progress through linear, stage-gated phases that deliver capability only after long decision and integration cycles. These processes manage change as risk rather than as a potential driver of improvement.
Comparison Between Traditional Models (E.G., Waterfall) and Safe.
Modern Lean-Agile frameworks, particularly the Scaled Agile Framework (SAFe), use short, cadence-based iterations to enable teams to deliver capability at the pace of relevance. This shift aligns with the DSR’s call for responsiveness and technological resilience. Within SAFe, Team and Technical Agility (TTA) empowers cross-functional teams to collaborate continuously, integrate frequently, and align outcomes directly with mission objectives.
When combined with systems thinking, TTA positions Defence organisations to treat networks, simulations, data, and people as components of a single interdependent ecosystem rather than isolated projects. This whole-of-system view supports coalition interoperability and rapid adaptation capabilities which are essential for future multidomain operations. In effect, agility at the technical level underwrites agility at the strategic level.
The Australian Army’s doctrine on manoeuvre warfare reinforces this approach by linking adaptability with initiative: This is because manoeuvre warfare “is key to maintaining a proactive force that is agile and maintains the initiative” (Webster, 2022; para. 2). Achieving such agility within simulation delivery requires empowered leadership, generative cultures, and technically fluent teams capable of responding to constant change.
Purpose
This paper proposes to address the constraints that traditional Defence acquisition and training models raise by recommending that the integration of TTA, underpinned by a systems thinking approach, into the simulation training ecosystem, supported through a trust-based culture, will enable Defence to meet its future operational requirements, overcome legacy constraints, and foster innovation at all levels. This paper also proposes that Technical Agility and Systems Thinking are foundational pillars in the delivery of simulation-based and mission rehearsal environments, emulating coalition command systems training environments that can respond to fluid strategic contexts and complex operational demands. It further hypothesises that applying TTA and Systems Thinking through SAFe, can improve the way simulation capabilities are delivered within the Australian Defence environment, strengthening readiness, resilience, and adaptability by aligning leadership, culture, and technology into a unified, system-oriented approach, thereby meeting the imperatives of the DSR and the NDS.
Figure 1, proposes a practical model for how the delivery of Defence Simulation can be enhanced when the principles of TTA within SAFe, using a systems thinking focus, are applied in support of military training’s foundational principles. Employing SAFe would enable simulation teams to build, adapt, and deliver high-fidelity training environments that remain relevant in the face of geopolitical, technological, or tactical shifts. By integrating agile practices and a systems thinking perspective into simulation delivery, Defence organisations could better align training outcomes with operational requirements while maintaining training systems that are adaptable, resilient, responsive and efficient across distributed networks designed to sustain the low latency and connectivity needed. Overview of the systems and technical agility.
Literature Review
A literature review was conducted to establish situational awareness of modern Defence simulation environments and identify criteria that support the paper’s analytical framework. Strategic policy, Defence doctrine, IEEE simulation standards, academic and technical sources were examined using keywords aligned with the DSR’s imperatives and related to simulation-enabled training, Systems-of-Systems (SoS) integration, and agile or systems-thinking methodologies.
Modern Defence forces face the twin challenge of keeping pace with technology while sustaining readiness. Publications such as Chen & Unewisse’s A Systems Thinking Approach to Engineering Challenges of Military Systems-of-Systems (2016) and the Australian Army’s The Future Ready Training System (2020) highlight the necessity of holistic, systems-oriented practices linking simulation, workflows, and operational outcomes. Similarly, the U.S. Modernised Enterprise Army M&S Concept advocates modular simulation models and containerised services to allow “flexibility in simulation design and execution while also allowing the offload of hardware burden to other virtualized servers that have resources available” (Hargrove et al., 2025). Collectively, these works promote agile, networked architectures supporting rapid integration and user-centred adaptation with technical agility and systems thinking as essential enablers of resilient training environments.
Yet Defence simulation training remains at a crossroads. Escalating complexity, coalition interoperability demands, and frequent scope changes expose systemic fragility. Fiscal pressures compound the issue: “the Defence Department has cut project maintenance and training budgets by 10 per cent to save money” (Tillett, 2025). This cost-driven approach undermines prioritisation of simulation as a capability enabler.
Unlike larger allies, the ADF lacks a unified, low-latency simulation infrastructure or the workforce scale to sustain service-specific establishments. Many existing Defence systems exceed the latency threshold needed for effective training, impairing realism and integration. Simulation assets, live ranges, high-fidelity simulators, and part-task trainers often operate in silos, diminishing collective training potential.
Another constraint is the absence of on-demand, Just-in-Time (JIT) delivery mechanisms. Current processes rely on ITIL v3, an IT service management framework that, as the literature notes, contains “gap [s] between the knowledge of ITSM frameworks and … implementation” (Melendez et al., 2016; as cited in Serrano et al., 2021, p. 10) and that “… [ITSM] is intrinsically connected with framework complexity” (Serrano et al., 2021, p. 10). Moreover, “ITSM systems lack a solution for process measurement and improvement” (Melendez et al., 2016; as cited in Serrano et al., 2021, p. 10). Such process-driven rigidity limits agility and innovation.
Institutional culture further constrains responsiveness. Public-sector frameworks prioritise compliance and accountability. As the Australian National Audit Office (ANAO) explains, “transparency on performance … is considered essential for effective accountability” (ANAO Annual Report 2023–24, 2023). While necessary for governance, over-emphasis on compliance suppresses the cross-functional decision-making required for agile simulation delivery.
The reviewed literature underscores that agility, systems thinking, and leadership culture are interdependent. Authors, including Westrum (2004) and Senge (1990), link generative cultures and learning organisations to performance outcomes. The DSR (2023) and Department of Defence (2024) similarly highlight preparedness, integration, and adaptability across all domains. Bureaucratic barriers and fragmented infrastructure, however, continue to inhibit the realisation of these objectives.
By consolidating findings from doctrinal and technical literature, this review identifies the foundations necessary to reform Defence simulation. 1. Workflow Efficiency: achieved through cadence-driven, agile frameworks. 2. Adaptability: enabled by empowered leadership and JIT responsiveness. 3. Interoperability: supported by open standards.
Case Study Summary.
Methodology
This paper applies a qualitative multiple-case study design methodology to examine how TTA and Systems Thinking could be operationalised in Defence simulation delivery. As Yin notes, “A case study is an empirical method that investigates a contemporary phenomenon (the “case”) in depth and within its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident” (2018, p. 15). “A case study … relies on multiple sources of evidence, with data needing to converge in a triangulating fashion” (Yin, 2018, p. 16). In alignment with this approach, the evidence for the cases was drawn from multiple source types including standards, policy artefacts, practitioner reports, and open documentation. This multi-source approach reflects Woodside’s view that “The use of mixed or multiple methods in case study research usually contributes to increasing accuracy and complexity/coverage in a study more so than generality” (2010, p. 33). To enhance credibility, disciplined triangulation was applied consistent with Stake’s guidance: “In our search both for accuracy and alternative explanations, we need discipline… In qualitative research, those protocols come under the name ‘triangulation’” (1995, p. 107). The objective of this paper is to evaluate whether the integration of Team and Technical Agility (TTA) with Systems Thinking, operationalised through the Scaled Agile Framework (SAFe), can improve Defence simulation and training delivery.
Research Questions
1. How does the adoption of TTA influence workflow efficiency in Defence simulation environments? 2. To what extent can systems-thinking principles enhance adaptability and reduce integration delay across Defence training systems? 3. What organisational and cultural factors most significantly affect interoperability within simulation federations and coalition networks?
The five case studies were selected through purposive sampling based on relevance to Australian or coalition Defence simulation programs with representation across both agile and sequential delivery environments to allow comparative analysis. 1. 2. 3. 4. 5.
Each case was analysed using open-source or unclassified documentation, practitioner artefacts, and Defence policy materials that met access criteria. The inclusion of multiple program types of federation architectures, networked emulations, and workforce transformation ensured diversity across technological, cultural, and organisational dimensions.
The analytical framework combined qualitative document analysis with case comparison matrices. Key sources were coded against the three analytical criteria. Latency thresholds were benchmarked using the IEEE Simulation Standards.
Cultural evaluation references Westrum’s (2004) typology of organisational cultures and Senge’s (1990) learning-organisation model to characterise leadership behaviours, information flow, and decision latency. These frameworks provided repeatable, literature-aligned instruments for qualitative comparison. The research followed a structured five-step protocol illustrated in Figure 1. 1. Case Identification & Classification: Cases categorised by domain, delivery model, and data availability. 2. Document Analysis: Collection of open-source artefacts, policy documents, and practitioner reports. 3. Coding: Application of the three analytical criteria across all sources. 4. Cross-Case Comparison: Mapping patterns of success and failure; consolidated in Table 2. 5. Validation: Triangulation against independent Defence publications and journals, Standards, and Experience to confirm alignment with doctrine and operational evidence.
This sequential but iterative protocol ensured traceability from data source to analytic outcome while allowing refinement of criteria through each iteration.
A qualitative comparative approach was applied. Each case was rated for evidence of (1) flow and efficiency, (2) adaptability, and (3) interoperability. Results were plotted against the framework visualised in Figure 2, illustrating relative alignment and variance between agile and sequential models. Findings show that cases demonstrating cadence-driven planning and continuous integration achieved higher scores across all three criteria. In contrast, networks adhering to rigid controls and a configuration design for different business needs exhibited latency exceeding the “200 … upper limits of tolerable delay” (IEEE, 2010.1-2012, p. 698) and slower response to requirement change. Methodology flow: Inputs, analysis lens, and outputs.
This practice-based study used publicly available materials and professional artefacts. Accordingly, it did not require formal ethics approval under institutional research governance. Ethical considerations were nonetheless addressed by anonymising all practitioner references, ensuring compliance with Sage’s requirement. As this work draws on open-source and experiential data, it does not establish causal relationships. Quantitative validation through metrics such as flow efficiency, defect rate, or interoperability uptime is recommended for future study. Nonetheless, the qualitative patterns observed across the five cases provide a credible foundation for the Results and Discussion that follow.
Results
The comparative analysis applied the three validated criteria of workflow efficiency, adaptability, and interoperability to five representative environments. Each case was evaluated through open-source artefacts, practitioner reports, and doctrinal references. Table 2 summarises the case characteristics, data sources, and key findings.
Case A: JCTC/DTEN Federation and DTEN Evolution
The JCTC and DTEN provided Australia’s primary simulation federation through the mid-2010s. Analysis found strong evidence of cadence-based development cycles, consistent with SAFe’s incremental planning and continuous integration model. Interoperability across systems was achieved through compliance and alignment with IEEE 1516-2010 High-Level Architecture (HLA) and 1278.1-2012 Distributed Interactive Simulation (DIS) standards.
Latency performance in cross-domain exercises consistently remained within the IEEE threshold of “100 ms to 200 ms … limits of tolerable delay” (IEEE, 2012, p. 698). These results confirmed effective technical agility and disciplined network engineering.
Figure 3 illustrates the JCTC/DTEN growth in creating a simulation delivery system based on flow, showing how iterative testing and feedback loops compressed release cycles delivered. The model demonstrates that frequent integration events improved both efficiency and interoperability without sacrificing assurance controls. Timeline of JCTC Development.
The JCTC was “a joint Australian/U.S. initiative” (Calytrix Technologies, n.d.), pioneering Live, Virtual and Constructive (LVC) simulation environments in Australia. Using protocols such as DIS and HLA, and the framework components Run Time Interface (RTI), and Federation Object Models (FOM), the team connected dispersed capabilities, enabled real-time interactions between simulators, whilst also supporting more complex federated and integrated environments, including Test and Training Enabling Architecture (TENA) for live training. These systems relied on a low-latency User Datagram Protocol (UDP) configured network infrastructure, as shown in Figure 4. Dis and HLA simulation.
Initially, the JCTC focused on building the DTEN as a low-latency network for milestone exercises, such as Talisman Sabre. As a temporary construct, the infrastructure evolved into a persistent, scalable national network with connections to multiple U.S. bases via the JTEN. This shift marked a pivotal moment in simulation delivery enabled by a leadership culture that prioritised outcomes, transparency, and technical empowerment.
Case B: AMN-TF Emulation (2011)
This case demonstrates how technical agility and configuration flexibility enabled the JCTC to rapidly emulate the U.S. CENTRIX-ISAF Afghanistan Mission Network (AMN) and establish a federated connection through JTEN and DTEN within an exceptionally short timeline. The senior directive and deadline were explicit. “On July 25, 2011, LTGEN Power signed a letter to Lt Gen. George Flynn, the Joint Staff’s Director of Joint Force Development” (McGowan & Deacon, 2012, p. 4), which also tasked the JCTC with replicating the AMN-TF and connecting to the live federation via JTEN and DTEN within three months. As described by McGowan and Deacon (2012), “the AMN-TF services could be delivered through our existing JTEN to DTEN connection, (and)… In October 2011, … personnel and equipment traveled to Canberra and Enoggera, Australia for the demonstration.” (2012, p 4-5).
This configuration supported the AMN-TF emulation locally and the federated reach-back to the live environment via JTEN↔DTEN, satisfying the direction and timeline set out in July 2011 and executed by October 2011.
Case C: Workforce/Tenure Signal and Cultural Effects (2015 - 2019)
The following case study summarises observed tenure/retention changes, along with their operational effects on handover risk and flow, utilising publicly visible signals (e.g., LinkedIn samples) and internal pipeline standardisation as mitigation measures.
Staff stability and knowledge continuity declined significantly following the 2015 contract transition, increasing handover risk and eroding the flow of delivery. This shift coincided with a cultural move away from empowered, outcome-oriented practices toward rule-dominant governance, reinforcing the central claim that generative cultures are causal enablers of technical agility and responsiveness 1 . Blackmore and Allitt (2021) noted that from 2015 to 2019 “the average tenure in this environment is less than 6 months … this represents a significant loss of not just capital, but also of corporate knowledge”. Prior to this timeframe, tenure had been multiple years, with staff drawn to the supportive and empowered culture.
Wessels warns that organisations “must understand the multidimensional impact of employee turnover when it comes to knowledge loss and knowledge management. The cost of losing institutional knowledge, impact on organizational performance, and decline in morale can be severe” (2024). Combined with rigid governance and risk-averse cultures, this limits responsiveness, especially during last-minute or bespoke training requirements. Without autonomy, simulation teams may default to rejection over innovation.
With operational examples like the DTEN, which is still operational today, the challenge is not technical capability but institutional. The problem statement must now shift beyond ICT shortcomings and instead examine leadership, structures, and culture.
Case D: AXELOS Transition From ITIL v3 to ITIL 4 (2019)
The following case provides evidence from the evolution of IT service management (ITSM) frameworks developed by AXELOS. It illustrates how a major global governance framework shifted from a traditional, process-centric model (ITIL v3) to a more adaptive, value-driven model (ITIL 4), reflecting the same principles of technical agility and systems thinking advocated throughout this paper.
In 2019, AXELOS released ITIL 4 to “reshape the established ITIL practices in the wider context of customer experience, value streams, and digital transformation, while embracing new ways of working, such as Lean, Agile, and DevOps” (AXELOS, 2020, p. 7). This marked a deliberate transition away from ITIL v3’s lifecycle model, which had been criticised for its heavy reliance on process conformity and sequential control. As Rance observed, “ITIL V3 is often seen as promoting a waterfall approach to development of new and changed IT services, but many organizations are moving away from this to a much more agile approach” (2018, para. 44).
The rationale behind this transformation paralleled challenges observed in Defence and other complex systems environments. ITIL v3’s rigid process silos often resulted in long lead times, disjointed communication between functional teams, and a focus on procedural output rather than customer-centric outcomes. These limitations reflected the same inefficiencies seen in traditional Defence acquisition models, large batch work, deferred integration, and late verification, where responsiveness was constrained by hierarchical decision structures and compliance checkpoints.
By introducing the Service Value System (SVS) and service value chain, ITIL 4 reframed ITSM as a flow-based ecosystem built around co-creation of value, continuous feedback, and adaptive governance. This model aligned more closely with Lean-Agile and DevSecOps concepts, embedding iterative improvement, decentralised decision-making, and transparency across organisational boundaries.
From a systems thinking perspective, ITIL 4 represents a systemic re-engineering of how value is generated and sustained within socio-technical systems. It removed isolated process queues, promoted end-to-end visibility, and encouraged collaboration across functional domains. In doing so, AXELOS demonstrated that even entrenched global frameworks could pivot from a compliance-driven model to one that prizes adaptability, flow, and human-centred innovation.
For Defence simulation enterprises, the AXELOS case provides a compelling parallel: both domains require integration of complex, interdependent components into cohesive, responsive systems that deliver measurable outcomes under constant change. Just as ITIL 4 redefined service management to emphasise value streams and agility, Defence simulation must embed technical agility and systems thinking within its operational fabric to sustain relevance and readiness in preparation for dynamic threat environments.
Case E: DoD Enterprise DevSecOps Reference Design (2022)
In 2022, the U.S. Department of Defense introduced an Enterprise DevSecOps Reference Design to modernize its approach to software delivery for mission-critical systems. Recognising that modern weapons platforms and information systems are increasingly software-driven, the initiative aimed to deliver resilient software “at the speed of relevance” (U.S. Department of Defense, 2022, p. 7). The design leveraged Microsoft Azure and GitHub technologies to create a secure, cloud-native environment capable of supporting rapid development and deployment cycles.
The implementation focused on Infrastructure as Code (IaC) to automate the creation of secure environments using Azure Resource Manager templates and PowerShell scripting. This automation enabled the provisioning of multi-subscription environments for development, testing, and production, while embedding security controls aligned with NIST 800-53 standards. Continuous integration and delivery were orchestrated through GitHub Actions, which provided a robust pipeline for building, testing, and deploying applications. Security was reinforced through zero-trust principles, notably the mandate to “inspect and log all traffic before acting,” (U.S. Department of Defense, 2022, p. 36) and through integrated monitoring tools such as Azure Monitor, Microsoft Defender for Cloud, and Sentinel.
The outcomes were significant. The DoD achieved a scalable and resilient DevSecOps platform that reduced deployment timelines, improved security posture, and streamlined compliance processes. By automating infrastructure provisioning and embedding security into every stage of the pipeline, the initiative demonstrated how cloud-native services and agile practices could transform software delivery for defense operations. This case exemplifies the practical application of DevSecOps principles in a high-assurance environment, offering lessons for Defence organisations seeking to integrate agility and security into simulation delivery pipelines.
Analytical Summary
Analytical Criteria Validation Across Case Studies.
The comparative analysis of the case studies reveals that both Agile-based and traditional Waterfall approaches contribute distinct strengths to the delivery of Defence simulation capability, with optimal performance achieved when agility is underpinned by disciplined control and assurance. The JCTC/DTEN simulation federation and AMN-TF Emulation cases demonstrated how agile, incremental development replaced sequential tasking with continuous flow, improving responsiveness and throughput while still retaining essential quality controls through structured integration events. In contrast, the more traditional, stage-gated models observed in earlier programs offered superior traceability, documentation rigour, and risk containment, attributes that are seen as critical for systems operating within security-sensitive or safety-assured environments.
The DevSecOps architecture and ITIL4 framework cases underscored adaptability, showing that iterative change management and automation can coexist with compliance and assurance processes to meet emerging mission needs without compromising stability or cybersecurity.
Conclusively, interoperability proved essential for achieving real-time training effects using architectures based on open standards to successfully integrate with C4I and coalition networks, while legacy enterprise ICT environments, though less dynamic, provided dependable control frameworks that safeguarded data integrity and information security. These findings confirm that embedding Technical Agility and Systems Thinking within a robust governance framework enables Defence to harmonise flexibility with control, delivering adaptive, secure, and interoperable simulation environments that achieve high-quality, real-time training effects at the speed of operational relevance.
Discussion
Prior academic treatments of Systems-of-Systems (SoS) and simulation (e.g., SoS, Test and Evaluation (T&E) frameworks and Model-Based Systems Engineering (MBSE) integration models) provide strong conceptual baselines for interoperability and assurance in complex environments. This paper extends that lineage by translating those models into a Defence-specific delivery pattern that combines cadence-based planning, Continuous Integration/Continuous Delivery (CI/CD), and generative leadership. In doing so, it connects theory-led constructs (SoS, T&E, SAFe, and MBSE) with field-validated workflows such as JCTC/DTEN federation and AMN-TF emulation.
Leadership and Vision
At the core of any successful organisation is leadership that defines clear direction, inspires loyalty, and aligns effort with mission priorities. In Defence capability development, stewardship of public funds and compliance are essential. However, excessive caution can obstruct innovation and responsiveness. The U.S. Department of Defense observed that its risk-averse culture, “creates enough obstacles to make it nearly impossible for non-traditional defense companies to contribute to the DoD mission” (Department of Defense, 2023, p. 2).
Westrum (2004) identified three organisational cultures: pathological, bureaucratic, and generative, stating that, “A focus on personal needs leads to a pathological environment, a focus on departmental turf to a bureaucratic style, and a focus on the mission to a generative style” (p. 2). Pathological cultures are power-oriented, bureaucratic and rule-oriented, while generative cultures are performance-oriented, characterised by high cooperation, shared risk, free information flow, inquiry over blame, and implementation of useful novelty. This topology is highly relevant to simulation training, where iterative learning should outweigh rigid compliance.
Transformational and Servant leadership models directly support this need. Wang and Rode found “significant relationships between transformational leadership and subordinate creativity” (2010), while “Servant leaders place the good of followers over their own self-interests and emphasize follower development” (Northouse, 2019, p. 349). Heifetz argued that leadership involves “mobilizing people to tackle tough problems” (1994, p. 15). Together, these models reinforce that effective leadership in simulation requires trust, empowerment, and alignment with purpose.
Military doctrine expresses this as mission command decentralised execution aligned to commander’s intent. During the JCTC era, simulation teams were empowered to iterate, respond to feedback, and integrate across disciplines. This culture of autonomy enabled rapid integration of individuals, groups, and joint audiences. Leadership that communicated intent and trusted teams to deliver results created a generative environment, demonstrating the link between culture, agility, and mission performance.
By embedding leadership behaviours that promote transparency, respect, and continuous improvement, military training organisations can achieve the technical agility needed for future operations. Adaptability and learning must be viewed as essential traits of an operationally ready Defence organisation.
Systems Thinking
A systems-thinking approach provides the structure to measure outcomes, improve flow, and strengthen competency. “For larger more complex simulation based events involving single or multiple real-world mission command devices as well as multiple simulation federates, a well-defined rigorous system of systems initialization process is necessary” (Tolk, 2012, p. 582). In Defence, this includes Network and ICT systems built to deliver real-time simulation training across a spectrum from individual virtual exercises to large-scale constructive joint Headquarters scenarios. Shared infrastructure should ease the burden on individual Services, enabling integrated support for coalition events and C4i stimulation at all levels.
Software systems should enable just-in-time deployment, iterative improvement, and continuous delivery underpinned by leadership and trust. A shared architecture mitigates duplication and cost escalation by standardising interfaces and promoting reuse. Van den Berg et al. note that “DIS and HLA implementations generally assume seamless network connectivity… [but] lack support for multicast protocols” (2016), which limits Defence network performance. The cadence-driven architecture proposed in Figure 5 isolates network-sensitive federates, standardises interfaces, and schedules integration events to sustain performance under enterprise routing constraints. Cadence-based Theatre Development.
A tightly aligned yet loosely coupled architecture provides resilience and agility, enabling component updates without disrupting the system. Figure 5 depicts how predictable update cycles (6–12 months) enhance planning, trust, and responsiveness. Simulation should be viewed as an enterprise ecosystem that links networks, scenarios, and user feedback to ensure mission-ready fidelity.
SAFe supports this shift with cadence-driven planning and continuous learning cycles. Work is deconstructed into small, valuable increments, improving transparency and reducing waste. Agile Release Trains (ARTs) and Solution Trains coordinate incremental delivery and alignment of simulation capabilities, ensuring that evolving scenarios remain operationally relevant.
Continuous learning becomes a systemic imperative. As the Unmanned Systems Integrated Roadmap 2017-2042 warns, “For the most demanding adaptive and non-deterministic systems, a new approach to traditional TEVV will be needed” (p. 10). Simulation can meet this need through iterative improvement and feedback-driven testing that augment or replace costly live training.
McDermott highlights the challenge of complex integration: “the number of interconnections among constituent systems, often imprecisely defined or proprietary interfaces, … can pose an overwhelming challenge” (2012, p. 3). Zeigler and Sarjoughian emphasise that SoS components “reflect diverse world views and heterogeneous formalisms that must be integrated together in the composite model” (2018, pp. 7-8). Friedenthal et al. describe MBSE as shifting “from controlling the documentation about the system to producing and controlling a coherent model of the system” (2015, p. 4). Together, these insights affirm that Defence must manage diverse system models through coherent enterprise representation, a principle reinforced in Table 3, where interoperability was validated across case studies.
Team & Technical Agility
Technical agility relies on culture, leadership, and teamwork to integrate Agile, DevSecOps, and Lean practices. SAFe defines Technical Agility as encompassing “team and technical practices that enable high-quality, fast flow of value” (SAFe, 2024).
Figure 6 provides a proposed example of a simulation-focused SAFe framework. Admiral Richardson stated, “It’s about the team that can bring the people, the process, and the technology together to learn the fastest… that’s the team that has the advantage” (Richardson, 2018; as cited in Vogel-Walcutt et al., 2018, p. 3). Technical agility enables Defence organisations to meet demanding timelines and dynamic environments. TTA, a core SAFe competency, empowers cross-functional teams to develop modular, rapidly integrated solutions aligned to mission requirements. Scaled agile framework applied to simulation training.
Teams with decision-making autonomy can investigate, prototype, and validate solutions in parallel with evolving needs. This ensures capability delivery remains aligned with operational demands, while preserving system reliability and assurance.
Simulation delivery would benefit from DevOps-enabled workflows that automate build, integration, and testing. “Ansible is a great tool for deployment as well as configuration management. Using a single tool for both configuration management and deployment makes life simpler” (Hochstein et al., 2017, p. 2), allowing simulation environments including virtual machines and federate start sequences to be reproducibly deployed on demand, reducing manual overhead and improving security and consistency.
To support secure, distributed simulation environments, Software-Defined Wide Area Networking (SD-WAN) can dynamically route traffic and prioritise simulation data across Defence and coalition networks. Paired with elastic compute infrastructure hosted within on-premises platform-as-a-service environments, simulation workloads can scale to match exercise demands, improving cost-effectiveness, resilience, and surge capacity.
SAFe’s core value of transparency would promote visibility across the simulation delivery pipeline. This can be achieved through Kanban systems, value stream mapping, and flow metrics that track scenario development, software changes, and system configuration. As Forsgren et al. observed, “our measure should focus on outcomes not output” (2018, p. 47). Disruption to these flows increases the risk of rework or degraded training support. In practice, flow efficiency (e.g., active-to-waiting work ratio), deployment frequency, and mean time to restore service, provides actionable leading indicators for simulation delivery health. While this paper does not present new measurements, these indicators are intended as the basis for future empirical assessment of the proposed model’s effects on readiness and rework.
Figure 7 depicts how a Value Chain encompasses the system as a whole, focusing an organisation on customer-driven, flow-based delivery with agility and feedback loops. Simulation delivery value chain.
SAFe’s “Measure and Grow” methodology assesses progress across outcomes, flow, and competency. These metrics evaluate if simulation solutions meet user needs, track delivery efficiency, and measure team agility in applying technical practices.
JIT delivery of simulation assets such as terrain databases, agent behaviours, and force structures enhances reuse, reduces waste, and aligns with MBSE and Model-Based Mission Engineering (MBME). MBSE “puts models at the center of system design” (Shevchenko, 2020) and ensures that “the requirements, design, analysis, verification, and validation associated with the development of complex systems” … “improves the analysis of the system and reduces the number of defects that are commonly injected in a traditional document-based approach” (Shevchenko, 2020). These assets can be assembled into composable, testable components that support agile delivery pipelines. The continuous delivery model tailored for Defence simulation and illustrated in Figure 8 can maintain an always-ready posture. Test automation and synthetic data validation allow teams to deliver high-quality training systems under tight timeframes. CI/CD pipeline for simulation delivery.
As discussed in the Background section of this paper, the rapid three-month creation of the AMN-TF emulation illustrated the effectiveness of agile planning, empowered teams, and modular design. Using containerisation like Docker, model-driven engineering, and DevSecOps practices supports the adaptive deployment of simulation systems. These frameworks strengthen resilience, interoperability, and responsiveness, aligning delivery with real-world Defence training needs.
Conclusion
Simulation must deliver accurate representations of Defence capabilities, systems, tactics, and strategies to enable training for highly skilled personnel across all domains. In future conflicts, Australia’s advantage will be our cognitive edge. As General David Berger noted, “we need to focus on training and simulation Force on Force that drives our leaders to think” (2021).
To realise this advantage, Defence must cultivate a trust-based, mission-focused culture underpinned by Systems Thinking and Technical Agility. This approach demands cross-functional autonomy, adaptive leadership, and delivery aligned with strategic outcomes as outlined in the DSR. Effective simulation delivery relies on a modern, technically skilled workforce guided by leaders who empower teams, flatten hierarchies, and promote continuous improvement. Through SAFe’s Measure and Grow approach and value stream mapping, Defence can identify delivery bottlenecks and strengthen integration across simulation and ICT systems.
Embedding TTA within SAFe equips teams to adjust dynamically to late-emerging requirements and align with operational needs. Adopting DevSecOps practices within a loosely coupled architecture, underpinned by unified Defence simulation networks and scalable compute resources, enables continuous delivery of secure, resilient, and cross-domain training environments. Equally, traditional Waterfall models retain value where control, assurance, and risk mitigation are paramount, providing structured documentation and compliance pathways essential to safety-critical or classified systems. The strength of future simulation delivery will lie in balancing Agile flexibility with disciplined governance, ensuring that adaptability does not compromise assurance or information security.
Simulation should no longer be viewed as a peripheral support activity but as a mission-critical capability central to force preparedness and joint readiness. A systems-oriented, technically agile ecosystem supported by empowered leadership, prioritised funding, common infrastructure, and a mission-driven workforce can achieve integrated, outcome-focused training effects that enhance Australia’s operational readiness.
Limitations and Future Research
This practice-based study draws primarily from the author’s professional experience within Defence simulation programs. While this provides valuable applied insight, it also introduces potential bias and limits generalisability. To mitigate this, methodological triangulation was employed by cross-referencing experiential findings with authoritative literature, Defence doctrine, and IEEE standards. Case studies were validated against independent operational exemplars and freely available documentation to maintain consistency and reduce subjectivity.
The use of open-source and unclassified literature restricted access to detailed technical and coalition data. Moreover, the perspectives of Defence personnel, industry partners, and allied stakeholders were outside the scope of this research but would provide a more balanced understanding of cultural and operational influences.
Future work should pursue empirical validation of the proposed model using measurable flow, competency, and readiness metrics. Comparative studies assessing the performance of SAFe and Technical Agility against traditional Defence training models would strengthen the evidence base. Incorporating interviews, surveys, and structured evaluations with Defence stakeholders would further illuminate organisational culture, leadership effectiveness, and barriers to adoption.
By addressing these limitations, future research can move beyond conceptual frameworks to provide tangible evidence of how Systems Thinking and Technical Agility influence Defence simulation delivery and operational preparedness. Instrumenting the delivery pipeline with flow and reliability metrics will enable Defence to quantitatively assess improvements in readiness, interoperability, and rework reduction. Embedding these practices will operationalise the transformation objectives of the DSR and NDS, elevating simulation from episodic project outputs into a persistent, cadence-based training capability that delivers measurable, real-time value across all Defence training, thereby enhancing Australia’s preparedness.
Footnotes
Acknowledgements
The author(s) wish to thank Paul Meilak for his review comments.
Author contributions
Greg Quilliam conceived, drafted, and revised the manuscript. Allison Quilliam provided further revision and editorial review.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
No funding was sought for the authoring, research or review of this paper.
Ethical Considerations
Not applicable. This research did not involve human participants or animals.
Informed Consent
Not applicable.
Consent for Publication
Not applicable.
Data Availability Statement
No datasets were generated or analysed for this study.