By Paul R Salmon FCILT FSCM FCMI
Introduction
Support modelling and analysis is no longer a niche technical function in UK Defence—it is a strategic enabler that underpins readiness, resilience, and operational advantage. Yet despite significant investment in modelling capabilities, the impact of support modelling is often blunted by a fragmented, siloed approach. The newly published 2024 Defence Support Modelling and Analysis Framework makes it clear: to deliver better support to the Front Line, Defence must urgently move from pockets of excellence to a fully integrated, enterprise-wide capability.
This article explores the risks of siloed support modelling, the benefits of a joined-up approach, and the five critical change interventions identified to turn ambition into action.
The Problem with Siloed Modelling
Across the Defence Support Enterprise (DSE)—which includes DE&S, SDA, Front Line Commands (FLCs), and industry partners—modelling and analysis capabilities have evolved organically. While centres of excellence exist, notably in inventory modelling within DE&S or strategic asset management within Strategic Command, there is no unified strategy, no common prioritisation framework, and no consistent architecture or tooling.
The results?
Duplicated effort, with multiple teams modelling the same phenomena in different ways. Incoherent assumptions, leading to mismatches between logistics plans and engineering support. Missed opportunities, where supportability insights are not exploited in platform design phases. Slow and reactive decision-making, due to fragmented data, tools, and organisational structures.
This fractured landscape is no longer acceptable in an era where geopolitical threats are increasing and operational agility is paramount.
The Case for an Integrated Approach
A joined-up support modelling and analysis approach transforms fragmented insight into strategic foresight. It enables Defence to:
1. Model Support as a Whole System
No single model—be it for spares, personnel, facilities, or maintenance—tells the whole story. Only by connecting these models across domains can Defence simulate “what if?” scenarios, test resilience under stress, and understand trade-offs between cost, availability, and readiness.
2. Embed Support Thinking Early in the Lifecycle
Designing in supportability from the concept stage avoids the costly mistake of building platforms that are unsupportable by design. Integrated modelling ensures that future maintenance, training, and logistics demands are visible and optimised from the outset.
3. Make Informed Investment Decisions
Support modelling is a core enabler of evidence-based decision-making. Whether deciding how to resource upgrades, introduce new capabilities, or streamline supply chains, robust modelling ensures scarce resources are deployed where they add most value.
4. Strengthen Data-Driven Decision Making
The framework rightly identifies high-quality, digitised, and assured data as foundational. A joined-up approach helps define what data is needed, aligns it across programmes, and ensures that AI and digital twins have the fuel they need to deliver insight.
Five Change Interventions: The Route to Integration
The 2024 Framework identifies five interventions—concrete actions that, if delivered, will replace today’s siloed approach with an integrated, digitally enabled, through-life capability.
CI-1: Plan and Prioritise Modelling Across Defence
Support modelling must be driven by strategic demand signals, not ad hoc tasking. A new prioritisation framework will balance resources, match modelling activity to Defence priorities, and ensure effort is not wasted on low-value analysis.
CI-2: Map the End-to-End Modelling Lifecycle
Too often, support modelling begins only once equipment is in-service. This intervention expands modelling to cover the full CADMID lifecycle—concept to disposal—ensuring coherence across phases and actors.
CI-3: Integrate Architecture and Tools
Today’s modelling landscape is cluttered with disconnected platforms and legacy systems. This intervention ensures Defence Digital and Business Modernisation for Support (BMfS) deliver a consistent, scalable, and secure architecture tailored to support needs.
CI-4: Drive Data Quality and Governance
Modelling is only as good as the data it uses. This intervention defines clear data requirements, aligns them with ongoing improvement initiatives (e.g. Kraken, Veritas, DDAP), and ensures support data is curated, accessible, and shareable.
CI-5: Build a Skilled, Integrated Workforce
A high-impact modelling function depends on people as much as tools. This intervention will identify current and future skills needs, ensure suitable qualifications across Defence and industry, and build a collaborative modelling community with shared standards.
Joined-Up Modelling in Action: What Good Looks Like
Imagine a future scenario where a new armoured platform is being designed:
At the concept stage, digital twins are used to simulate platform supportability, with input from engineers, logisticians, and maintainers across MOD and industry. Support scenarios are tested using integrated models—fleet sizing, maintenance intervals, facilities, and training pipeline all stress-tested under various operating conditions. Procurement decisions are informed by a Whole Life Cost model, not just upfront capital cost. As the platform enters service, sensor data feeds predictive maintenance models, linked to inventory management tools, which trigger automated resupply requests based on real usage rather than forecasted consumption. A central dashboard offers real-time performance insight—linking modelling, analytics, and actual performance to optimise readiness.
This is not science fiction—it is an achievable, near-term reality if Defence commits to an integrated support modelling future.
Risks of Standing Still
Failure to join up support modelling is not a neutral choice—it actively damages Defence’s ability to deliver.
Platforms will remain unsupportable, with escalating sustainment costs. Readiness will suffer, as support solutions fail under stress or are too slow to adapt to emerging threats. Resources will be wasted, as poorly prioritised analysis fails to add value. Defence will fall behind allies and adversaries, who are investing heavily in AI-enabled logistics and predictive sustainment.
Conclusion: From Framework to Force Multiplier
The 2024 Support Modelling and Analysis Framework provides a clear vision: a coherent, collaborative, digitally driven modelling capability that enhances operational capability. But vision alone is not enough. We must deliver the interventions, secure senior endorsement, resource the change, and—most importantly—foster a culture where modelling is not seen as an optional add-on but as a fundamental tool of command.
Support modelling is not about tools, spreadsheets, or software. It is about decision advantage. And in a contested, rapidly evolving battlespace, that may prove to be our most decisive capability.
Paul R Salmon FCILT FSCM FCMI is Chair of the CILT Defence Forum and Lead Data Steward for Support in DE&S. He is a champion of evidence-based decision making in defence logistics and has authored multiple articles on support modelling, data governance, and sustainment strategy.
Leave a Reply