By Paul R Salmon FCILT, FSCM
Introduction – The Case for Change
Disruption is no longer a rare event in supply chain management; it is the new operating environment. From pandemics to geopolitical tensions, from the Suez Canal blockage to semiconductor shortages, supply chains are now expected to operate in a world defined by volatility, uncertainty, complexity, and ambiguity.
For decades, organisations have relied on monolithic enterprise platforms such as Enterprise Resource Planning (ERP) and Advanced Planning Systems (APS) to manage the complexity of procurement, inventory, and distribution. These systems, while robust, were designed for relatively stable operating conditions. Their strength lies in consistency and control, not agility.
Today, that lack of agility is a liability. Traditional platforms often require years to upgrade and millions in investment to adapt. When disruptions strike, organisations can find themselves locked into rigid systems unable to pivot quickly enough.
Enter Decision Engineering and Orchestration (DEO). Rather than demanding “rip and replace” transformations, DEO offers a way to plug agility into existing systems. It leverages composable architecture — modular, interoperable software building blocks that can be connected, reconfigured, or replaced without tearing down the entire stack. This approach enables organisations to evolve their decision-making capability continuously, adapting as the environment changes.
In short: DEO provides a path for supply chains to become living, adaptive ecosystems, rather than brittle machines vulnerable to every shock.
What is Decision Engineering and Orchestration?
At its core, DEO is both a methodology and a technology approach. It combines three essential ingredients:
Decision Engineering – The structured design of decision processes using data, analytics, and optimisation models. Instead of relying solely on instinct or siloed planning, organisations engineer decision pathways that consider constraints, risks, and trade-offs. Orchestration – The coordination layer that integrates data, tools, and workflows across functions, ensuring that decisions made in procurement align with those in production, logistics, and customer service. Composable Architecture – The software enabler. Think of a system made from interoperable “bricks.” Each brick — whether AI demand sensing, risk analytics, or simulation modelling — can be slotted in or swapped out without breaking the overall system.
This differs sharply from traditional system integration. Classic integration connects systems so they can share data. Decision orchestration goes further: it aligns and synchronises decisions across the enterprise, making sure each choice reinforces the overall supply chain strategy.
The analogy is simple: integration makes sure everyone is speaking the same language; orchestration ensures they’re all reading from the same score.
Why Composable Beats Monolithic
The limitations of monolithic supply chain platforms are becoming increasingly clear:
Rigidity: Upgrades require vendor roadmaps, long testing cycles, and major costs. One-size-fits-all: Customisation is difficult, leading to compromises in capability. Obsolescence risk: Emerging technologies like AI, blockchain, or digital twins can’t easily be plugged in. Rip-and-replace pain: Organisations often hesitate to modernise because replacing an ERP is like open-heart surgery on the business.
By contrast, a composable approach:
Allows organisations to adopt targeted innovations quickly. Want to try AI-based inventory optimisation? Slot it in. Reduces risk and cost by avoiding full system replacement. Supports continuous evolution: systems improve over time, not in disruptive leaps. Creates a future-ready foundation for technologies not yet mainstream today.
This is why Gartner calls composable supply chains the path to “resilient enterprise systems.” Instead of betting everything on one platform, leaders build flexible ecosystems where innovation and resilience reinforce each other.
DEO in Action – Plugging the Gaps
To see DEO in practice, consider how different sectors are applying composability to enhance agility.
1. Inventory Optimisation in Retail
During the COVID-19 pandemic, global retailers faced unprecedented demand swings: groceries surged, fashion plummeted, home fitness equipment spiked. One major retailer avoided widespread stock-outs by integrating an AI-powered demand sensing module alongside its legacy ERP. The plug-in model used point-of-sale and external signals (weather, social media, mobility data) to fine-tune forecasts at the SKU level. The ERP remained the system of record, but the AI “brick” delivered agility without disruption.
2. Simulation Modelling in Defence Logistics
In defence supply chains, the cost of failure is far greater than lost sales; it can compromise mission success. A NATO-aligned military logistics command applied DEO by introducing a simulation modelling tool that could stress-test inventory strategies under contested logistics conditions (e.g., cyber disruption, fuel shortages, denied access routes). Instead of redesigning its entire supply system, it plugged the simulation engine into its existing planning environment. Decision-makers could then war-game different strategies before committing resources.
3. Supplier Risk Management in Manufacturing
An automotive manufacturer, hit hard by semiconductor shortages, implemented a risk analytics module that ingested data from suppliers, shipping routes, and geopolitical risk indices. This new block identified early-warning signals of potential disruption (e.g., factory shutdowns in Asia). By orchestrating this data into procurement decision workflows, the manufacturer reduced its dependence on single-source suppliers.
4. Patient-Centric Supply in Healthcare
Hospitals during the pandemic faced challenges balancing ventilator supply, oxygen cylinders, and PPE. A European healthcare network introduced a digital twin of its supply chain — a virtual mirror built on top of existing systems. The twin allowed planners to test “what if” scenarios, such as regional outbreaks, and orchestrate reallocation of equipment between hospitals. Again, no rip-and-replace was required: the twin plugged into existing procurement and inventory systems.
These examples illustrate the power of DEO: plugging capability gaps rather than rebuilding entire systems.
Decision Agility as Competitive Advantage
In volatile environments, speed and quality of decisions are the ultimate differentiators. DEO enhances both.
Faster response times: AI-assisted orchestration means signals of disruption can trigger proactive action, not reactive firefighting. Resilience through options: Modular systems allow supply chains to test and pivot strategies rapidly. Optimised performance: Improved decisions reduce excess inventory, lower transport costs, and improve service levels simultaneously.
Consider Amazon: while not labelled as DEO, its approach exemplifies decision agility. Every part of its supply chain technology stack can evolve independently. That composability underpins its ability to pivot from books to groceries to pharmaceuticals — while maintaining consistent service standards.
For organisations across sectors, the lesson is clear: decision agility = competitive advantage.
Challenges and Considerations
Of course, DEO is not a magic bullet. Leaders must manage several challenges:
Data Quality and Governance Composable modules are only as good as the data flowing into them. Poor master data management will undermine even the best AI optimiser. Integration Standards Without agreed data formats and APIs, plugging in new bricks risks creating spaghetti systems rather than elegant ecosystems. Skills Gap DEO requires a new type of professional: the decision engineer — fluent in supply chain, analytics, and systems thinking. This skillset remains scarce. Change Management Employees can suffer “tool fatigue” if every new challenge brings another plug-in. Clear orchestration is needed so tools feel like a seamless system, not a cluttered toolbox. Governance of Decision Rights As decision-making becomes more automated, organisations must define who owns the final call — humans, algorithms, or both.
Addressing these challenges is as much about leadership and culture as it is about technology.
The Future of DEO
Looking ahead, DEO is likely to evolve in three major directions:
Digital Twins as Orchestration Hubs Instead of standalone modules, digital twins will serve as the integration layer, orchestrating data and decisions across the enterprise. AI Copilots for Decision-Makers Generative AI and copilots will sit alongside planners, offering recommendations, trade-off analysis, and even auto-executing routine decisions. Autonomous Supply Chains Over time, DEO could move toward semi-autonomous supply chain ecosystems, where human oversight focuses on exceptions and strategy rather than day-to-day firefighting.
Defence and humanitarian supply chains are likely to act as proving grounds, given their high-stakes environments and complex, distributed networks. Lessons from these sectors will then filter into commercial practice.
Conclusion – Building Resilient Supply Chains Brick by Brick
Decision Engineering and Orchestration represents a fundamental shift in how organisations manage supply chains. Instead of ripping out legacy systems or accepting their limitations, DEO provides a way to add agility, intelligence, and resilience — one composable block at a time.
This approach ensures that supply chains are not frozen in time but can adapt continuously to new challenges. The result is a more resilient, innovative, and competitive organisation.
As supply chain leaders, the question is no longer whether disruption will happen — but how ready we are to respond. DEO offers a pragmatic, powerful answer: build resilience brick by brick, and orchestrate decisions with agility.
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