Supply chain control towers and digital twins: Do they really make supply chains less fragile?

In this context, the concepts of supply chain control towers and digital twins are increasingly promoted as a “new toolkit” for risk management: one provides near-real-time oversight of the present, the other lets organizations test-drive the future. The digital-twin-in-logistics market was valued at roughly USD 1.2 billion in 2023 and is projected to grow at more than 25% annually between 2024 and 2032. But do these technologies truly make supply chains less fragile, or will they become expensive slideware if companies fail to prepare properly?

What a control tower is – and what it isn’t

Gartner defines a supply chain control tower as the combination of people, process, data, organization and technology that captures and uses (near) real-time operational data across the business ecosystem to provide enhanced visibility and decision-making. IBM describes it as a connected, personalized dashboard that centralizes data, KPIs and events across the supply chain, enabling organizations to understand, prioritize and resolve critical issues in real time.

Vendors such as SAP and OpenText emphasize three core value layers: end-to-end visibility, analytics and forecasting, and process orchestration – meaning not just raising alerts but recommending or triggering response scenarios. Accenture uses the term “true supply chain control tower” to describe a setup that brings people, processes, technology infrastructure and data together in new ways of working that can evolve as business conditions change.

For Vietnamese companies with multiple plants, warehouses and markets, the core question should not be “Which vendor’s control tower should we buy?” but “Where are we weakest across the trio of visibility, analytics and orchestration?” Some organizations lack basic multi-node inventory visibility; others have plenty of data but no cross-functional governance for acting on alerts. The best control tower is the one that solves concrete, prioritized problems, not the one that looks most like what “global leaders” are using.

Digital twins: from modelling to a risk “laboratory”

If control towers help organizations see the present more clearly, digital twins help them “rehearse” the future. McKinsey describes digital twins as virtual models fed continuously with real-world data about assets, people and processes, enabling leaders to experiment, forecast and optimize before making changes in the physical world. Recent academic work on digital twins in logistics and supply chain management highlights their potential to support network design, demand planning, inventory allocation and disruption scenario analysis.

A 2024 study on digital twinning and global supply chains examined three companies in different industries and found that digital twins improved key performance indicators by revealing bottlenecks and testing what-if scenarios around suppliers, transportation routes and inventory levels. However, it also warned that the time and financial costs are significant, limiting wider adoption for now. Other analyses estimate that digital twin applications in logistics will grow by more than 25% annually, spurred by the need to simulate risks and optimize networks under prolonged uncertainty.

In Vietnam, consulting projects are beginning to use digital twins to optimize plant–warehouse–port networks, modelling different production-shift and transport-route scenarios as manufacturers relocate capacity and factor in rising labour and land costs. One 2025 insight report notes that digital twins are “reshaping” parts of Vietnam’s logistics and supply chain landscape as companies seek AI-powered simulations to support decisions on cost, service and resilience.

Four prerequisites so control towers and digital twins don’t become “PowerPoint projects”

The first is data and integration. All credible sources agree that without clean, timely, multi-source data, control towers and digital twins remain attractive models on a screen. Data must be gathered from suppliers, transport, plants, warehouses and sales channels, and then synchronized and standardized. Investment in integration platforms – APIs, IoT, EDI – and internal data governance is a non-negotiable foundation.

The second is process and decision rights. Gartner urges chief supply chain officers not only to invest aggressively in advanced visibility but also to build iterative scenario-planning capabilities tied to commercial outcomes. If alerts from the control tower are not linked to clear playbooks – who does what, within which timeframe, following which scenarios – they will simply accumulate in an inbox with no real impact.

The third is people and organizational change. Studies repeatedly highlight an uncomfortable truth: most failures in supply chain technology projects stem from organizational capability, not from the tools themselves. Control towers and digital twins require new roles – planners who can interpret analytics, data specialists who understand operations, translators between IT and business – not just an expanded IT team. Training, internal communication and linking KPIs across functions to supply chain performance metrics are all essential.

The fourth is roadmap and ROI. McKinsey advises against launching “end-to-end” digital twin programs from day one; instead, companies should start with a narrow use case with clear impact – for example, network optimization for a strategic product family – and expand from there. Likewise, a control tower should begin as a minimum viable product focused on a few critical flows, rather than trying to cover every trade lane and supplier tier at once.