The Cost Benefits of Interoperable Digital Twins

21 July 2025

This blog explores the financial and operational benefits of adopting interoperable digital twins in manufacturing, covering technical maturity levels, integration strategies, real-world applications, and future-proofing tips.

Interoperability, which is a digital twin’s ability to exchange data, collaborate, and adapt within diverse technology environments, is what drives scalable cost benefits and prolonged ROI. Without interoperability, digital twins are siloed entities that risk underperformance or inflated costs.

This article unpacks the cost implications of adopting interoperable digital twin platforms in manufacturing while navigating challenges in deployment. From technical maturity levels and integration approaches to real-world use cases and future-proof strategies, it serves as a comprehensive guide for organizations exploring the financial advantages of interoperable digital twins.

The Technical Definition of Interoperability

Digital twin interoperability spans these critical layers of the technology stack:

1. Technical Interoperability This foundational level ensures that digital twins and their associated physical systems can establish basic connectivity and data exchange.

2. Syntactic Interoperability At this stage, systems are able to exchange information using standardized data structures and communication protocols. This ensures that devices, regardless of manufacturer or platform, can format and transmit data in a way that other systems can interpret without errors.

3. Semantic Interoperability Going beyond format compatibility, this level ensures that different systems not only share data, but also understand its meaning. It involves aligning terminologies and data definitions so that the receiving system can interpret information as intended.

4. Pragmatic or Operational Interoperability Here, the emphasis is on how data is interpreted and applied in real-world operations. This level enables digital twins to actively support decision-making and execution processes.

5. Dynamic Interoperability This level introduces adaptability. Systems at this stage are capable of adjusting to real-time conditions and evolving operational needs.

6. Organizational Interoperability The highest level, often overlooked yet highly transformative, focuses on the alignment between different organizations, stakeholders, or vendors involved in a digital twin ecosystem.

Connectivity alone does not equate to interoperability. While a connected system may communicate, it doesn’t guarantee optimal collaboration. Without shared standards or adaptable frameworks, data exchange can lead to inefficiencies, errors, or lost insights; undermining the potential ROI of digital twin platforms.

To grasp the importance of interoperability, consider the USB protocol. A universal standard that allows devices to "discover" one another and work instantly, USB eliminates the need for bespoke adaptors. Digital twin interoperability frameworks aim to mimic this simplicity, enabling seamless system discovery and integration across manufacturing ecosystems.

Digital Twin Maturity Levels and the Role of Interoperability

Digital twins evolve through six widely recognized maturity levels. Understanding their progression highlights how interoperability compounds cost benefits:

Level 1: Digital Representation of Assets

At this initial stage, a digital twin provides a precise virtual copy of the physical asset. This includes an exact rendering of all static features and the captured status of any dynamic processes at a given moment. While basic, this stage allows for foundational situational awareness by digitally reflecting the current state of the physical system.

Level 2: Integration of Process Models

Building on the replicated digital asset, this level introduces models related to the asset's physical and business processes. These models use historical data to simulate and assess how the asset might respond to real-world events, thus extending the Digital Twin's capability from representation to interpretation and estimation.

Level 3: Real-Time Data Synchronization

At this stage, sensor networks feed real-time data into the digital twin, enhancing both static and dynamic process representations. This real-time link allows the Digital Twin to respond to both critical and routine changes in the physical world, providing comprehensive, timely situational awareness and enabling responsive decision-making.

Level 4: Active Interaction with Physical Systems

This level enables a two-way communication channel between the Digital Twin and its physical counterpart. With real-time simulations and insights, users can issue remote commands, and the Digital Twin can interact directly with the physical system. This creates a feedback loop that supports remote operation and real-time control.

Level 5: Autonomous Decision-Making

At this advanced stage, the digital twin can independently make operational and maintenance decisions. It uses real-time and historical data to optimize processes, reduce reliance on human input, and minimize errors. Importantly, the Digital Twin can also learn from past actions, gradually becoming an adaptive, self-improving system.

Level 6: Cross-System Collaboration

The highest maturity level enables a Digital Twin to communicate and coordinate with other digital twins across different systems. Through this interoperability, multiple Digital Twins can jointly analyze data and make decisions that optimize performance not just locally, but across an entire system-of-systems (SoS) network.

Each progressive level reduces inefficiencies and improves decision-making. For instance:

Level 4 minimizes downtime, which translates to millions in annual savings for a manufacturing plant.
Level 5 reduces labor costs, allowing resources to be allocated to high-value tasks.
Level 6 enables interoperable digital twin platforms to achieve system-wide optimizations, saving costs across logistics, procurement, and production processes.

Technical maturity correlates closely with interoperability readiness. Manufacturers that reach Level 6 can make use of interoperable systems for exponential cost reductions. Conversely, fragmented ecosystems stuck at Levels 1-3 experience diminishing ROI due to disconnected technologies and duplicated efforts. Therefore, Level 4 is the recommended minimum maturity level for manufacturers aiming to achieve meaningful ROI.

From Point-to-Point Integration to System-Level Frameworks

The Current Cost of Bespoke System Integration

Point-to-point integration, a traditional method of connecting systems individually, remains widely used but is increasingly seen as inefficient for scaling complex architectures such as digital twins. While the global system integration market, which includes point-to-point approaches, is valued at over $400 billion (Grand View Research, 2023), each additional component in a point-to-point setup significantly increases integration complexity, cost, and maintenance overhead.

Limitations of Point-to-Point Approaches

Challenges with point-to-point integration include:

Skyrocketing costs for maintenance and upgrades.
Difficulties adapting legacy systems to modern IoT and AI technologies.
Increased chances of error propagation across communication lines.

Benefits of Framework-Driven Interoperability Models

Adopting framework-driven interoperability models slashes these costs and inefficiencies. Frameworks standardize communication, enable plug-and-play integration, and adapt more easily to emerging technologies. For instance, interoperable digital twin ecosystems create modular environments that allow manufacturers to upgrade individual pieces without disrupting core operations.

Cost Savings Enabled by Interoperable Digital Twins

Lower Integration and Deployment Costs

Interoperability eliminates expensive bespoke integration setups, reducing infrastructure costs. Standardized frameworks accelerate deployment timelines, leading to faster ROI realization.

Reduced Error Propagation and System Downtime

When systems function in isolation, error propagation can reverberate across workflows. Interoperable digital twins mitigate these risks, ensuring teams benefit from cleaner data streams and fewer operational interruptions. Real-time predictions avoid unplanned downtime, often saving millions annually.

Faster Time-to-Value and Scalability

Modular interoperable systems enhance flexibility, allowing organizations to scale up efficiently. Manufacturers make use of interoperable systems to decrease project timelines for new installations and expansions; achieving faster time-to-value returns. For rapidly growing industries, this agility optimizes long-term cost structures.

Multi-System Interoperability in Supply Chains

Integrating Across Ports, Logistics, and Manufacturing

Consider a global supply chain integrating digital twin frameworks across shipping ports, logistics fleets, and factory floors. Rather than siloing systems, interoperability ensures each node collaborates seamlessly:

Factory twins predict inventory needs.
Logistics twins adapt delivery schedules.
Port twins optimize loading and unloading processes.

The result is end-to-end visibility across supply chains, reducing latency and IT overheads. This interconnected view streamlines operations and enhances productivity for manufacturers managing complex, distributed supply chains.

System-of-Systems Value

Interoperable frameworks transform cost benefits beyond individual optimization. Rather than optimizing workflows at discrete points, the system-of-systems approach compounds savings across an organization’s entire operational landscape, unlocking exponential ROI.

Strategic Considerations: Designing for Long-Term Interoperability

Why Decisions Today Impact Costs Tomorrow

System architecture decisions made during the digital twin adoption phase have direct implications on operational costs. Manufacturers that adopt customizable, modular frameworks experience long-term savings compared to those employing rigid, bespoke integrations.

To ensure long-term interoperability:

Data Standardization: Commit to universal data formats ensuring seamless technology updates.
Trust Frameworks: Implement security protocols and privacy measures assuring reliable exchanges between systems.
Technology Neutrality: Opt for vendor-agnostic solutions to maintain flexibility across diverse digital twin ecosystems and avoid long-term costs from vendor lock-in.

The Future of USB-Like Interoperability Across Digital Twin Ecosystems

The vision for digital twin interoperability mirrors the simplicity of USB functionality. Manufacturers can look forward to ecosystems where operational components “plug and play,” adapting dynamically to new workflows, applications, and technologies. Rooted in IoT best practices like standardized protocols, modular design, and edge-to-cloud connectivity, this evolution promises smarter capital allocation and operational savings across industries.

For manufacturers, it is not merely a feature; it is a system design imperative that drives cost optimization, scalability, and long-term competitiveness.

Organizations must shift from reactive iterations to proactive architecture planning to benefit fully from interoperable digital twin platforms. Decisions made today in terms of frameworks, standards, and adaptability will determine operational costs and ROI in the years to come.

Want to delve deeper into how interoperable digital twins can transform your manufacturing processes? AIOTEL’s TWINVRSE™ platform enables scalable, IoT-driven, AI-first digital twin deployments tailored to your business needs. Reach out to our team to see the future of efficiency in action!