Digital Twins in GRC: Risk That Is Simulated, Not Just Documented
In today’s turbulent global landscape, risk is no longer something that can be managed solely through static policies, controls, and spreadsheets. It is dynamic, systemic, and interdependent — flowing across organizational silos, cascading through supply chains, and constantly evolving in response to regulatory, geopolitical, environmental, and technological forces that impact decision-making and an organization’s ability to reliably achieve objectives. To navigate this complexity, organizations need GRC solutions/tools that are equally dynamic and adaptive.
One of the most promising advancements in this space is the use of digital twins for Governance, Risk Management, and Compliance (GRC). Digital twins — virtual replicas of business systems, processes, or ecosystems that are continuously updated with real-world data — provide a unique capability for modeling uncertainty, visualizing interdependencies, and simulating the impact of risk and change (e.g., regulatory change, business change).
This idea came to life vividly in a recent supplier risk workshop I conducted in Madrid, Spain. Two large global manufacturers expressed their ambition to use digital twins to simulate the impacts of disruption events — from climate-related catastrophes to the geopolitical shock of a potential conflict in the Taiwan Strait. These conversations underscore the strategic value of digital twins in enhancing organizational resilience and proactive decision-making.
Then yesterday, I met with a life sciences firm in Switzerland that is in the midst of an RFP. They told me that they are specifically looking for a GRC platform that supports digital twins to simulate risk and regulatory change on their enterprise.
Simulation is the ultimate value of the story, but is built on documenting the current state of the organization and GRC . . .
In my presentations and conversations with organizations implementing business-integrated GRC strategies (GRC 6.0), I emphasize that the first and most accessible use case for a digital twin is to establish a real-time, dynamic view of the current state of GRC. Even before simulation, this initial visibility delivers meaningful value — especially for organizations earlier in their maturity journey. A digital twin of the organization (DTO) serves as a foundational representation of how risk, controls, compliance, and objectives interact across the enterprise. This “current state map” of the organization’s GRC architecture is the low-hanging fruit that enables better alignment, communication, and accountability.
Once this foundation is in place, simulation becomes the next frontier: scenario modeling, table-top exercises, micro-simulations, and war-gaming. But without an accurate digital reflection of the current state, the insights from simulations will be incomplete or misaligned.
Understanding Risk & Resilience Management at Multiple Levels
To appreciate the transformative potential of digital twins, it’s helpful to distinguish GRC 20/20’s three levels of risk management capability within organizations:
- Strategic Risk & Resilience Decision Support. At this level, risk is used to evaluate and guide organizational decisions: market expansion, new product development, capital allocation, mergers, and acquisitions. This context provides the most business value, yet it is often the least structured in many enterprises. Digital twins help model how external conditions and internal shifts affect strategy and long-term performance — enabling resilient, evidence-based decisions. This is what what Alex Sidorenko refers to RM2 (Risk Management v2).
- Objective-Centric Risk & Resilience Management. This layer focuses on managing uncertainty in the achievement of specific objectives — financial, operational, regulatory, legal, ESG, and beyond. These objectives cascade from the strategic level and exist across entities, departments, processes, projects, assets, and third-party relationships. Digital twins map these layers and the relationships between risks, objectives, and performance — creating a living model of risk in context. This alignment of risk to objectives is established in ISO 31000, and is what Tim Leech refers to as Objective-Centric Risk & Uncertainty Management.
- Operational Risk & Resilience Execution. Here, risk is managed through tasks, controls, issues, audits, and assurance processes down in the operations, processes, transactions, and interactions of the organization. When connected to objective-centric risk management, this work supports performance and compliance. But when isolated, it often devolves into a compliance exercise with limited strategic value. Digital twins provide the connective tissue that links operational controls back to objectives, strategies, and regulatory obligations — bringing tactical risk into alignment with broader goals. This is what Alex Sidorenko refers to RM1 (Risk Management v1).
Digital twins, uniquely, have the potential to integrate across all three layers — transforming how risk and compliance professionals understand, communicate, and act on uncertainty.
GRC Use Cases for Digital Twins
1. Strategic Risk Management & Scenario Analysis
Digital twins allow organizations to simulate the impact of strategic decisions, enabling leadership to ask “what if” in a structured, evidence-driven way.
- A global energy firm models different climate futures — rising sea levels, extreme heat waves, flooding — and assesses impacts on physical infrastructure and energy continuity in their strategy.
- A multinational manufacturer simulates a potential conflict in the South China Sea to assess disruptions in shipping lanes, supplier access, and contractual obligations.
Digital twins enable multi-scenario forecasting so leadership can evaluate strategies and make decisions — dual sourcing, inventory strategies, or regional shifts — before crises occur.
2. Objective-Centric Risk Analysis
At the objective level, digital twins allow risk professionals to model how various risks and controls influence specific business goals, performance, and outcomes.
- A pharmaceutical company models ESG objectives across facilities, aligning emissions data, regulatory requirements, and site-level performance in addition to compliance with mandates.
- A logistics company assesses how volatile fuel prices, labor unrest, and digital outages affect KPIs like on-time delivery and service quality.
This approach reveals how tradeoffs, decisions, and external events shape actual outcomes, turning abstract risk into decision intelligence.
3. Operational Risk & Control Testing
Digital twins offer an environment for continuous assurance and virtual control testing — reducing reliance on periodic audits.
- A financial institution simulates phishing, ransomware, or DDoS attacks across its IT stack, testing resilience and refining incident response procedures.
- A global retailer models transaction surges, fraud patterns, and internal controls across digital channels during peak seasons.
These controlled simulations reduce organizational exposure while improving preparedness and adaptive response capabilities.
4. Regulatory Change Management
Digital twins are ideally suited to understanding the impact of regulatory change across jurisdictions, functions, and systems.
- A bank uses a digital twin to simulate the impact of EU DORA on business units, policies, and training needs — and prioritize remediation accordingly.
- A technology company models global data privacy laws (e.g., PIPL, DPDP, CCPA) to determine how they affect data flows and vendor obligations.
With regulatory overlays integrated into the digital twin, compliance teams can visualize change impact, track dependencies, and operationalize compliance faster.
5. Third-Party Risk & Extended Enterprise Resilience
Digital twins map the extended enterprise — suppliers, outsourcers, partners — to simulate and manage risk in increasingly interdependent ecosystems.
- A consumer electronics firm models its semiconductor supply chain to predict the impact of shortages and logistic bottlenecks.
- A defense contractor uses war-gaming to identify chokepoints, sanction risk, and dual-use technology compliance exposures.
- A fashion brand integrates ESG signals, satellite imagery, and supplier data to assess due diligence under the regulations and global frameworks.
These digital environments enable proactive planning, procurement agility, and stronger third-party oversight.
A GRC Future That Is Simulated — But Starts with Seeing Clearly
The future of GRC isn’t just about simulation. The first step is visibility: seeing your risk, compliance, and governance architecture in one place. That’s what a digital twin delivers. For less mature organizations, this real-time, integrated view of the current state of GRC is where the immediate value lies.
From there, organizations can evolve to simulate disruptions, test controls, and model regulatory impact — supporting continuous improvement, adaptive governance, and purpose-driven risk management.
Yet despite the clear value, very few GRC platforms today support digital twins natively. Most are still static systems of record. Forward-looking organizations are building or integrating digital twin capabilities externally, or seeking next-generation platforms that bring this vision to life.
If you’re exploring this space and want to understand which vendors are leading, feel free to reach out. I cover the full spectrum of GRC technologies and architectures.
Digital twins represent more than a technological trend — they are a catalyst for transforming how organizations understand themselves and navigate a complex, fast-changing world.
Let’s continue the conversation. Whether your organization is exploring the basics of a digital twin for current-state visibility or seeking to enable advanced simulations for resilience and compliance, I’d be happy to share insights from the field..