How would your leadership decisions change if you could run your organisation in parallel, test scenarios, see impacts, and fix problems before they materialise? That’s the promise of a digital twin of an organisation (DTO): a governed, living model of processes, people, systems, and data that lets organisations simulate change, measure outcomes, and accelerate value delivery. DTO offers a practical path to faster, safer, and more confident transformation for organisations focused on enterprise performance transformation.
This article explores the benefits of having a digital twin of an organisation. A DTO enables enterprises to simulate, predict, and optimise performance across functions. It also highlights how DTO-powered business agility and an AI-driven digital twin strategy together empower organisations to make faster, data-backed decisions and drive continuous transformation.
rethink DTO as your organisation’s strategic nervous system
Most organisations treat analytics and process maps as disconnected tools. A DTO connects them, linking org charts, workflows, and systems to real-time data on work volumes and risks. The result is a live model with a unified view that reveals how value truly flows across the business. With this clarity, leaders can pinpoint bottlenecks, fix root causes, and predict the impact of every change before it happens.
the top business benefits of a DTO: practical, measurable, immediate
When scoped and governed correctly, the digital twin of organisations provides tangible benefits:
- Faster, safer decision-making. Simulate proposed changes (reorganisations, process redesigns, system upgrades) to quantify outcomes before committing resources.
- Operational resilience and risk reduction. Run “what-if” scenarios to see regulatory, supply or staffing risk impacts and prepare mitigation steps.
- Improved change adoption and onboarding. DTOs help teams visualise new ways of working, reducing training time and resistance.
Quantitative studies and vendor experience show DTOs delivering quicker time-to-value for transformation programmes and measurable reductions in operational waste when paired with disciplined governance. These benefits mark a clear shift from one-time change initiatives to an ongoing, adaptive performance system.
from insight to execution: enterprise performance transformation with DTO
A DTO moves an organisation from isolated improvement projects to continuous performance transformation. Instead of disparate metrics and one-off pilots, the DTO becomes the ground truth for strategy-to-execution alignment: translating strategic targets into process changes, resource plans, and real-time performance dashboards.
This reduces gaps between intent and outcome and shortens the feedback loop for continuous improvement. Academic and practitioner research shows DTOs enhance agility by making enterprise models testable and actionable.
As transformation becomes continuous, the next frontier emerges: using DTOs to enable business agility at scale.
DTO-powered business agility: simulate, reallocate, recover
Business agility is the ability to reallocate resources and change processes with confidence. DTO-powered business agility enables planners to:
- Reallocate capacity
- Validate contingency plans
- Coordinate cross-functional changes based on real-time data
By connecting the DTO to operational systems and IoT inputs, simulations mirror actual conditions, ensuring decisions reflect current realities, not assumptions. This convergence forms the foundation of an enterprise metaverse, an intelligent, multi-model environment for dynamic decision-making where AI further enhances foresight and accelerates responsive transformation.
designing an AI-driven digital twin strategy
AI takes the DTO beyond description, turning it into a predictive engine. By layering machine learning and analytics, organisations can detect patterns, forecast outcomes, and act before issues arise. In practice, AI-driven DTOs improve simulation speed by up to 50% and forecast accuracy by over 25%. To make it work, you need:
- Reliable master data as your single source of truth
- Real-time inputs from systems, sensors, and transactions
- Transparent AI models that explain recommendations
- A feedback loop that learns and refines over time
This approach transforms decision-making from reactive to predictive, empowering leaders with confidence-backed, evidence-based action. With strategy and intelligence aligned, the final step is execution, translating vision into a scalable roadmap.
practical roadmap: how organisations should start, and scale
The best way to start is small and scale alowly but confidently. A staged approach helps reduce risk and show ROI early:
- Start with a high-value area: Choose one domain, such as customer onboarding or factory operations, and build your first baseline model.
- Strengthen your data foundation: Clean, reliable data fuels every simulation.
- Experiment before you commit: Test a few “what-if” scenarios, measure outcomes, then scale what works.
- Govern for trust: Assign clear ownership and track model changes to ensure reliability.
- Keep it evolving: Compare simulated results to real outcomes and refine continuously.
how can Infosys BPM accelerate your AI-driven digital twin strategy?
As enterprises aim to become more predictive, responsive, and efficient, building a DTO can be a catalyst for enterprise performance transformation. Infosys BPM helps organisations bring this vision to life, combining process expertise, AI-driven insights, and governance to turn real-time data into measurable performance gains.
Frequently Asked Questions
Q1. How is a digital twin of an organisation (DTO) different from traditional enterprise architecture or process modelling?
A DTO extends static models by combining structural views (processes, capabilities, org units, systems) with live operational data, so it reflects how the organisation actually behaves in real time. Rather than just documenting the landscape, it enables simulation of alternative designs and operating scenarios and compares “as‑is” and “to‑be” states in a continuous improvement loop.
Q2. What are the most tangible business benefits enterprises typically realise from a DTO?
Enterprises report better visibility of value flows, faster impact assessment of change initiatives, and improved resource and asset utilisation when DTOs are used to test scenarios before implementation. DTOs also support risk reduction and resilience by allowing organisations to explore regulatory, operational, or demand shocks virtually and design mitigations in advance.
Q3. What are the critical data and governance prerequisites for building a trustworthy DTO?
A robust DTO requires a reliable baseline of master data on processes, systems, and organisational structures, plus access to high-quality event and performance data from operational systems. Clear governance covering model ownership, change control, and validation of simulation assumptions is essential to avoid the twin drifting away from reality or becoming an untrusted “model on the side.”
Q4. How does AI enhance the value of a DTO beyond visualisation and reporting?
AI techniques such as machine learning and process mining can automatically discover process variants, detect patterns, and generate predictions on throughput, bottlenecks, and risk under different scenarios. Studies and practitioner reports show that combining DTOs with AI improves simulation speed and forecast accuracy, making the twin a practical decision-support engine rather than just a descriptive model.
Q5. What is a practical, low-risk way for large organisations to start with DTOs and then scale?
Most guidance recommends starting with a single high-value value stream (for example, purchase-to-pay or customer onboarding), capturing the as‑is operating model, and running a few targeted “what‑if” simulations to prove value. Once benefits and learning are established, organisations can extend the DTO across more processes and business units, supported by iterative cycles of modelling, testing, implementing, and measuring outcomes.
