Digital Transformation Last updated November 5, 2026
What Is a Digital Twin? A Definition, Types, and Uses
See how digital twins work, from physical assets to business processes.
What Is a Digital Twin? Definition, Types, and Business Applications
A digital twin is a virtual representation of a real-world asset, system, or process connected to data about how it behaves. The term covers different approaches: an asset twin may use CAD models and IoT sensor data, while a process twin uses event logs to represent how work moves through cases, activities, and resources. If you want to understand operational workflows rather than physical equipment, a process twin can help you examine the current flow and explore what-if scenarios with simulation.
What Is the Digital Twin Definition?
A digital twin is a virtual representation of something real, connected to data about its behavior. That definition applies to physical assets, connected systems, and business processes, but each type uses different data and answers different questions.
An asset twin might represent a machine or production line using engineering models and equipment data. A process twin represents how work moves through activities, teams, and systems, using event data recorded as work happens.
The connection to real-world data distinguishes a digital twin from a static diagram. Data may update continuously or at intervals. The update cycle depends on the use case and the data available.
The distinction matters when you choose a method. Asset twins often rely on engineering models, sensors, and equipment telemetry. Process twins use event logs: records of activities, timestamps, and cases that show how work actually happened. Both can support analysis and simulation, but a process twin does not require a physical asset model or IoT sensors.
How Did Digital Twins Develop?
The idea of using physical replicas and simulations to prepare for space missions dates back at least to NASA’s Apollo 13 work in 1970. In 2002, Dr. Michael Grieves described a framework connecting a physical product with its virtual counterpart across the product lifecycle. NASA engineer John Vickers coined the term “digital twin” in 2010.
How Does a Digital Twin Work?
A digital twin connects a representation of something real to data about its behavior, so you can analyze what is happening and explore possible changes.
The details vary by use case, but the basic steps are similar:
- Collect relevant data. For an asset twin, this may include sensor readings, equipment telemetry, and engineering data. For a process twin, it may include event logs from ERP, CRM, or workflow systems.
- Create a representation. Model the asset, system, or process at a level of detail that fits the question you want to answer. A process representation can include activities, decision points, resources, and timing.
- Connect the representation to data. Use updates from the real-world source to keep the model relevant. Updates may be continuous or periodic.
- Analyze behavior. Compare expected and observed performance, investigate variations, or use simulation to explore possible outcomes.
- Use the findings to inform decisions. A twin can help you assess a change before you make it. It does not make the operational change for you.
For a process twin, event data provides evidence of what happened. Process mining reconstructs the actual flow from that data. You can then use a process model and simulation to examine possible changes, such as adjusting capacity or changing a routing rule.
What Are the Types of Digital Twins?
Digital twins can represent a component, an asset, a connected system, a business process, or an organization. The right type depends on the scope of the question you need to answer.
| Type | What it represents | Typical data |
|---|---|---|
| Asset twin | A physical asset, such as a machine, vehicle, or building | CAD or engineering data, IoT sensors, and equipment telemetry |
| System twin | Connected assets or components, such as a production line or utility network | Data from the assets and systems that make up the larger system |
| Process twin | How work moves through a business process, such as order-to-cash or procurement | Event logs with case identifiers, activities, timestamps, and resource information |
| Organization twin | How an organization operates across processes, resources, and relationships | A combination of process and organizational information |
A component twin focuses on an individual element, such as a valve or machine component. It may form part of a larger asset or system twin. These categories can overlap: a production line may include asset twins for individual machines and a system twin for the line as a whole.
If your question is about how people, systems, and work interact, a process twin is the relevant type. It uses process data rather than a detailed physical model.
What Is a Digital Twin of an Organization?
A digital twin of an organization (DTO) widens the same idea from one process to the whole organization: its processes, resources, structures, and the relationships between them. That is a different scope with a different starting point, so this page stays with the process twin and hands the organizational view over. Read the guide to the digital twin of an organization for the levels you climb, what keeps it live, and which process to model first.
For many companies, a digital twin is the ultimate goal. The mistake is trying to get there in one step. First document your processes and connect them into a full architecture. Then add data so you can measure them. Finally, make that view continuous and live.
How Does Digital Twin Technology Apply to Business Processes?
A process twin uses event data to represent how work actually moves through business activities and systems.
Business processes generate digital records as work moves through systems. An event log can capture a case identifier, an activity, a timestamp, and sometimes information about the resource or system involved. Process mining uses these records to reconstruct how the process actually ran.
A process twin can show the paths cases took, how long activities and handoffs took, and where cases were delayed or repeated. Unlike a diagram created from interviews alone, it starts with observed event data. A process model adds structure and context, while simulation lets you explore scenarios.
This is different from an asset twin. A process twin does not model the physical condition of a machine or require sensor data. It represents how work moves through business activities and systems.
Why Do Business Process Digital Twins Matter?
A process twin helps you investigate operational questions using evidence from your own process.
- See the actual flow. Compare the paths in event data with the process you expect to see.
- Find delays and rework. Identify where cases wait, repeat activities, or take different routes.
- Explore possible changes. Use simulation to assess scenarios such as changing capacity or routing.
- Track process performance. Use KPIs and updated data to see how the process changes over time.
A twin does not guarantee that a proposed change will work in practice. It gives you a structured way to examine the data and test assumptions before deciding what to do.
How Do You Build a Digital Twin of Your Process?
You can start a process twin with event data from systems you already use; you do not need IoT sensors to analyze a business process. The seven steps below build the twin for one process; growing it into an organization-wide twin is a different order to climb, covered in the digital twin of an organization guide.
- Choose one process. Start with a process that matters to your team and has usable event data. Examples include order-to-cash, procurement, or customer support.
- Prepare the event log. Look for a case identifier, activity name, and timestamp. Depending on your question, resource names, costs, or other attributes may also help. See our guide to creating a process mining event log.
- Discover the actual flow. Use process mining to reconstruct the paths cases took and examine timing, variation, and rework.
- Model the process. Use a process model to make the flow easier to interpret and represent the structure you want to analyze. BPMN can help you describe activities, gateways, and decision points.
- Set up a scenario. Define a specific what-if question, such as what may happen if you change capacity or adjust a process rule. Keep your assumptions clear.
- Run a simulation and review the results. Compare the scenario with the current process using measures such as cycle time, throughput, or waiting time, where your data and model support them.
- Decide what to test in practice. Use the results as input to a decision. After a change, review new process data to understand what happened.
ProcessMind combines process mining, process mapping, dashboards, KPIs, and process simulation. You can try ProcessMind with your process data.
What Capabilities Should You Look For in a Platform?
For a process twin, look for capabilities that connect event data to an understandable process view and help you assess possible changes.
| Capability | What it helps you do |
|---|---|
| Process mining | Reconstruct the actual flow from event data |
| Process mapping and BPMN | Document process structure and make the flow easier to discuss |
| Process simulation | Explore what-if scenarios using a model and its assumptions |
| Dashboards and KPIs | Track process performance and communicate findings |
| Data preparation | Organize event data from your business systems for analysis |
| Collaboration | Share process views and findings with the people involved |
When you evaluate a tool, check that its capabilities match your data and the questions you need to answer. A process analysis tool does not replace engineering software for building detailed asset twins.
You can see how what-if analysis works or explore process simulation.
What Are Real-World Applications of Digital Twins?
Digital twins are used across industries, but the model and data differ depending on whether you are studying physical assets, connected systems, or business processes.
Manufacturing
An asset or system twin can represent equipment or a production line. Teams can use engineering and equipment data to examine performance or simulate possible changes to a line.
A process twin answers a different question: how work orders, inspections, or production cases move through the organization’s processes. These views can complement each other, but they are not the same model.
Supply Chain and Logistics
A system twin may represent connected facilities, transport, or inventory flows. A process twin can show how orders, procurement, or fulfillment cases move through business systems and teams.
Event data can help you identify delays and variations in those workflows.
Healthcare
A process twin can help you analyze administrative and operational flows, such as patient intake, scheduling, or billing. It can show where cases wait or take different paths.
Patient-specific clinical twins are a separate application and may require different data, models, and safeguards.
Cities and Utilities
City and utility asset or system twins can represent infrastructure and networks using engineering data and sensor readings. Process twins can complement these views by showing how related operational work, such as service requests or maintenance cases, moves through teams and systems.
Energy
Energy organizations may use asset twins to represent equipment such as turbines and system twins to examine connected infrastructure. When event data is available, process mining can provide a separate view of business processes such as maintenance planning or service operations.
Digital Twin vs. Simulation: What’s the Difference?
A digital twin connects a representation to data about something real; simulation runs a model to explore possible outcomes.
A simulation can compare scenarios, such as different staffing levels or process rules. You can run a model without connecting it to current operational data.
A digital twin is a virtual representation connected to data about a real-world asset, system, or process. It may include simulation, but simulation on its own is not a digital twin.
For a process twin, event data helps describe the actual flow. A process model represents its structure, and simulation can help you compare possible changes. Results depend on the model, input data, and assumptions you provide. They are scenario estimates, not a guarantee of what will happen.
If you want to assess a process change, read how to run what-if analysis.
Where Does ProcessMind Fit In?
ProcessMind helps you analyze and improve business processes; it does not build asset twins from CAD models or IoT sensor data.
You can use ProcessMind to examine event data, map process flows, track KPIs, identify bottlenecks, and simulate what-if scenarios. The process twin workflow brings those capabilities together:
- Discover how work actually flows from event data.
- Map the process so your team can understand and discuss it.
- Analyze process performance with dashboards and KPIs.
- Simulate possible changes and compare scenarios.
Start with one process and the event data you already have. To see what the simulation capability covers, explore process simulation.
Build a digital twin of one process
Start with event data from a process you know. Use it to see how work flows today, then explore a change with simulation.
For the next step, see how what-if analysis works, or explore process simulation.
