Process digital twin
A process digital twin is a virtual dynamic model that exactly reproduces the sequence, parameters and logic of a real business process for its analysis, optimization and prediction.
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What is a process digital twin
A process digital twin is a virtual dynamic model that exactly reproduces the sequence, parameters and logic of a real production or business process. Unlike a static BPMN diagram, a digital twin uses real data to simulate the system's behavior and predict results.
A process digital twin makes it possible to simulate the operation of the system, analyze bottlenecks and predict the result without interfering with real work. The technology is actively used in industry, logistics, banking and public administration.
According to Gartner, by 2026, 60% of large organizations will use digital twins to optimize processes, which will increase efficiency by 20-30%.
Main tasks of a process digital twin
The technology solves the following key tasks:
- What-if modeling — checking the impact of new inputs or schedule changes without risk to current work.
- Optimization — identifying redundant links, reducing execution time (cycle) and costs.
- Prediction — calculating future indicators based on accumulated statistics and real-time data.
- Staff training — safe practice of actions in a virtual environment.
Process digital twins are built using BPMN models and a Workflow Engine, integrate with BPMS and low-code platforms for automatic execution.
Stages of creating a process digital twin
The creation of a process model is based on the following stages:
- Data collection — integration with corporate systems, use of Process Mining for analysis of real event logs.
- Simulation modeling — building an algorithm of process steps in specialized software.
- Calibration and validation — configuring the model on real data and checking its accuracy.
- Analysis and implementation — running virtual scenarios to obtain the optimal work plan.
Digital twin technology requires an integrated approach. The design service will help determine goals and choose modeling tools.
Process digital twin and Process Mining
Process Mining is a key tool for creating digital twins. The technology automatically extracts process models from event logs of information systems, showing how processes are actually executed. Comparing the Process Mining model with an ideal BPMN model makes it possible to identify deviations, bottlenecks and inefficient operations.
Frequently asked questions
How is a process digital twin different from a BPMN model?
A BPMN model is a static graphic description of a process. A digital twin is a dynamic model that uses real data to simulate the behavior of a process. A digital twin can be executed on a Workflow Engine and predict results in real time.
Where are process digital twins used?
Process digital twins are used in industry, logistics, banking, public administration and in document workflow systems.
What tools are used to create process digital twins?
Simulation modeling tools (AnyLogic, Simio), Process Mining systems (Celonis), as well as BPMS and low-code platforms with simulation support are used.
How does a process digital twin help optimize business?
A digital twin allows testing changes without risk to current work. It shows how changes will affect execution time, staff load and financial indicators. A Workflow Engine is used to execute the model.
What is Process Mining and how is it related to digital twins?
Process Mining is a technology of automatic extraction of process models from event logs of information systems. These models are used to create digital twins that reflect the real state of processes.
What data is needed to create a process digital twin?
Event logs from information systems (ERP, CRM, BPM), data about operation execution time, resource load, operation cost, as well as input and output flow data are needed.
Can a process digital twin be used for staff training?
Yes, a process digital twin is ideal for staff training. Employees can practice actions in a virtual environment without risk to real work.
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