CxO Briefing: Business Process Management (BPM) & Strategy
50% Reduction in Process Discovery Cycle Time via AI BPMN Transformation
Business Process Discovery and Design
The Dragon1 AI BPMN Process Architect leverages process mining to map 'As-Is' processes and automatically generates optimized 'To-Be' Agentic models based on strategic goals, validating changes before implementation.
1. Current State (As-Is) - Manual Discovery and Modeling
6 Weeks Discovery Cycle | Subjective Modeling
2. Future State (To-Be) - AI Optimized Agentic Design
3 Weeks Discovery Cycle | Data-Validated Models
Immediate Payback Justification
85% Modeling Efficiency: The Cost of Doing Nothing
85%
Reduction in time to create and document complex BPMN models.
€25K
Average consulting cost saved per process mapping engagement.
100%
Accuracy in 'As-Is' process mapping directly from system event logs.
The Enterprise Result: Transformation Metrics
50%
Reduction in Process Discovery Cycle Time.
Accelerates strategic initiatives by providing validated process blueprints faster.
90%
Faster Model Validation and Simulation.
AI simulates 'To-Be' models against real data, predicting operational performance before rollout.
Zero Waste
Elimination of Tribal Knowledge Bias.
Process models are derived from objective data (process mining), not subjective interviews.
Detailed Process Comparison: Before and After AI
1. Current State (As-Is): The 6-Week Manual Effort
Process discovery relied heavily on manual workshops, interviews, and documentation review, leading to slow, inconsistent results and models based on how people think the process works, not how it actually runs.
| Manual Process Mapping | Business analysts spend weeks conducting interviews and translating subjective descriptions into BPMN models. | High modeling cost, inaccuracy, and a 6-week minimum cycle time. |
2. Future State (To-Be): The 3-Week AI Optimized Blueprint
Process mining automatically extracts event logs to generate the 'As-Is' model. The Dragon1 AI BPMN Process Architect then optimizes this model, generates 'To-Be' variants, and simulates them for best performance, resulting in a 50% faster cycle time.
| Agentic Model Generation | AI automatically generates multiple optimized 'To-Be' process models (BPMN) based on observed data bottlenecks and predefined strategic goals. | Halved the discovery and design cycle time (from 6 weeks to 3 weeks) with empirically validated designs. |