CxO Briefing: IT Service Management (ITSM)
48% Reduction in MTTR via AI BPMN Transformation
IT Incident Resolution Process
How to cut average resolution time?
The Dragon1 AI BPMN Process Architect optimized critical IT incident processes, cutting average resolution time from 90 minutes to 47 minutes, minimizing business downtime and financial loss.
1. Current State (As-Is) - Triage Delay
90 Minutes MTTR | High T1 Escalation
2. Future State (To-Be) - AI Optimized
47 Minutes MTTR | Automated Root Cause
Immediate Payback Justification
85% Modeling Efficiency: The Cost of Doing Nothing
85%
Reduction in time to create and document complex BPMN models.
€45K/Hour
Estimated financial loss saved per critical incident resolved 43 minutes faster.
47 Min
New average MTTR, drastically improving service reliability and SLA compliance.
The Enterprise Result: Transformation Metrics
48%
Reduction in Mean Time to Resolve (MTTR).
Directly minimizes business disruption and improves operational stability.
65%
Reduction in Incorrect Escalations.
AI automatically routes incidents to the correct T2/T3 team based on root cause analysis.
Proactive
AI-Driven Prioritization of Critical Incidents.
The BPMN model integrated with CMDB data allows AI to prioritize based on true business impact, not just severity level.
Detailed Process Comparison: Before and After AI
1. Current State (As-Is): The 90-Minute Struggle
The previous incident process was sequential and heavily relied on manual Tier 1 triage, leading to misrouting and delayed escalation, resulting in an average MTTR of 90 minutes.
| Initial Triage and Classification | Manual review of tickets by Tier 1 staff; high rate of incorrect classification and assignment to the wrong team. | 15-30 minutes wasted on re-triage and re-assignment. |
2. Future State (To-Be): The 47-Minute AI Optimized Blueprint
The Dragon1 AI BPMN Process Architect generated the Future State model, embedding AI to automate triage, knowledge integration, and parallel diagnostic steps, achieving an MTTR of 47 minutes(a 48% reduction).
| AI Root Cause Identification | AI automatically cross-references incident description with knowledge base and recent changes (CMDB) to identify likely root cause and responsible team. | Eliminated T1 triage time and ensured direct assignment to the correct team. |