Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨ Join us at New York University for the AI Pitch Competition · April 2, 2026 · Apply Now ✨
EFI Logo
Contact Us
Back to Resources
Case StudyOil & Gas Extraction & Processing
Offshore Oil & Gas Facility

Integrating Real-Time Alerts with Automated Ticketing

An offshore oil & gas facility integrated Innvendt's real-time electrical monitoring alerts directly into ServiceNow, creating an automated maintenance response loop that eliminated manual alert triage and reduced MTTR by 45%.

4 min readOctober 5, 2024
Primary Impact
45%
Reduction in MTTR
< 5 minutes
Alert-to-Ticket Time
Down from 2-4 hour manual triage—for automatically classified alerts
45% reduction
MTTR
Mean time to repair reduced 45% through faster alert response and better-quality ticket context
70% reduction
Operator Workload
Alert triage workload reduced 70%; operators focus on high-priority reviews and exception handling
4.6/5.0
Ticket Quality Score
Technician-rated ticket completeness score, up from 2.8/5.0 with manual ticket creation

The Challenge

The facility's electrical monitoring system generated hundreds of alerts per week across substations, earth grids, and electrical distribution equipment. Alert triage was manual: a central monitoring room operator reviewed each alert, assessed its significance, and manually created a ServiceNow incident ticket for alerts requiring field response. This triage process introduced 2-4 hours of delay between alert generation and ticket creation, during which developing fault conditions could worsen. The manual process also produced inconsistent ticket quality—critical information from the alert record was frequently omitted from tickets, requiring field technicians to call back for context before they could begin work.

The Solution

Innvendt's ServiceNow integration connector was deployed to automate the alert-to-ticket workflow. Alert classification logic (configured to the facility's operational policies) automatically assesses incoming alerts and creates ServiceNow incidents with pre-populated priority, assignment group, and detailed context from the alert record and sensor history. Human operators review and approve ticket creation for high-priority incidents; routine alerts generate tickets automatically without operator involvement.

Implementation

Alert Classification Policy Configuration

Alert classification rules were configured in the Innvendt platform based on a workshop with the facility's maintenance engineering and operations teams. Rules evaluated alert parameters (sensor type, threshold exceedance magnitude, trend rate, location criticality) to assign each alert to one of four response categories: automated ticket (no human approval), operator-reviewed ticket, monitoring only (no ticket), or emergency notification (immediate call to on-call engineer). The policy was validated against three months of historical alerts before go-live.

ServiceNow Ticket Template Design

ServiceNow ticket templates were designed to include all information a field technician needs to begin work without additional research: sensor location (with GIS map link), alert type and threshold exceedance details, 7-day sensor trend chart, similar historical incidents at the same location, and the maintenance procedure recommended for the detected condition. Technicians who previously called the control room for context before travelling to the asset now had all required information on their mobile device before departure.

Feedback Loop and Continuous Improvement

A feedback mechanism allowed field technicians to update the alert record with their field findings upon completing the maintenance action: what they found, what they did, and whether the sensor readings returned to normal within the expected timeframe. This feedback was used quarterly to refine the alert classification rules—identifying alert types where automated ticket creation generated unnecessary dispatches and alert types where monitoring-only classification missed genuine faults requiring intervention.