Our team is debating whether to implement full workflow automation for incident routing or maintain our current manual routing process with some automation assistance. We’re trying to optimize incident response times while ensuring incidents reach the right subject matter experts.
With automation rule reliability, we’ve seen some incidents get stuck in routing loops when the automated logic can’t determine the appropriate owner based on incident category and severity. Manual routing control gives us flexibility to handle edge cases, but it’s slower and depends on the availability of our incident coordinators. We’re also considering hybrid workflow options that combine automated initial triage with manual escalation paths.
What has worked better in your organizations? Are there specific incident types that benefit more from automation versus manual oversight? I’d appreciate hearing about real-world experiences with different routing strategies in VVQ 23R3.
Our hybrid approach uses automation for initial assignment based on clear criteria (location, product line, incident type) but requires manual confirmation before final routing to investigators. This adds about 30 minutes to response time but reduces misrouted incidents by 80%. The key is having well-defined automation rules that know their limits and escalate to human decision-makers when confidence is low. We track a ‘routing confidence score’ that determines whether automation proceeds or requests manual review.
After implementing incident routing systems across multiple organizations, here’s what I’ve learned about balancing automation and manual control:
Automation Rule Reliability: Full automation works best when you have well-defined incident categories with clear ownership mappings. Start by analyzing your last 6-12 months of incident data to identify patterns. Calculate what percentage of incidents fall into categories that could be reliably automated versus those requiring human judgment. In my experience, about 60-75% of incidents fit clear patterns suitable for automation. The key is building rules that are specific enough to be accurate but not so rigid they fail on minor variations. Implement fallback logic that routes uncertain cases to a triage queue rather than making a wrong assignment.
Manual Routing Control: Don’t eliminate manual routing entirely - instead, position it strategically. Manual control is essential for: 1) High-complexity incidents involving multiple departments, 2) Incidents with unclear or incomplete information, 3) Situations where automated routing fails confidence thresholds, and 4) New incident types not yet covered by automation rules. Train your coordinators to recognize patterns that should be converted into automation rules, creating a feedback loop that continuously improves your automated routing.
Hybrid Workflow Options: The most effective approach combines the speed of automation with the judgment of manual oversight. Implement a tiered system: Tier 1 (60-70% of incidents) - Full automation with direct assignment based on clear criteria, no manual review needed. Tier 2 (20-30% of incidents) - Automated suggestion with required manual confirmation before final routing. Tier 3 (5-10% of incidents) - Manual routing from the start for complex or sensitive cases. Use incident metadata to automatically determine which tier applies.
For optimal response times, configure your automation to route incidents within 5 minutes of creation for Tier 1, within 30 minutes for Tier 2 (allowing time for coordinator review), and assign Tier 3 incidents immediately to your senior incident coordinator. Monitor routing accuracy metrics weekly and adjust automation rules based on manual override patterns. This hybrid approach typically achieves 85-90% routing accuracy with average response times 40% faster than pure manual routing.
The routing confidence score is an interesting concept. How do you calculate it? Is it based on matching criteria or historical routing patterns? I’m concerned that adding manual checkpoints might slow down our response times, especially for time-sensitive safety incidents that need immediate attention.
Consider implementing smart automation that learns from manual routing corrections. When a coordinator manually reassigns an incident that automation routed incorrectly, capture that as a training example. Over time, your automation rules become more accurate. We’ve reduced manual intervention from 30% to under 10% of incidents using this approach. The system now handles most routine cases automatically while still allowing human override for complex situations.
For time-sensitive incidents, you should have separate fast-track automation rules that bypass manual review entirely. We use severity level and incident category combinations to trigger immediate automated routing for critical safety events. For example, any incident marked ‘Critical’ with category ‘Patient Safety’ goes directly to our safety team lead with simultaneous notifications to quality director and regulatory affairs. No manual intervention needed. Lower severity incidents can afford the manual review step without impacting response times significantly.
We went full automation two years ago and it was a mistake for complex incidents. Simple, routine incidents route perfectly - equipment failures, documentation errors, etc. But anything requiring cross-functional input or judgment calls ends up bouncing between queues. We’ve since moved to a hybrid model where automation handles the first 70% of incidents and manual routing kicks in for anything flagged as complex or high-priority.