The transition from traditional tiered support to a swarming model represents a significant shift in IT service management. Here I look at AC3's experiment in implementing a swarming support model using ServiceNow, analysing both the technical configuration and organisational outcomes.
Understanding Support Models
The Traditional Approach
The conventional tiered support model has long been the standard in IT service management. This hierarchical structure consists of four distinct levels:
Tier 0 provides self-service solutions, enabling users to resolve common issues through automation, such as password resets. Tier 1 serves as the frontline service desk, handling initial contact and basic troubleshooting. Tier 2 offers specialised support with advanced troubleshooting capabilities, while Tier 3 consists of subject matter experts who handle the most complex issues.
This model effectively funnels requests through a single point of contact and protects specialised resources. However, it often results in knowledge silos, delayed resolution times due to escalations, and limited opportunities for skill development among junior staff.
The Swarming Alternative
Swarming eliminates traditional tiers in favour of collaborative teams with diverse expertise. This approach aims to resolve issues more efficiently by bringing together experts from different domains, fostering knowledge sharing, and reducing handover delays.
AC3's Implementation
AC3 is a managed service provider for secure cloud solutions based in Australia and New Zealand.
Swarm Structure
AC3 implemented four distinct swarms:
The Priority swarm handled high-priority incidents, with team members shifting to support the Dispatch swarm during quieter periods. The Dispatch swarm managed incoming issues, while the Alert swarm focused on monitoring notifications. Complex or long-term issues moved to the backlog swarm for dedicated attention.
Technical Configuration
Built with ServiceNow
The implementation leveraged several key ServiceNow capabilities to reach our desired outcomes.
- Service Channels
- Automated assignment rules directed tasks to appropriate swarms based on priority, contact channel, and age
- Clear routing logic ensured consistent work distribution
- Flexible spillover mechanisms prevented bottlenecks
- Skills Management
- Comprehensive skill taxonomy and skill level development
- Staff-skill mapping with verifiable metrics to determine skill levels
- Task categorisation linked to required skills
- Regular skill assessment and updates incorporated into existing performance reviews
- Advanced Work Assignment
- Intelligent task distribution based on available skills
- Workload balancing across team members
- Optional agent assignment declination with automatic reassignment
- Cross-swarm overflow handling for peak periods
- Dashboards and Reports
- Visibility of long-term issues
- Highlight bottlenecks
- Measure and track KPIs
Operational Results
The implementation delivered several measurable improvements:
- Decreased response times across all priority levels
- Reduced mean time to resolution
- Enhanced collaboration between technical specialists
- Improved knowledge sharing across the organisation
However, challenges emerged in supporting multiple distinct customer environments, where deep client-specific knowledge proved crucial.
Key Learnings
Our experiment was successful due to a number of factors and provided insights for organisations looking to implement their own swarming model.
Success Factors
- Technology Configuration
- ServiceNow's flexibility supported the operational transformation
- Automated routing reduced administrative overhead
- Skill management became fundamental to team composition
- Process Development
- Clear work distribution rules proved essential
- Regular swarm composition reviews needed to maintain effectiveness
- Balance between automation and manual intervention optimised outcomes
- Cultural Adaptation
- Staff embraced collaborative problem-solving
- Cross-discipline interaction improved solution development
- Early and effective organisational change management brought everyone onboard
- Significant mindset shift supported the transformation
Implementation Recommendations
For organisations considering similar transitions:
- Skill Management
- Implement objective skill measurement criteria
- Use certifications or experience metrics for skill levels
- Maintain regular skill mapping updates
- Start with broad skill categories and refine as needed
- Work Assignment
- Phase in automation gradually
- Retain manual oversight for complex cases
- Build flexible workload distribution mechanisms
- Implement clear escalation paths
- Performance Monitoring
- Establish clear metrics for success
- Gather regular feedback from staff and customers
- Maintain flexibility to adjust the model based on results
Conclusion
While AC3 ultimately transitioned to customer-aligned support teams, our experiment with the swarming implementation provided valuable insights. The experience demonstrated that swarming models may be better suited to internal support organisations rather than multi-customer environments. However, the technological and process improvements developed during this implementation continue to benefit the organisation in its evolved form.
The key to success lies in maintaining flexibility and willingness to adapt based on operational feedback. Organisations considering similar transitions should focus on building robust skill management processes, implementing appropriate technology support, and fostering a collaborative culture while remaining mindful of their specific operational context.
