Project led by Bruno Jiménez, now an Akaen partner.
Delivery speed is the key metric in logistics and e-commerce. To deliver packages on time, internal operations must run smoothly. This case describes how one of Germany’s largest e-commerce and transport groups replaced overloaded manual incident triage with an intelligent classification system capable of processing 19,500 tickets a month accurately and autonomously.
Executive summary
About the customer
A leading German e-commerce and transport group with thousands of employees and 24/7 operations. Its Service Desk is the company’s central nervous system: any delay in incident resolution directly affects the delivery chain and end-customer experience.
The Challenge: a Service Desk saturated by volume and fragmentation
With approximately 19,500 monthly tickets arriving through multiple channels (email, web forms, direct entries in Jira), the team of agents dedicated much of their day to reading, interpreting and redirecting incidents to the correct queue. Manual classification caused incorrect assignments, increasing the TTR (Time-to-Resolution) and generating a cascade effect on service SLAs.
The team had the skills, but its time was consumed by triage that required speed and consistency rather than expert judgement.
The Solution: Intelligent Triage Architecture
An End-to-End automation solution was implemented that acts as a traffic controller for the company's incidents. The system operates in three phases:
Automated Processes (3 key phases)
Incidents scattered across email, forms and Jira, without a standard format.
Automatic centralisation: capture, standardisation and preparation for immediate processing in Jira.
Manual triage consumed hours every day and led to incorrect assignments.
A hybrid engine (AI + rules) interprets context and routes incidents to the right specialist with 90% accuracy.
Recurrent incidents saturating the queues of specialists.
Automatic scripts for known patterns: 1,800 tickets/month closed with no human intervention.
Operational comparison
- • Manual triage of each ticket.
- • Frequent incorrect classifications.
- • High TTR caused by reassignment.
- • Agents dedicated to reading and interpreting.
- • Automatic AI classification with 90% accuracy.
- • Direct assignment to the right specialist.
- • 1,800 tickets/month resolved automatically.
- • Agents focused on complex incidents.
The Impact
The transformation of the Service Desk turned an operating bottleneck into a scalable and predictable system:
- Capacity freed up: 2 FTEs reassigned from triage to management and continuous improvement tasks.
- Economic efficiency: over €120,000 in estimated annual operating cost savings, based on the German market.
- Quality of service: reduction of TTR by elimination of erroneous reassignments.
- Scalability: the system absorbs volume increases without expanding the team.
Operational results
- Stronger SLA performance: consistent resolution times, even during volume peaks.
- Zero-Touch real: Almost 10% of tickets are resolved without human intervention.
- 24/7 operations: the system classifies and resolves incidents outside working hours.
Conclusion
“Hyperautomation is a practical tool today, not a future promise. An intelligent Service Desk resolves tickets, frees talent and protects SLAs.”
Would you like to transform incident management in your organisation? .