Logistics worker with smart robot arm using IOT and AI technology in logistics warehouse

AI-based failure prediction

Designing and deploying an AI-based real-time alerting system for a global logistics company

Real-time insights and early warning about system outages

For logistics providers, the availability of a well-organised system is essential for an efficient package delivery process. If the system is down, delivery will be delayed. This will negatively impact the customer relationship and the company-internal processes. The customer, a global logistics company, approached T-Systems to create a solution that would enable effective monitoring of critical interfaces to their customer-facing systems.

The challenges

  • Business impact: revenue decreases due to sudden outages in systems relevant for sales
  • High support costs: resource intensive processing of customer support enquiries
  • Negative customer experience caused by delayed communication of outages

The solution

  • Development and go-live of individual machine learning models for anomaly detection based on internal metrics from production systems, as well as external data
  • Design and deployment of a real-time alerting system notifying all relevant channels (customer support, incident response team) and systems in case of outages via e-mail, SMS, or Teams Webhook
  • The solution also mimics the strategies of the experts to perform root-cause analysis for incident detection

T-Systems designed and deployed an AI-based real-time alerting system notifying all relevant channels (customer support, incident response team) in case of outages

Dominik Zabel, T-Systems

Customer benefits

  • Rapid resolution of incidents and minimisation of downtime costs
  • Significant reduction in incoming customer support enquiries and costs in incident resolution
  • Increased end customer satisfaction

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Relevant solutions

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