Customer Case Study: Global Logistics Provider Transforms Operations with the Informat Platform

Logistics and transportation organizations operate in an environment of razor-thin margins, operational complexity, and rising customer expectations for real-time visibility and fast, reliable delivery. This case study examines how a global mid-size logistics provider — referred to here as "Atlas Logistics Group" (ALG) — used the Informat low-code platform to transform its operations, unifying customer-facing and internal processes across 40 countries while reducing costs and improving service quality.

ALG operates freight forwarding, warehousing, and last-mile delivery services across North America, Europe, and Asia-Pacific, with approximately 3,500 employees, 120 facilities, and annual revenue of $950 million. The company had grown through acquisition, and its operations reflected that history: 15 different operational systems across regions, inconsistent processes, limited visibility across the supply chain, and a customer experience that varied dramatically depending on which region and which legacy system was handling the shipment. Customer inquiries about shipment status consumed 40% of customer service capacity — not because customers were demanding but because information was fragmented across systems and often outdated by the time it was assembled into a response. The IT team of 45 was fully consumed maintaining legacy systems and managing integrations between them, with no capacity for innovation.

The Solution: Unified Operations Platform on Informat

ALG selected the Informat platform to build a unified operations layer on top of its fragmented legacy systems. Rather than attempting to replace the 15 regional operational systems — a multi-year, high-risk program — ALG used Informat to create standardized processes, unified customer experiences, and real-time visibility that spanned the legacy systems. The approach was phased over 18 months, with each phase delivering measurable value.

Phase 1 — Shipment Visibility and Customer Portal (10 weeks): The first phase built a unified shipment visibility platform using Informat. The application aggregated shipment data from all 15 legacy systems, normalized it into a standard data model, and presented real-time tracking, milestone updates, and exception alerts to customers through a self-service portal and to ALG staff through operational dashboards. AI-powered ETA prediction provided more accurate delivery estimates than carrier-provided ETAs by learning from historical performance patterns. The impact was immediate: customer service inquiry volume dropped 45% as customers found answers in the portal; customer satisfaction improved 22 points on ALG's tracking metric; and operations staff gained, for the first time, a unified view of all shipments across all regions and carriers.

Phase 2 — Operational Workflow Automation (14 weeks): Building on the unified data foundation, the second phase automated key operational workflows: exception management (when a shipment was delayed, damaged, or misrouted, the system automatically created a case, notified the customer, assigned resolution tasks to the appropriate staff, and tracked resolution through completion); customs clearance (automated document checking, regulatory validation, and broker assignment); and invoicing and billing (automated generation of accurate, timely invoices from shipment data, reducing billing errors and disputes). Exception resolution time decreased 60%, customs clearance cycle time decreased 35%, and billing disputes decreased 50%. The operations team, initially skeptical of workflow automation, became strong advocates as they experienced the reduction in administrative work and increase in time available for value-adding activities like carrier negotiation and customer relationship management.

Phase 3 — AI-Powered Operations Intelligence (12 weeks): The third phase applied AI to operational optimization: route and mode optimization (AI analyzing shipment characteristics, carrier performance, cost, and transit time to recommend optimal routing and mode selection for each shipment); predictive exception detection (AI identifying shipments likely to experience delays before they occurred, based on patterns in historical data, enabling proactive intervention); and capacity forecasting (predicting warehouse and transportation capacity needs to optimize resource allocation). Route optimization reduced transportation costs by 8% while maintaining or improving transit times. Predictive exception detection reduced actual exceptions by 25% through proactive intervention. And capacity optimization improved warehouse utilization by 15% and reduced premium transportation spend by 30%.

Metric	Before Informat	After Informat	Improvement
Customer Service Inquiry Volume	Baseline	-45%	Self-service portal deflection
Customer Satisfaction	Baseline	+22 points	Significant improvement
Exception Resolution Time	Baseline	-60%	Automated workflow management
Transportation Costs	Baseline	-8%	AI route optimization
Billing Disputes	Baseline	-50%	Automated accurate invoicing
Warehouse Utilization	Baseline	+15%	AI capacity forecasting

Conclusion

Atlas Logistics Group's transformation with the Informat platform demonstrates that meaningful operational transformation is achievable even for organizations with complex, fragmented legacy system landscapes. By building a unified operations layer on top of existing systems rather than attempting to replace them, ALG achieved dramatic improvements in customer experience, operational efficiency, and cost performance while avoiding the risk and disruption of core system replacement. The phased approach delivered measurable value at each step, building organizational confidence and momentum. Two years into its transformation, ALG has not just better software — it has a fundamentally more agile, data-driven, and customer-centric operating model that positions it to compete effectively in an industry where digital capability increasingly determines competitive success.