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Perspectives | Case Study

Intelligent Automation Transforms Document Processing for a Logistics Major

Read | Oct 01, 2024

Download Case Study

AUTHOR(s)

A WNS Perspective

Key Points

Amid the increasing complexity of global logistics and evolving post-Brexit regulations, a leading UK-based logistics provider sought to optimize its document management processes. Handling large volumes and unpredictable spikes of import / export documents, the company aimed to streamline labor-intensive processes, minimize errors and improve operational efficiency.

Intelligent Document Processing for Logistics: Deploying AI and ML Platforms

Logistics Document Automation

The logistics provider partnered with WNS to implement its Artificial Intelligence (AI) and Machine Learning (ML) powered platform, WNS Malkom.

Hyperautomation in Logistics

This end-to-end shipping automation solution seamlessly digitized document workflows and delivered:

AI-powered Logistics Operations

%
Reduction in TAT

Automated data extraction and validation accelerated document processing.

>%
Data Auto-captured

AI-driven automation captured the majority of fields without human intervention.

>%
Accuracy

Combined AI and human effort ensured high accuracy.

%
Cost Reduction

Streamlined document processing led to lower operational costs.

Logistics Process Automation Solutions: Driving Efficiency and Cost Reduction

Read the entire case study to discover how intelligent automation transformed document processing for this logistics provider.

FAQs

1. How can AI-powered document processing improve efficiency in shipping and logistics?

AI-powered document processing can automate data extraction, classification, and validation across shipping and customs documents. This helps reduce manual handling, accelerate turnaround times, and improve operational consistency. WNS (Part of Capgemini) leverages WNS Malkom to help logistics organizations digitize document-intensive workflows and scale operations more efficiently.

2. How can logistics companies manage increasing document volumes without increasing manual workloads?

Logistics companies can use intelligent document processing, automated data capture, business-rule validation, and exception-based workflows to handle fluctuating import/export volumes. A scalable automation model helps teams process more documents while allowing employees to focus on complex cases and higher-value activities.

3. How can organizations improve data extraction accuracy while automating logistics documents?

Organizations can combine AI-driven extraction with data validation, standardized business rules, and human review for exceptions. This approach helps identify inconsistencies, improve data quality, and support reliable downstream processing. WNS combines intelligent automation with logistics domain expertise to help organizations balance processing speed with accuracy and control.

4. How can logistics leaders integrate intelligent document processing with existing systems?

Leaders should assess document formats, current workflows, backend applications, data standards, and integration requirements before implementation. APIs, configurable connectors, and workflow automation can connect document processing with existing logistics systems while supporting security, auditability, and business continuity.

5. How can decision-makers measure the ROI of logistics document automation?

Decision-makers should track average handling time, cost per document, data extraction accuracy, automation rates, manual interventions, and processing capacity. Establishing baseline metrics and monitoring results after implementation helps quantify operational value and guide further investment. WNS (Part of Capgemini) combines AI, analytics, and process expertise to help logistics organizations pursue measurable efficiency improvements.