A case study on how RPA integration in intermodal logistics eliminates manual data entry, accelerating quote times and boosting sales conversion rates.
Intermodal transport lies at the heart of global supply chains, driven by cost optimization and sustainability goals. However, managing combinations of road, rail, and sea transport introduces significant operational complexity. One of the biggest operational bottlenecks logistics sales directors face is the manual consolidation of freight rates, port, terminal, and customs tariffs across different transport modes. The industry average for responding to spot or contract requests for quotation (RFQs) from customers ranges between 24 and 48 hours. Especially in dynamic market conditions, this delay directly translates into lost sales and reduced customer satisfaction on financial balance sheets.
Another risk stemming from manual processes is data entry errors. Manually transferring price lists in various formats (PDF, Excel, email) from shipping lines, rail operators, and local hauliers into Excel spreadsheets leads to margin errors in quotes and operational losses. With sales teams spending 40% of their time on data collection and manual calculations, resources for customer relationship management and new market development are severely restricted.
To eliminate these operational inefficiencies, a Robotic Process Automation (RPA) integration was implemented at an international intermodal logistics provider. In this project, software robots (bots) were deployed to mimic the repetitive, rule-based tasks performed by human operators. The workflow was structured as follows: the moment an incoming intermodal transport request reaches the system, RPA bots simultaneously access designated supplier portals, rail tariffs, and shipowner systems.
Throughout this technological transformation, Logistivo played a key role as a strategic technology partner, making multimodal integrations seamless, preventing data flow interruptions, and improving decision quality. The flexibility of the infrastructure ensured seamless communication with the systems of different transport operators via APIs or web scraping methods.
The changes in Key Performance Indicators (KPIs) achieved in this case study clearly demonstrate the operational leverage of technology:
In today's logistics industry, where speed and price transparency are critical, running operations with traditional methods is unsustainable. Companies that fail to integrate RPA and process automation into their business models are bound to lose market share due to high operational costs and slow response times. Organizations that can respond to customer requests in minutes rather than hours, establish error-free operations, and direct human resources to value-added tasks stand out in the competition. Digital transformation in intermodal transport is no longer an operational choice, but a strategic necessity to maintain market presence and sustain profitable growth.
No, it is not required. RPA bots work by using the interfaces of existing software just like a human; this allows integration without making fundamental code changes to your existing ERP, CRM, or legacy systems.
RPA uses AI-powered OCR (Optical Character Recognition) technology to recognize, extract, and automatically save data from unstructured PDF, email, or Excel documents into standardized databases.
It frees sales teams from operational burdens such as manual data entry, price collection, and preparing quotes in Excel. This allows teams to focus their time directly on customer relationships, strategic pricing, and new sales opportunities.
RPA bots connect to the web portals of shipowners and rail operators at defined intervals or via triggers to pull the most up-to-date spot rates in real time and transfer them to the quote calculation module.
Depending on the complexity of the processes, RPA projects implemented in logistics typically deliver a return on investment (ROI) in as little as 6 to 9 months, boosting operational profitability.