Moving liquid hydrocarbons, like crude oil and biofuels, is a complex process. The sheer volume of these products, with approximately 540,000 railcars moving within the US in 2024 (Intra-U.S. Movements by Rail), creates a massive logistical challenge. Each railcar has a loaded volume, origin, destination, and numerous other characteristics that are crucial to track; however, manually tracking these details is time-consuming and prone to error.
This isn't just a simple tracking problem. It's a matter of operational efficiency and profitability. While some issues are common across all transportation methods, rail transport has its own unique set of challenges that can significantly impact a business. The key to solving this is to automate routine tasks and let human experts focus on the exceptions that truly require their attention.
The Top 6 Challenges in Rail Logistics
Organizations using rail as a key part of their logistics often face a series of problems that traditional methods can't solve. These issues prevent companies from having real-time visibility and control over their operations.
- Manual data entry: Information is often typed into multiple systems, creating opportunities for human error.
- Disparate data sources: The same transaction data might be found in different systems, leading to inconsistencies.
- Delayed or missing data: This directly impacts visibility and decision-making.
- Lost or misrouted railcars: Railcars can get flagged as “bad ordered,” meaning they are out of service for inspection or repair, which can cause significant delays.
- Fleet tracking difficulties: It’s challenging to track railcars when they move across different third-party systems.
- Railcar vetting: Ensuring railcars meet compliance standards and are suitable for transport requires meticulous checks.
Historically, companies have tried to solve these problems by either hiring more people or building complex, rigid IT systems. These solutions are slow, expensive, and lack the flexibility needed to adapt to new business rules or data formats.
A Modern, AI-Powered Approach to Logistics
Before deploying any technology, it's critical to start with a clear understanding of the business problem. A skilled business analyst can work with operations teams to uncover the root causes of inefficiency. Once a clear picture emerges, AI and automation can be deployed in a phased approach, integrating seamlessly with the existing railway depot operations.
Here's how a modern, AI-powered system transforms the logistics workflow:
1. Automated Transaction Flow
Instead of manual data entry, AI can train a model to read incoming data from emails, PDFs, and EDI feeds. This model ingests the information, formats it correctly, and exports it to your existing systems. It can also learn from master data, identify gaps, and even suggest new entries, which saves time for support teams.
This starts as a semi-automated process where AI prepares the files for human approval and can eventually evolve into a fully automated, “hands-off” workflow.
2. Intelligent Monitoring and Analysis
Once the data is flowing, AI tools move beyond basic tracking to provide real-time insights. They can:
- Flag anomalies in transit times or identify bottlenecks in the network.
- Identify missing or inconsistent data that needs human intervention.
- Track individual railcars over time to spot recurring issues, such as contamination or mechanical failures.
The goal isn't to replace human judgment. It's to highlight exceptions so that analysts can focus their expertise on the most critical issues, like negotiating with a carrier or a repair shop.
3. End-to-End Integration and Touchless Transactions
This approach can extend across the entire rail transport life cycle, including invoicing. By following the same principles and leveraging AI, companies can transition toward touchless transactions, where invoices are automatically generated and verified, reducing manual effort and improving accuracy.
The path from slow, error-prone manual data entry to real-time, accurate insights doesn't have to be a single, massive project. Organizations can leverage technology to automate workflows in a phased approach, ensuring they have the right technology, governance, and business analysis in place. The future of efficient rail logistics is not about throwing more people at the problem; it's about leveraging technology to automate workflows and transition to exception-based checking. This applies across the transaction lifecycle, starting with the gathering of initial data. For example, capturing rail fuel surcharge data without spending hours navigating numerous web pages. The keys are to ensure that the technology infrastructure and governance are in place, conduct the appropriate business analysis to capture processes and requirements, and assemble the pieces in a step-by-step approach.
The Future of Rail Transport for Energy Assets
The future of efficient rail logistics is not about throwing more people at the problem; it's about empowering them with the right technology. By adopting a modern, AI-powered approach, organizations can transition from reactive, manual processes to proactive, automated workflows. The keys to this transformation are to start with a clear business analysis, deploy technology in strategic and manageable steps, and utilize AI to automate routine tasks, ultimately allowing human experts to focus on what matters most. This shift promises to deliver not only greater operational efficiency but also a significant boost to a company's profitability and competitive advantage.
