Integrating Your Order Document Processing: A Guide to Best Practices
To ensure a smooth and efficient flow of information from your order documents into your Transport Management System (TMS), it's crucial to choose the right integration method. This guide outlines the two primary methods for submitting documents for data extraction—Direct File Upload and Dedicated Email Inbox—to help you select the best fit for your operational needs.
Method 1: Direct File Upload (Drag & Drop)#
This method involves a user manually uploading document files directly into the system's web interface.How It Works#
A user logs into the platform, navigates to the upload section, and either drags and drops files from their computer or uses a file browser to select one or more order documents (e.g., PDF, PNG, JPG). The system then processes these specific files immediately.Pros & Cons#
✅ Direct Control: You have precise control over exactly which documents are processed and when. It's ideal for single, high-priority orders that need immediate attention.
✅ Instant Feedback: The user is present during the upload and receives immediate confirmation or error messages, allowing for quick corrections.
❌ Manual & Repetitive: This process requires manual effort for every batch of documents. It interrupts workflow and consumes valuable employee time.
❌ Doesn't Scale: As order volume grows, this method becomes a significant bottleneck, increasing the risk of human error (e.g., forgetting to upload an order, uploading duplicates).
Best Practices#
Use the file upload functionality for urgent, one-off orders that need to be processed outside of the standard automated workflow.
It's an excellent tool for initial testing and setup to verify that the data extraction is working correctly with specific document types.
Reserve this method for exceptions, not for your daily, high-volume processing.
Method 2: Dedicated Email Inbox#
This method uses a specific, monitored email address to receive and automatically process order documents.How It Works#
You are create a dedicated email address (e.g., orders@company.eu). Your team, partners, or customers send their transport orders as attachments to this email address. Our system automatically monitors this inbox, extracts the attachments from new emails, processes them to convert them into data, and sends the structured data to your TMS. The entire process is touchless.Pros & Cons#
✅ Fully Automated: This is a "set it and forget it" solution. Orders are processed 24/7 as they arrive with no human intervention required.
✅ Effortless & Scalable: This method seamlessly handles any volume of orders without creating a bottleneck. It's perfect for growing businesses.
✅ Easy for Everyone: Sending an email is a universal and familiar process. This requires almost no change in workflow for your clients or internal teams. They simply send orders to a different email address.
Best Practices#
Communicate Clearly: Inform all relevant parties about the process. Specify that only order documents should be sent to this address to ensure smooth processing.
Define a Fallback: Establish a clear internal process for handling any processing errors or for documents that are complex and require manual review.
Our Recommendation: Email Integration for Superior Efficiency#
While both methods are effective, we strongly recommend the Dedicated Email Inbox for the vast majority of use cases.The manual drag-and-drop method creates an operational bottleneck and relies on repetitive manual work, which is inefficient and prone to error. In contrast, the email integration automates the entire inbound document pipeline. It saves dozens of hours of manual work, eliminates the risk of forgotten uploads, and allows your team to focus on more critical, value-adding activities than data entry. It is the most robust, scalable, and efficient solution for modern logistics operations. 🚚Master Data Management: Overcoming Key Integration Challenges#
A successful integration depends on the quality of your master data within your Transport Management System (TMS). When our system extracts data like customer names and addresses from an order document, it needs to match them accurately against the records in your TMS.This guide outlines the most common data-matching challenges and provides a framework for handling them effectively.1. Customer Matching#
The goal is to reliably link the customer found on an incoming order document to the correct customer account in your TMS.The Challenge#
Customer names on documents are often inconsistent, they not always have vat codes. You may receive orders with variations, abbreviations that don't exactly match your TMS records.Variation Example: An order from "ABC Logistics" needs to be matched to the customer record "ABC Logistics, Inc." in your TMS.
Missing Data: The document might lack a unique identifier like a customer ID or VAT number.
Recommended Approach#
For optimal accuracy, the system's customer matching logic should be configured to follow a prioritized, step-by-step process:1.
Search by VAT ID (Primary Method): The system should first check for a VAT/Tax ID on the processed document.If a VAT ID is present, it should be used to query the TMS for an exact match.
In cases where a single VAT ID is associated with multiple customer branches, the system must then use the postal code from the document's address as an additional filter to pinpoint the correct branch.
2.
Search by Location and Name (Secondary Method): If a VAT ID is not available, the system should proceed with a location-based search.It should first filter the entire customer database by matching the country code and postal code from the document.
On this reduced set of potential customers, the system should then perform a fuzzy search on the customer name. A similarity threshold of 70-80% is recommended. A customer record that meets this threshold is considered the likely match.
3.
Flag Uncertain Matches for Review: To ensure data integrity, any match that is not 100% certain (e.g., a match made via the secondary fuzzy name search) should be flagged for user attention. It is recommended that the system's interface visually highlights these matches—for instance, by using a yellow or orange color—to clearly indicate to the user that a manual verification is advised before finalizing the order.
2. Location (Address) Matching#
Accurate location matching is critical for planning, routing, and execution. The loading and unloading addresses on the order must be correctly identified from your TMS database of locations.The Challenge#
Addresses on documents can be unstructured, incomplete, or formatted differently from the data in your TMS.Formatting Example: "123 Rue" vs "123 Route"
Ambiguity: A large company may have multiple docks or warehouses at the same address, requiring a more specific location code.
Typos: Misspellings in street names or city names are common.
Wrong information Sometimes postal codes or house number can mismatch slightly with real address for instance the last postal code number is different.
Not full address Sometimes address is not full only provided partial data like FR00 Trua
Recommended Approach#
To achieve the highest matching accuracy, your system’s location matching logic should be implemented using a prioritized, multi-layered strategy that leverages the high-quality data provided by our service.1. Primary Method: Coordinate-Based Radius Search (Most Accurate) 🌍#
Your system should first check if latitude and longitude coordinates are provided in the processed data. Since our service geocodes addresses whenever possible, this will often be the case.If coordinates are available, the most effective search method is to query your TMS for all known locations within a small radius (e.g., 100 meters) of the provided point.
To further validate the match and ensure precision, this geospatial search can be combined with a check on the postal code and house number. This is the most reliable way to pinpoint an exact location.
2. Secondary Method: Normalized Address Component Search#
If coordinates are not available, your system should fall back to matching based on address components.Utilize Normalized Data: It is critical to use the normalized fields (e.g., normalized_street, normalized_postal_code) we provide for all matching attempts. This data is cleaned of non-Latin characters and standardized, which is essential for accurately matching addresses from countries like Germany (DE) or Poland (PL).
Filtering: First, narrow down the search by filtering all TMS locations by the normalized country and postal code.
Fuzzy Street Matching: On this filtered list of potential locations, perform a fuzzy match on the normalized street name to account for common variations (e.g., "Street" vs. "St.", "Route" vs. "Rue").
3. Handling New Locations: Automated Creation#
If a location cannot be found in your TMS using the methods above, but our service has successfully extracted a complete and valid address, we recommend that your system automatically creates a new location record. This ensures your TMS master data stays current and minimizes the need for manual intervention for new, valid sites.4. Handling not full address#
In case the address is not full we will return the data which is available like country code FR, postal code not full only region 00 and city name Trua. Users usually update the full adress after loading base on CMR data.
Modified at 2025-09-25 07:42:39
