Logistics companies, freight, shipping, air etc. have long tried to digitize and automate document processing. This is not surprising for an industry that has high volumes, frequent transactions, and lots of paperwork for tracking and execution of orders. The potential ROI of automating document heavy processes is clear and yet many logistics companies, despite frequent attempts, have failed to automate many of their processes involving documents. Even for tech-forward logistics firms with strong RPA implementations, a robust process improvement focus and automation “Centers of Excellence” (COE), many processes involving documents have remained elusive to generate a sufficient ROI or have outright failed when automated. Why?
Top Reasons Logistics Companies Struggle to Automate Document Heavy Processes
- Variability in Documents
- Unknown Requirements Up-Front
With Traditional RPA/OCR:
Variability: Logistics companies and freight brokerages receive a wide variety of documents from an even larger number of vendors. Traditional automation solutions use OCR templates or models to try and extract the necessary information from Bills of Lading, invoices, freight payments etc. and upload them into a system of record. These approaches require lots of time to train or set up, and are inflexible. When documents are received with unexpected fields/ tables or are damaged, OCR without local logic throws exceptions. The process breaks and is now “Brittle” requiring lots of services and eliminating the hopeful ROI.
With the exception handling available to traditional RPA, developers in an automation COE or IT, must either route the exception to a subject matter expert, ask how the finance or accounting professional would handle the situation and/or create a new template for future reference. In a recent conversation with a large logistics company, an automation COE leader recently told us, “The business user keeps asking, ‘Why do we have to keep having these meetings? I thought we fixed this already?’”. Because of the constant maintenance work required to keep these processes running, and the time-suck it has on business units, processes with lots of different document types fail to meet ROI thresholds and remain stubbornly manual. Wouldn’t it be easier if logic could just be added on top of the OCR or automation for future exceptions?
Unknown Requirements Up Front: In traditional approaches to RPA, the first step is to map out a process and try to identify all of the possible variations which may occur. Typically led by outsourced consultants, this takes time and money to identify as many variations as possible in the hope that processes don’t break. Not only is this time consuming, costly and inefficient, but often if asked, the business users can’t tell the development team all of the variations. They are stored in a user’s memory, but are hard to articulate until it is needed. When requirements aren’t mapped up front, processes break frequently, causing frustration and requiring expensive maintenance services. Because of this, most automation teams steer clear of processes with unknown requirements, leaving a huge portion of documents un-automated and frustratingly manual.
But when you train a new employee how to conduct a process manually, you don’t spend the time and money to train them on all potential edge cases on their first day. Instead, you train them on how a process should occur, and then enable their intuition and problem solving to learn and handle the rest as new documents are encountered. Automation should work the same way…and now it does.
The New Approach:
Kognitos built a new approach to automate document processing from end to end 10X faster and over 5X cheaper than traditional RPA or OCR tools. How? By approaching a process the same way a human would. If a front-line team member in the AP department of a freight broker received a BOL from a new vendor, in a totally new format, they would still be able to understand it based on past experience, and extract the needed information. If they didn’t understand it, they would walk over to their manager’s desk and receive instruction on how to proceed. After receiving instruction, that employee would jot it down on a sticky note, or remember the logic needed to handle that document type in the future.
With Kognitos, we have made handling exceptions and adding local logic on top of OCR/automation as simple as having a conversation. When Kognitos encounters an exception, it creates a question or request (in English) for the business user. The business user simply needs to respond in English with basic instructions like “For invoices from this vendor, the supplier number is always under the document ID”. Kognitos’s brain processes this logic (just like a person), remembers it and applies it anytime the situation is encountered again. Processes don’t break, they just pause, wait for instruction and then continue.
Value of Conversational Exception Handling:
- Automation COEs don’t need to code in exceptions, they can be handled by the business user.
- Expensive “Maintenance” contracts are no longer needed and the money saved can be spent on core business instead.
- Implementations of processes are far faster as only the “Happy Path” is needed.
- Even highly variable processes with lots of document types and vendors can have strong cost savings, error reduction and ROI calculations when automated.
The key is to have an automation tool that automates the same way humans approach documents and that tool is Kognitos.
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