Let’s look at how easy it is for a business analyst to design a robot that automates a typical document-heavy process like invoice processing. Previously, Jim the office guy manually opens emails and invoice attachments or downloaded invoices from web portals and then copied and pasted the information into SAP.
In this demo, we’ll watch as Allen the analyst designs and deploys a robot to automate this exact process with RPA and cognitive document automation which leverages intelligent OCR and machine learning to automate the processing of unstructured data.
First, Allen opens the design studio to build out the workflow. The robot will:
- log into Outlook
- open the email
- click on the link to the online vendor portal
- retrieve the invoice
- acknowledge receipt of the invoice on the vendor portal
- read the invoice
- send invoice data to SAP
- manage exceptions
Invoices come in many shapes, sizes and formats, but training the solution to read them is simple with embedded intelligent OCR that classifies documents and extracts information from them. You don’t even have to leave the design studio. Just open an invoice and define all the information you need to extract from a document sample. It’s easy-to-train documents right in the design studio, so this or any other robot knows where to look for key information on each invoice. Just point and click to fill in the required fields. Here machine learning works to find, read and understand the information and documents. When new vendors submit new invoice formats, the system can automatically identify and learn the new format. If an invoice layout changes, machine learning capabilities can learn the new format on the fly from user input. Our diligent robot sends a notice to the end-user who can point and click to select the information to extract with no system downtime and no need to retrain the system or get help from Alan, the analyst or IT.
Let’s a recap, Alan taught the robot how to read initial document samples right in the RPA design studio when building out the workflow. When something changes, Jim trains the robot on exceptions and the robot gets smarter and doesn’t need to bug Jim, because it knows what to do the next time. Everyone wins!
(1) Jim shifts from being a data gatherer to a data user, (2) Alan can design and deploy robots as seamlessly leveraged cognitive document automation with machine learning and intelligent OCR to process unstructured data. IT isn’t stuck fixing code on broken robots every time there’s an exception. And (3) Jim’s boss can monitor robot and human productivity and drive continuous improvement with robotic process intelligence. With the power of RPA and cognitive document automation in a single easy-to-use design environment, you can reduce data processing costs and accelerate workflows to improve operations and customer experience.
