Welcome to the final blog in our six-part series that takes you on a journey through the latest concepts in multichannel document capture and intelligent OCR. We’re focused on how AI has transformed what’s possible in making your documents and data work for you—and not against you.
In part one, we looked at how RPA marked a revolution in empowering businesses to solve problems associated with manual, data-centric tasks, yet was historically ineffective in automating document processing. In part two, we examined the emergence of cognitive document automation (CDA), which does the “head work” of understanding what the document or email is about, what information it contains and what to do with it. Part three of our series took a deeper dive into what you should look for in a CDA solution. (Hint: You’ll need much more than just OCR functionality). Part four tackled the question: How do we measure the success of CDA? And part five examined some of the challenges RPA customers face when implementing CDA solutions and trying to maximize user productivity.
Read More: Cognitive Document Automation: How Do We Measure Success? (Part 4)
For part six in our series, we’ll look beyond RPA and CDA and identify the essential components for transforming business areas and operations end-to-end—at scale.
Beyond RPA and Cognitive Document Automation: Intelligent Automation at Scale
For a business to achieve full Digital Transformation, more is required than just an individual technology solution, like Cognitive Document Automation or RPA, or even a combination of the two. RPA and CDA are essential components, of course, especially when you consider that 62 percent of all business processes rely on documents and records. For example, if a business wants to include a PDF or document as part of an RPA process they’re automating, they need the ability to perform document capture and transformation. But we can’t stop there.
Consider the following scenario: let’s say that thanks to your RPA and CDA deployment, you’re able to process more documents and electronic data faster, accelerate business processes, and improve information visibility—even when originating from multiple channels and formats. You’ve cut the time necessary to configure and maintain document and electronic data capture projects via Machine Learning and visual, no-coding robotic process design. And you’ve reduced the manual labor required for document classification, separation, and data entry. You’ve even cut repetitive data collection, entry, aggregation, migration and integration tasks.
But what about streamlining operations or improving interactions with customers, during onboarding, and throughout their journey? Monitoring overall system performance? Improving communication across mobile and other channels? Or gaining valuable insights to make better decisions and reduce risk?
Automating end-to-end business operations is where the true ROI of Digital Transformation lies—and by that, we mean everything from RPA, content capture and data injection, to process orchestration, to advanced analytics that help inform better business decisions.
Vendors that provide only standalone technology solutions leave their customers to struggle—now or later on—to integrate a set of disparate technologies that can’t “talk” to each other. What organization wants to be forced to procure multiple solutions from multiple vendors and support a complex (not to mention timely and costly) implementation to achieve their goals?
A highly integrated, open intelligent automation platform is the ideal scenario because it automates operations in a way that scales to the needs of the business—no partnerships, multi-vendor product integrations or overhead required. This platform-centric approach delivers rules-based and AI-powered interoperable technologies essential for automating end-to-end business operations: Cognitive Capture, RPA, Process Orchestration, Mobility and Engagement and Advanced Analytics.
The best part is there’s no need to rip and replace existing technologies (if you already have an RPA solution in place, for instance) because you can integrate new capabilities and build on your current investment. This helps eliminate some of the pain while delivering on the promise of Digital Transformation—helping increase competitiveness, accelerate time to value, and lower total cost of ownership.