Any business or industry deals with a combination of business processes and tasks. Some tasks are completely structured/predictable, some less structured yet predictable, and some completely unstructured and unpredictable. The predictable and structured processes with well-defined tasks can be managed in logical steps, scripted, and programmed with some efforts and due diligence. These types of processes can be managed using a variety of traditional approaches such as Business Process Management.
On the other hand, managing unpredictable & unstructured processes requires on-the-fly thinking, applying the right business acumen, and making a quick decision to achieve the desired outcome. This is where Robotic Process Automation (RPA) could be a key solution element for handling the nuances of Dynamic Case Management.
Managing dynamic work is difficult, and therefore businesses across the globe have been experimenting with different techniques and approaches over time. For instance, consider the scenarios where work involves
As you would notice, a lot of this work is dynamic in nature – unpredictable in terms of what you find in the next step of the current process or the next iteration of the same process. Historically, a lot of systems have tried to address this problem, however, the core challenge of variability across software systems, dynamism in terms of data, processes, and stakeholders continue to remain challenges. The need of the hour thus would be to have a solution that doesn’t need a tight integration across systems and can bring not only deterministic but also cognitive capabilities to the fore. The proposed solution should not expect the underlying systems to be changed or tweaked or integrated traditionally as that might render the solution ineffective in managing the ever-changing scenarios.
The inherent capability of RPA to use front end automation in addition to the API-based or other backend integrations makes it a core contender in the race to solve the case management conundrum. RPA plays a pivotal role in achieving the rule-based ‘Deterministic Automation’ as well as the cognitive capability led ‘Intelligent Automation’ and enables ‘Human-empowered Automation’.
Deterministic automation in RPA is the proven art and science of using front-end UI automation through software programs called Robots. The robots can handle all variety of use cases spanning one or multiple software systems, management of data from varied sources, etc. much like a human user. This allows the human user to focus on high-value tasks and lead to better efficiency in case management. Additionally, RPA platforms like AssistEdge can provide tool-based “Process Discovery” allowing organizations to unearth their processes and variations better by removing human bias and providing data-based intelligence on process tasks.
In addition to the above-mentioned, Intelligent Automation in RPA allows handling cognitive use cases like image processing and unstructured data with the help of Automation Intelligence or Machine Learning techniques. RPA platforms like AssistEdge provide the flexibility to use industry-leading cognitive services for handling complex business processes. The tool allows drag and drop-based orchestration to stitch need-based invocation of AI and ML capabilities and use the provided intelligence to drive Robot actions.
Let’s consider the most basic document management scenario. Businesses have large amounts of unstructured data in the form of documents such as handwritten scanned papers, images, contracts, enrolment forms, email correspondence as well as data in various software systems such as invoices, purchase orders, sales orders, etc. Dynamic Case Management would need the ability to understand the data and then based on the insights from this data interact with software systems to complete the business processes. RPA tools leverage Optical Character Recognition (OCR) for reading through scanned documents and convert them into meaningful data. Further to this, Computer Vision (CV) and Natural Language Processing (NLP) techniques are also used to generate summaries, locate contextual information, derive business insights, and more. RPA tools allow human users to review and approve the generated insights and recommended actions. Once done the Robots can formally update the case details into various target systems through front-end automation.
Dynamic Case Management through RPA is a great example of a human-machine partnership in which process handling is enhanced through Artificial Intelligence-driven decision-making and automation, providing greater precision. RPA platforms like AssistEdge thus help organizations handle dynamic cases and provide:
RPA (deterministic and intelligent) can be a potent approach to today’s dynamic and complex case management needs. They can help an organization in identifying automation opportunities and implement them in a manner that doesn’t impact any of their current assets. Additionally, this solution lends itself to a very agile change management process.
AssistEdge provides a cohesive automation platform through its products like AssistEdge RPA, AssistEdge Engage, and AssistEdge Discover.
AssistEdge RPA offers a platform for automating various processes, bringing about sweeping changes across an enterprise. It provides the capabilities to build and execute both “Unattended” and “Attended” Intelligent Automation. Powered by Albie, the cognitive engine, AssistEdge RPA 18.0 empowers enterprises to embark on the journey towards Automation Singularity.
AssistEdge Engage helps organizations in reimagining their contact centers and achieving superior customer experience. Customers benefit from faster query resolution, reduced hold time, increased first call resolution, and suitable offers, thereby improving brand connect and loyalty.
AssistEdge Discover is a leading process discovery product that captures and leverages user’s digital interactions to create business process maps and transformational insights that aid organizations in process improvement, automation, and efficiency. Powered by empirical data, the outcomes are free from human biases providing a powerful foundation for operational excellence and continuous improvement.