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ROBOTIC PROCESS AUTOMATION

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Robotic & Process Automation 

Robotic process automation (RPA), also known as software robotics, uses intelligent automation technologies to perform repetitive office tasks of human workers.
Robotic process automation (RPA), also known as software robotics, uses automation technologies to mimic back-office tasks of human workers, such as extracting data, filling in forms, moving files, et cetera. It combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. By deploying scripts which emulate human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems.

PROCESS IDENTIFICATION

In this step, we review proposed processes for automation and add qualified processes to backlog. We identify data needed for matrix and assign data collection

SCORING AND PRIORITIZATION

In this step, we score and prioritize processes leveraging matrix data and kick off preliminary process flow design discussions.

AUTOMATION DESIGN

In this step, we Draft RPA automated functional design for selected sub-process, Identify opportunities to optimize before automation (time-boxed) and Discuss automation progression/increments for end-to-end processes.

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RPA and intelligent automation

In order for RPA tools in the marketplace to remain competitive, they will need to move beyond task automation and expand their offerings to include intelligent automation (IA). This type of automation expands on RPA functionality by incorporating sub-disciplines of artificial intelligence, like machine learning, natural language processing, and computer vision.

Intelligent process automation demands more than the simple rule-based systems of RPA. You can think of RPA as “doing” tasks, while AI and ML encompass more of the “thinking” and “learning,” respectively. It trains algorithms using data so that the software can perform tasks in a quicker, more efficient way. As artificial intelligence becomes more commonplace within RPA tools, it will become increasingly difficult to differentiate between these two categories.

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RPA and artificial intelligence

Robotic process automation is often mistaken for artificial intelligence (AI), but the two are distinctly different. AI combines cognitive automation, machine learning (ML), natural language processing (NLP), reasoning, hypothesis generation and analysis.

The critical difference is that RPA is process-driven, whereas AI is data-driven. RPA bots can only follow the processes defined by an end user, while AI bots use machine learning to recognize patterns in data, in particular unstructured data, and learn over time. Put differently, AI is intended to simulate human intelligence, while RPA is solely for replicating human-directed tasks. While the use of artificial intelligence and RPA tools minimize the need for human intervention, the way in which they automate processes is different.

That said, RPA and AI also complement each other well. AI can help RPA automate tasks more fully and handle more complex use cases. RPA also enables AI insights to be actioned on more quickly instead of waiting on manual implementations.

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RPA and hyperautomation

Hyperautomation is the concept of automating everything in an organization that can be automated. Organizations that adopt hyperautomation aim to streamline processes, and they leverage technologies such, as artificial intelligence (AI) and robotic process automation (RPA), to operate certain workflows without human intervention.

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