Progression of Automation
Updated: Dec 17, 2021
A Brief Review of Robotic Process Automation, Business Process Automation, Intelligent Automation and Hyperautomation
As the need for automation becomes more widespread across industries, it is important to understand the distinctions between various types of automation available today. From robotic process automation (RPA) and business process automation (BPA) to intelligent automation (IA) and hyperautomation, we’ll define what they are and how each is evolved from the previous one.
Automation in a Nutshell - RPA, BPA, IA and Hyperautomation
Progressive technologies have enabled automation to evolve from automating simple and repetitive tasks to advanced and cognitive automation of complex workflows and end-to-end business processes. Such progression is as follows:
It starts with conventional RPA that automates repetitive tasks and workflows.
By adding business process automation technologies, the automation can be expanded to deliver both workflow and end-to-end business process automation (RPA/BPA).
Utilizing Artificial Intelligence (AI) to analyze complex and unstructured data and events, cognitive decisions can be made during the automation, evolving from rules-based RPA/BPA to intelligent automation.
Finally, integrating IA with analytics and decision-making engines will offer hyperautomation.
Hyperautomation platforms are then used to develop and deploy a variety of IA solutions for a broad range of functions within an enterprise.
Robotic Process Automation (RPA)
Automating Mundane and Repetitive Tasks
Repetitive tasks that follow certain predefined workflows such as invoice processing and data entry can be automated using RPA. Users can utilize RPA’s design tool to create the workflow. The work that should be done in each step of a workflow (such as entering data in a certain fashion) can be defined by users without writing software codes and only by using predefined functions. When completed, one or more “bots” are activated to run multiple workflows simultaneously. Thus, significant productivity is achieved by computers running multiple bots instead of live employees. The resulting work is consistent and free from human errors. Furthermore, bots can deliver additional benefits such as operating 24/7 with no break, reducing payroll expenses, and managing variable workloads through real time up-down scalability.
Conventional RPA uses rules for the evaluation of structured data used in a workflow and when certain decisions should be made by applying rules to such structured data. Later in this article we will see how RPA can be more intelligent and carry out cognitive automation.
Workflow of an RPA can interact with humans (Attended RPA) or run entirely with no human intervention (Unattended RPA) as described below.
Attended RPA (With Human Intervention)
Certain processes cannot be entirely automated without human intervention, therefore, attended RPA can be used to automate more complex segments of a process and interact with humans at certain points of a process that requires intervention. Attended RPA augments the productivity of employees by reducing the transaction time and eliminating errors. Attended RPA usually runs on employee desktops.
Unattended RPA (Without Human Intervention)
Unattended RPA can automate end-to-end processes and workflows that do not require human intervention or engagement. The workflow can be created by a process manager and activated based on a schedule or the occurrence of an event. It typically runs on a server and in the background, independent of human involvement.
Business Process Automation (BPA)
Automating End-to-End Business Processes and Multiple Tasks
Whereas RPA automates repetitive workflows and delivers automation for a single task, BPA automates a series of tasks that form an end-to-end business process. In other words, BPA can use multiple RPAs to automate an entire business process. For example, an accounts payable end-to-end business process typically consists of invoice processing, payment scheduling and payment disbursement through various methods of payment. RPA can be used to automate each of these 3 steps followed by a BPA to integrate the 3 RPAs and deliver an end-to-end business process. Generally speaking, RPA delivers automation at a micro-level using low-code platforms, while BPA can automate at a macro-level using no-code platforms.
Integrating RPA and BPA offers a unique approach to automation as it systematically extends and expands the automation to a broad range of micro-level and macro-level tasks and processes.
Low-Code Automation Platform Vs. No-Code
A major objective of RPA and BPA is to empower users to rapidly develop automation applications without designing and writing software codes. To that end, RPA vendors offer application design tools as described below.
Low-Code Platform offers a design tool equipped with a library of prepackaged and readily usable software modules (usually called services and microservices) and a scripting module. Users can design automation applications by creating a script-driven flow of services and provide parameters required for each service to run. Though this does not require writing software codes, it does need scripting of services to be created by users. Low-code platforms are often used at a micro-level automation and in detailed workflows and tasks that are a subset of an end-to-end process. Non-software engineers can be trained to use the tool and rapidly develop automation applications.
No-Code Platform provides users with an intuitive drag-and-drop tool with which they can develop end-to-end business process automation applications by dragging and dropping icons that each may represent a series of functionalities (or RPAs). All complex software required to build an application are already created by software engineers and are made available to users in an easy drag-and-drop, no-coding-needed fashion. No-code platforms can empower employees to design complex business process automation without software coding or scripting.
No-Code Platforms Give Rise to Citizen Developers and Democratize Software Engineering
No-code platforms have created a vision for future employees based on a strategy to democratize software engineering. They empower non-engineer employees, or citizen developers, to use their knowledge of conducting their own tasks to create workflows that can digitize and automate their processes in order to significantly increase their own productivity without depending on IT. Thus, citizen developers without formal training in software development and software engineering can develop software using no-code platforms.
Making Automation Smart and Cognitive
The next step in the evolution of automation is to add AI and offer Cognitive Automation. AI technologies, such as Natural Language Processing and Natural Language Understanding (NLP/NLU), Machine Learning (ML) and Deep Learning (DL) enable RPA/BPA automation to process complex tasks and processes that require AI to analyze unstructured data and events and determine the next steps.
The Ultimate Intelligent Automation
The ultimate intelligent automation is achieved by adding multichannel analytics and smart decision-making engines to AI-driven RPA/BPA. Such a platform, offered as a Platform-as-a-Service (PaaS), is then used to develop complex and sophisticated IA solutions.
Hyperautomation harnesses the power of RPA and BPA, AI, analytics and decision-making engines to drive more sophisticated automation with intelligent decision making similar to human intelligence for workflows and end-to-end business processes. It enables the automation to continuously monitor and analyze the data and events during the execution of the workflow and processes to make intelligent decisions and select the next best steps in the workflow or even correct the deficiencies of the workflows. Used in Enterprise Content Management (ECM) and compliance, hyperautomation can identify the intent within content and categorize, classify and distribute it similar to the functioning of the human brain.
The diagram below depicts a hyperautomation platform with integrated RPA, BPA, AI, analytics and decision-making engines capable of cognitive and analytics-driven automation for both workflows and end-to-end business processes.
Making Automation Affordable, Available and Applicable for Companies of All Sizes
Any one or a combination of the above-mentioned automation technologies empowers companies to realize significant improvement and operate more efficiently across the enterprise as they embrace Digital Transformation.
Historically, the use of AI technologies and AI-driven intelligent automation solutions by enterprises required significant investment and qualified resources, hence, they were not affordable by all enterprises or for all applications. The affordability and customization of RPA had often been a major barrier to adaptation by companies across the globe.
Successful deployment of intelligent automation solutions and full recognition of their Return-on-Investment (ROI) often requires special programs beyond the technologies and products. Democratizing AI and intelligent solutions for enterprises of all sizes means vendors must offer scalable automation at highly affordable prices with on-premise software or SaaS delivery options, flexibility in customization, consultations and proofs-of-concept; as well as post-sale operational assistance to assure the solution works for customers’ specific needs.