Software robotics, sometimes referred to as robotic process automation (RPA), uses automation technology to simulate back-office functions performed by human employees, such as extracting data, filling out forms, moving files, etc.
What is Robotic Process Automation (RPA)?
To integrate and carry out repetitive operations between enterprise and productivity applications, it mixes APIs and user interface (UI) interactions.
RPA technologies carry out the autonomous execution of a variety of tasks and transactions across unrelated software systems by deploying scripts that mimic human operations.
By performing business process activities at a large volume using rule-based software, this type of automation frees up human resources to focus on more difficult jobs.
RPA gives CIOs and other decision-makers the ability to quicken the process of their staff’s digital transformation and increase their return on investment (ROI).
What is robotic process automation (RPA)? What types of repetitive jobs is it capable of handling?
It is a primer for IT and business professionals as well as anyone else who needs to debunk the idea.
Robotic process automation (RPA) must be the stage where machines rise up to control humanity with merciless efficiency if “machine learning” seems like the start of a dark dystopian future (imagine The Terminator mixed with The Matrix).
Robotic process automation doesn’t really include any robots at all.
Thankfully, robotic process automation (RPA) doesn’t require anything of the sort, with the possible exception of efficiency. This automation software doesn’t really even use any robots.
According to Chris Huff, chief strategy officer at Kofax, “Robotic process automation is not a physical or mechanical robot.”
What is an Automated Robotic Process?
Instead, software robots running on a physical or virtual machine are the “robot” in robotic process automation.
According to Aaron Bultman, director of product at Nintex, “RPA is a type of business process automation that enables anyone to write a set of instructions for a robot or “bot” to perform.”
RPA bots are able to emulate the majority of computer-human interactions in order to complete a huge number of flawless jobs quickly and in large quantities.
That kind of automated technology is intended to seem somewhat dull, especially in comparison to Hollywood robots.
The main goal of RPA is to automate some of the most boring and repetitive computer-based operations and business procedures. Consider activities like copying and pasting or transferring files from one place to another.
RPA automates routine tasks that formerly required human intervention—often a lot of it done repetitively and laboriously. RPA also promises to increase organizational efficiency in this way.
Let’s take a step back and add a few more precise definitions of RPA to our toolbox. Use these to deepen your own understanding or to assist others to understand RPA, particularly when working with non-technical people.
Robotic process automation (RPA) must be the stage where machines rise up to control humanity with merciless efficiency if “machine learning” seems like the start of a dark dystopian future (imagine The Terminator mixed with The Matrix).
Thankfully, robotic process automation (RPA) doesn’t require anything of the sort, with the possible exception of efficiency. This automation software doesn’t really even use any robots.
According to Chris Huff, chief strategy officer at Kofax, “Robotic process automation is not a physical [or] mechanical robot.”
Five Ways to Define RPA in Everyday Language
RPA, to put it simply, is the method by which a software bot automates repetitive, high-volume, rule-based, and trigger-driven processes by combining automation, computer vision, and machine learning. -David Landreman, CPO of Olive.
- “All robotic process automation entails is programming a computer to carry out monotonous, repetitive manual activities. A bot will be able to duplicate any task that has a logical step to do it. —Vishnu KC, lead senior software analyst at ClaySys Technologies.
- “RPA is software that executes rules-based computer actions automatically.” Chris Huff, Kofax’s chief strategy officer.
- “RPA is a more sophisticated type of business process automation that can record tasks done by a person on their computer and subsequently carry out those same duties autonomously. In essence, it is a copycat virtual robot. — Marcel Shaw, an Ivanti federal systems engineer.
- “To put it simply, RPA’s function is to automate repetitive processes that were previously carried out by people. Applications and systems are programmed into the software to perform repetitive activities. A workflow with numerous steps and applications is taught to the software.” — Anthony Edwards, COO of Eggplant.
Does that Procedure Fit with RPA?
It is a separate tale for another day to evaluate your internal processes and workflows that would be suitable candidates for RPA.
Having said that, there are some fundamental standards worth mentioning in this context because they might give you and your team a clearer understanding of what RPA is and how it might be effective.
These criteria can also be useful as you talk about RPA installation with non-technical coworkers throughout the business. All operations that demand a lot of repetitive data work from employees fall under one of the broad categories.
According to Landreman, the CPO at Olive, “RPA is perfect for activities needing a high level of human data processing.”
“When logic-based solutions are anticipated, repetitive tasks or data-intensive procedures are the most popular deployments of RPA programs as supplements.”
Landreman suggests using the following four basic check-offs to identify potential RPA fits:
- The procedure needs to follow rules.
- The procedure needs to be repeated frequently or has a predetermined trigger.
- The process inputs and outputs must be well stated.
- There should be enough volume in the task.
How may RPA be used? Examples of business processes and use cases
Demonstrate to non-IT folks how RPA could minimize tedious labor in their daily occupations.
RPA should be easier to explain and promote outside of IT than other concepts like serverless or microservices, which are more difficult to simplify for non-technical individuals. The definitions listed above address this.
Also, it may be simpler to explain to non-IT individuals how RPA implementations could improve their daily lives by removing tedious tasks from the workplace. (The same job would be more difficult when attempting to convey to a field service technician the advantages of, for example, containerization.)
According to Muddu Sudhakar, CEO of Aisera, “businesses and organizations embrace RPA because it helps them boost efficiency across a wide variety of populations” (including users, customers, employees, sales and marketing personnel, business people, accountants, legal and finance experts, etc.).
Nevertheless, with concrete examples of how technology may be used in the workplace, the light bulbs typically go on more quickly. Let’s thus go back to data-intensive procedures as a suitable place to start.
Sudhakar reminds us of the wide range of operations that can be performed on data, including receiving, processing, collecting, correcting, creating, and so forth.
Consider the monotonous procedures in departments like finance, customer service, and human resources.
Think about how much labor there is in a field like finance: Just handling the receivables and payables alone has often required a lot of manual, repetitive work from specialized employees.
This is the reason why you hear grand claims regarding RPA in particular business functions: For instance, Gartner forecasts that by 2020, 73 percent of corporate controllers—up from 19 percent in 2018—will have implemented some kind of RPA in their financial departments.
Customer service and human resources are two examples of typical business units that use repetitive, rule-based, data-intensive operations. Certain sectors, like the insurance and financial services sectors, also suit the bill.
The COO of Eggplant, Edwards, provides the following concrete use case as an illustration: processing of returns.
Consider the last time you exchanged an online purchase to consider the implications both for you and the store where you made the transaction. In reality, those “free” returns are anything but.
“Traditionally, processing returns has been done manually and at a high expense. Companies can handle returns with RPA without increasing costs or delaying operations, according to Edwards.
“The RPA program can now manage the return, which includes a number of repeating steps: sending a message verifying return receipt, updating the inventory system, adjusting the customer’s payment, making sure that the internal billing system is updated, and so on.”
For both the customer and the company, the procedures involved in returning a pair of shoes that didn’t quite fit, for example, map pretty well to Landreman’s criteria above.
It’s a rule-based process with a defined trigger that is repeatable, precise inputs (like starting the return and returning the item), and certain outputs (like your refund), and there is unquestionably a sizable volume for retail firms in particular.
There are many “opportunities” for inefficiencies, mistakes, and other problems during this vital procedure.
Let’s face it, it is also monotonous. It’s the sort of process that RPA was created to enhance.
According to Huff from Kofax, “The ability to automate [with RPA] allows staff to shift their emphasis to more deliberate and important work while also avoiding data-entry errors that can harm processing times, compliance, and the general customer experience.”
Intelligent automation and RPA
RPA solutions must go beyond task automation and broaden their product lines to include intelligent automation in order to be competitive in the market (IA).
By adding branches of artificial intelligence including machine learning, natural language processing, and computer vision, this kind of automation builds on the capabilities of RPA.
Intelligent process automation calls for much more than just RPA’s straightforward rule-based architecture.
When compared to AI and ML, which focus more on “thinking” and “learning,” respectively, RPA can be thought of as “performing” tasks. It uses data to train algorithms, enabling the software to carry out tasks more quickly and effectively.
Artificial intelligence and RPA
Artificial intelligence (AI) is frequently confused with robotic process automation (RPA), but the two are very different.
Cognitive automation, machine learning, natural language processing, reasoning, hypothesis creation, and analysis are all combined in artificial intelligence (AI).
The key distinction is that AI is data-driven, whereas RPA is process-driven. While AI bots utilize machine learning to spot patterns in data, especially unstructured data, and learn over time, RPA bots can only follow the processes set by an end user.
To put it another way, RPA is only designed to duplicate tasks that are led by humans, but AI aims to replicate human intelligence.
RPA tools and artificial intelligence both reduce the need for human participation, but they automate processes in distinct ways.
Having said that, RPA and AI work nicely together as well. RPA may employ AI to address more complicated use cases and fully automate activities.
Also, RPA makes it possible to respond to AI findings more immediately than waiting for manual implementations.
Advantages of RPA
What other advantages can RPA offer outside business processes like the ones we just looked at in HR, customer service, and finance?
Eveline Oehrlich, Chief Research Analyst at DevOps Institute, suggests considering what your company could accomplish with the freed-up time from the IT team.
Oerlich observes that “the productivity promise of RPA is too promising to ignore.” “Technology will advance, but this does not always mean that occupations will be replaced by robots.
These bots should enable CIOs to free up staff members to work on more important projects that promote their company’s digital transformation initiatives.
Remind doubters that many companies provide free trials so you may try RPA out before you commit. “
RPA and AI Relationship
Why is there conflict?
Unlike, for instance, a deep neural network, RPA does not learn as it goes. The RPA bot often won’t be able to figure it out on its own if something changes in the automated process, such as when a field in a web form moves, as we previously observed.
Even if you adopt that stance, RPA and AI do in fact have a relationship, one that is expanding.
According to Kofax’s Huff, “RPA technologies that copy rules-based human actions complement AI technologies that enhance and mimic human judgment and behavior.”
The conventional “white-collar” knowledge-based workers and “blue-collar” service-based workers combine as the engine to drive productivity for a business, and the two technologies work hand in glove in a similar way.
Head of Jane.ai’s AI R&D David Costenaro observes that as RPA is implemented with AI technologies, it acquires capabilities.
Deep neural networks, one of the currently popular AI technologies, are “bringing brand-new tools to the RPA arsenal, notably in vision and language tasks,” according to Costenaro.
These features can now enable RPA workflows at decision nodes where they previously could not.
This enables an algorithm to “see” documents and images holistically and analyze them for routing and downstream logic.
Using AI and the ongoing development of processing ever-more-complex data simulates decision-making at the human level, according to Oerlich. “This speeds up decision-making and removes the possibility of prejudice on the part of humans.”
RPA challenges
Although RPA software can support business expansion, there are several challenges, including organizational culture, technological difficulties, and scaling.
A company’s Culture
While RPA may lessen the necessity for some employment rolls, it will also spur the creation of new positions to handle more difficult tasks, freeing up staff members to concentrate on higher-level planning and original problem-solving.
As job responsibilities change, organizations will need to encourage a culture of learning and creativity.
A workforce’s ability to adapt will be crucial for the success of automation and digital transformation programs.
You may get teams ready for ongoing changes in priorities by educating your personnel and spending money on training programs.
Scaling challenge
RPA may conduct numerous processes at once, however because of internal or regulatory changes, it may be challenging to scale in an organization.
A Forrester survey indicates that 52% of customers say they have trouble scaling their RPA program.
For a program to be considered mature, a corporation must have 100 or more active working robots, yet most RPA programs stop at the first 10 bots.
FAQs
Why is it called robotic process automation?
Instead, software robots running on a physical or virtual machine are the “robot” in robotic process automation.
According to Aaron Bultman, director of product at Nintex, “RPA is a type of business process automation that enables anyone to write a set of instructions for a robot or “bot” to perform.”
What are the types of robotic process automation?
Types of RPA
Observed automation: This kind of bot is often activated by the user and lives on their machine.
Unattended Automation: These bots operate in the cloud similarly to batch operations, processing data in the background.
RPA hybrid:
What is robotic process automation for example?
An illustration of robotic process automation
RPA definition Robotic process automation (RPA) conjures up images of physical robots engaged in labor-intensive tasks like housecleaning, lifting heavy things, and doing all other tasks performed by human workers.
Where is robotic process automation used?
The automation of customer interactions using RPA is a typical illustration of this. Businesses are increasingly embracing RPA to automate the time-consuming process of seeking information for clients rather than having an employee do it manually.
