Robotic process automation (RPA)

Robotic process automation (RPA) refers to an adaptable set of automations that first became available to consumers in the early twentieth century. Traditional forms of automation must be supervised by a specially trained employee. However, once properly developed and applied to a specific task, RPA can operate without human supervision. This gives businesses greater flexibility when assigning their employees to various tasks. By automating the simple and monotonous tasks, or by automating those tasks that can be performed more quickly and accurately by a computer service, businesses can improve the services they offer and increase their profit margins.

Several types of robots are now available to businesses. These automated software suites are capable of moving large amounts of data at rapid speeds without introducing errors, validating that data to ensure its accuracy, and interfacing with both the datasets and relevant consumers. Additionally, unlike previous forms of automation, RPA is capable of learning from its own mistakes, adapting to changes in business practices, and working to find solutions to unexpected problems. For these reasons, experts predicted that as RPA packages had become available to a greater number of businesses, RPA would continue to have a significant economic impact into the future.

Background

Automation is an important part of many modern industries. It occurs when repetitive tasks that were once carried out by humans are instead carried out by computers or specialized machines. Automation is typically carried out when a task is difficult for humans to perform effectively or quickly. However, it may also occur when a necessary task is monotonous and repetitive, allowing businesses to use their employees for more demanding jobs.

The history of robotic process automation (RPA) can be traced back to the 1990s. In the early 1990s, computer researchers began automating certain parts of the software design process. Specifically, they began automating the process of testing experimental user interfaces. At the time, this meant testing the visual elements of computer interfaces, such as text and icons, to ensure that they properly interfaced with existing applications.

Though the number of computer models available to consumers was small when compared to the modern market, it was growing at a rapid pace. As the home computer market grew, and more models became readily available to consumers, user interfaces were required to be more adaptable than ever before. Because these ever-increasing demands required large amounts of manual testing, computer engineers sought a more efficient solution. They designed scripts to automate large parts of the testing process, allowing engineers to spend more of their valuable time working on improving computer systems.

Though a significant improvement over the manual testing process, the automated testing scripts developed during the 1990s were far simpler than true RPA. During the 2000s, computer engineers developed screen scraping software, a true precursor to modern RPA. Screen scraping allowed automated processes to extract datasets from one application, then use those datasets in other applications. Though this process had little value to the average home computer user, it was extremely useful for any business or organization that routinely dealt with large datasets. Prior to the development of screen scraping, such datasets would have to be manually transferred between applications. Screen scraping was quickly adopted by banking institutions and insurance companies, allowing their software to handle large amounts of sensitive financial information.

During the 2010s, early RPA technology could be found in most major financial institutions and large businesses. At the time, many businesses sought to improve their efficiency by utilizing enterprise automation. Enterprise automation meant critically examining the internal processes of a business with the intent of replacing any manual processes with automation. Though initially difficult and expensive, enterprise automation allows businesses to future-proof their existing business models by ensuring that they can keep pace with more modern competitors. To accomplish these difficult goals, many businesses adopted RPA.

By the 2020s, RPA technology had become commonplace in the business world. In the past, RPA was only available to large businesses. The process of automation would be carried out by specialized technology firms, and many types of existing RPA software were bound by strict license agreements. However, as the financial barrier for adapting RPA technology to the needs of a business lowered, the process was adopted by a greater percentage of the financial world. Many technology firms began to offer RPA services to small businesses, promising to increase productivity and efficiency. As the number of technology firms offering automation as a service continued to grow, experts predicted that more businesses would turn to automation instead of human labor.

Overview

Traditional automation requires some human supervision. In manufacturing, this may involve a specialized worker overseeing machines that carry out assembly, periodically providing maintenance in the event of an error. In computerized automation, it may involve entering datasets and checking the resulting information provided by the automation software. RPA, however, is not supervised by humans. Instead, an automated script carries out the task independently and reliably.

Several types of automated systems are commonly used in RPA. The first, data entry systems, involves scripts that autonomously move large volumes of information between applications. Robots are much faster at data entry than their human counterparts and are able to rapidly move large volumes of information without introducing errors.

Robots in RPA are also commonly used for validation and verification. Computer scripts and algorithms can access large quantities of data more quickly and accurately than human operators. For this reason, they are adept at verifying the information provided by consumers, checking that such information matches the data a company keeps on file. These robots can be adapted to specific tasks, allowing them to be utilized in various industries. They are particularly common in the financial sector, where customers are commonly required to submit large amounts of information for unique or proprietary verification processes.

Systems integration robots are used to merge the operations of several existing technical infrastructures. These robots are most useful when one business has repeatedly acquired smaller businesses. Many businesses operate through the use of unique, proprietary, or specialized software. When a business is acquired, the larger business is forced to shift its acquisition to its own unique or proprietary systems, or to continually transfer important data between the two systems. Integration robots create complex connections between technological systems, allowing for new systems to be integrated into a larger network without intensive and time-consuming labor.

Trigger robots learn to carry out specific actions once another action or event has occurred. They are used for complex scheduling, acting as virtual assistants to humans. They are also used to independently carry out procedural tasks, such as supply-chain processes, emailing clients when shipments are sent, and tracking how inventory moves within a warehouse. Such robots not only perform their tasks more quickly and efficiently than a human, they also provide business owners with important datasets that can be used to maximize efficiency and profits.

Some businesses combine all of these styles of robot, automating large parts of their product process. Some companies offer RPA suites, in which several of these automation software packages are designed in a manner that allows them to interact with one another. For example, an RPA suite might be able to automate aggregating data points, verifying that data, calculating a total debt owed, then send information regarding that debt directly to a customer. Though this process might take a human a significant amount of time, a properly designed RPA suite could carry them out almost instantaneously.

Businesses primarily invest in RPA to increase their profit margins. Though investing in a specialized RPA might be a large initial expense, once the necessary processes have been automated, the company no longer needs to pay workers to complete them. This may allow the business to hire fewer workers, increasing its net profit by decreasing its expenses.

Automation experts argued that the economic importance of RPA would only continue to increase. They asserted that RPA would become more accessible to additional industries, resulting in significant growth in the RPA market. Unlike traditional automation processes, RPA software is able to learn from its mistakes, deal with unexpected problems, and adapt to sudden changes in a business model. As these processes continued to be improved and refined, RPA and similar intelligent technologies became more of a staple in both small and large businesses. In many industries, businesses that are unable to utilize RPA may be at a significant disadvantage to those who utilize modern computerized automation.

Continued growth in the RPA industry was expected to eventually allow machines and computer software to perform jobs that were traditionally held by human workers. Though this could result in drastic changes to the economy, including continued job losses, it would also allow businesses to reap greater profit margins. It could also free workers from completing mundane or repetitive tasks, allowing focus on areas where machines struggle, such as creative and abstract tasks.

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