Robots are coming, and they’re everywhere. No matter just confined to mindless machines operating on factory assembly lines, the robots of the future can also think and perform tasks like humans. This idea lies at the heart of robotic process automation (RPA).
As with all things tech, this might seem confusing at first. Just the term robot is itself loaded with many connotations and confusions.
Don’t worry though; that’s why we’re here. If you’re a beginner to RPA, this article will walk you through all the basics.
So keep on reading to find out everything you need to know about robotic process automation!
RPA 101: Robotic Process Automation Fundamentals
Now, what exactly is Robotic Process Automation?
Simply put, Robotic Process Automation (RPA) is a technology that let’s robots do complex tasks in place of humans. Unlike traditional mechanical robots in factories, however, the robots of RPA are software robots; smart computer programs optimized for virtual tasks.
The complex tasks these robots perform are large in number and repetitive. RPA, with its high speed and intelligence solving these tasks, can be easily configured to perform a large number of them in a short amount of time.
Essentially, RPA interacts with computer software the same way that humans do. RPA are specifically designed to capture these human interactions, thereby making certain tasks easier.
Why Use RPA?
The major benefit of using RPA is that they can cut costs for a business, improve data processing and guide customers better for an improved overall experience.
RPA is also easy to integrate with existing IT infrastructure systems. As a result, an organization can adopt RPA without investing time and resources to train employees to use new software tools.
RPA can optimize tasks like calculating, inputting data, copying data from one application to another, or logging into applications.
Who Uses RPA?
RPA isn’t just a dream in some far off future; it’s also very much a reality already present in existing industries and businesses.
Here are some industries that are currently employing RPA as part of their organization:
Organizations use RPA in finance for several reasons. They can quickly scan and process invoices, compare account balances, and automate governing procedures.
By deploying RPA in the healthcare industry, healthcare providers can easily document and track transactions in a healthcare system. This documentation may include structured log files and forms involving data entry and processing.
RPA also has several use cases in the telecommunications industry. For example, through RPA, a telecommunications company can set up new billing systems and services for both new and existing accounts.
As far as the supply chain goes, RPA can do anything from automating data input, smart system maintenance, and even tracking shipments.
A technical industry like systems integration will naturally benefit from RPA. Major players in the systems integrators market, such as Deloitte, Genpact, and Wipro, all use RPA to develop vertical scaling applications for their clients.
Many other industries are deploying RPA for several use cases, but they all have one thing in common: they have high volume, predictable tasks that humans have traditionally performed.
Types of RPA
Broadly speaking, RPA can have two major categories. Each category differs from the other based on the extent to which it is automated. The categories of RPA are as follows:
The first level of automation is attended automation. The software bots in attended automation have to be manually triggered. Although there are rules for this kind of automation, they are not as rigid, so the process as a whole is only semi-structured.
The second level of automation is robotic automation. Unlike with attended automation, events or schedules trigger software bots in robotic automation, so such bots are therefore fully automatic. In addition, robotic automation has a rigid set of rules enforced by the system at all times.
Each type of RPA comes with its own set of advantages and disadvantages, so make sure you go with the one best suited for your business application.
Challenges of RPA
As with any technology, several pitfalls and challenges come with RPA. Here are some of the significant challenges associated with RPAs:
Hard To Scale
Although RPAs already exist in organizations, they do so on a small scale. Even though software bots are easy to introduce and implement initially, they are challenging to govern and manage. For this reason, they can be hard to introduce on a larger scale.
Another major concern is privacy; RPA bots often work with sensitive data, including login credentials and personal information. Although RPA vendors are now seeking ISO 27701 certification, RPA is still a long way off from fully complying with security standards.
RPA can handle certain use cases, and it can handle them well. Challenges can arise, however, when use cases and applications evolve beyond what the developers initially anticipated. Because of such cases, RPA is not as resilient as traditional human labor.
RPA technology is very much in its infancy stages. Although it can automate tasks, it still struggles with complex processes. As a result, making multiple decisions in complex processes and handling more than a few applications at a time can often lead to RPA failure.
Finally, perhaps the biggest challenge with RPA is difficulty integrating new technology due to the organizational culture.
Not all employees are willing or able to adapt to new changes and the new job roles and responsibilities that come with them. For this reason, training programs for RPA are a must.
RPA vs Artificial Intelligence (AI)
Although both RPA and AI are based on machine intelligence, they are not the same thing.
RPA is an automation process that is used side by side with people to automate repetitive tasks. On the other hand, AI is not just limited to automating processes but is a general technology developed to replace humans altogether instead of working alongside them.
Whereas RPA uses structured inputs and rigid logic, AI can get by using unstructured inputs and developing its own logic.
Despite these differences, organizations can use RPA and AI side by side. RPA works best when paired with AI technologies that can help the software bots perform much better.
Despite being a relatively new technology, Robotic Process Automation shows excellent promise moving forward in a future where data and transactions are everywhere.
By automating large volume repetitive tasks, RPA can help many industries optimize their business processes and ultimately save on costs, time, and human resources.