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How Robotic Process Automation Works

Home / Future Sight / How Robotic Process Automation Works
12th November 2022
7 Minute Read

Robotic Process Automation (RPA) or software robots, are a growing field of automation, which is being increasingly adopted by companies and applied to processes across the organization. RPA applications enable businesses to improve their efficiency and effectiveness more cheaply than buying comparable automation solutions.

 

What is robotic process automation?

 

RPA is mostly used to mimic the tasks of employees when they carry out tasks such as filling in forms, extracting data from databases, and organizing files. The technology utilizes both APIs and user interface (UI) applications to emulate human interactions and carry out repetitive tasks. 

RPA robots are designed to learn and copy from existing users, which means there is no requirement to change the underlying IT infrastructure. The application of the RPA robots is flexible, so they can work with oversight from a staff member, attended or totally autonomously, unattended.

 

How does robotic process automation work?

 

RPA robots access the existing IT system and integrate with the current applications, automating tasks. This can be done in two ways, from the front end of the IT system, connecting desktop applications, or capturing data from the user interface. RPA robots can also access via the back-end systems and services using a process automation server.

RPA uses rules-based software to carry out business process activities in bulk. This frees up employees to work on tasks, which require extra human input. The laborsaving element of RPA is one of the strongest benefits of generating a better ROI.

RPA also has the flexibility to be combined with advanced cognitive technologies, such as natural language processing (NLP). This enables complex processes, which would normally have needed human interaction to function effectively. This is a growing sector of digital transformation in business where RPA and AI work in conjunction for a mutual goal.

 

The process of RPA

  

1. Evaluation

The whole of the existing relevant business process systems are evaluated through a series of interviews and workshops. All the stakeholders involved in the systems are included in the evaluation, as their hands-on experience is invaluable in an overall assessment. From the evaluation data, a plan can be drawn up, which defines objectives as well as possible opportunities for automation.

 

2. Design

The design of the RPA system is broken down into two parts. The initial practical part involves converting processes, that have been chosen as viable RPA subjects, into functioning automation solutions.

The second part of the design sees the documentation of these automation solutions into a plan right across the organization. This automation plan needs to be validated by all parties involved to create an accurate framework for the software construction.

 

3. RPA System Construction

All the research and fact-finding from previous parts of the program are collated and integrated into working solutions, bringing all the components together in one application. This condenses all the process logic into one business process application.

 

4. Realization

Once the business process application is completed the individual RPA processes need to be approved to certify their operation. Live testing is enabled in the production workspace and any errors or problems can be quickly corrected, as each of the processes are tested in turn.

Once again, all staff involved in the RPA process are involved in the implementation as they are valuable contributors in checking the automation outcomes are valid.

 

Examples of robotic process automation

 

With their frequent, high volumes of data needing frequent and repetitive processing, it’s no surprise that the financial sector was one of the first to recognize the advantages of RPA.

However, as technology has evolved so have the practical applications, so now many industries make use of the technology including manufacturing, retail, healthcare, insurance, and many more.

 

For many organizations, RPA demonstrates impressive results. However, it needs to be said there have been casualties too. A frequent stumbling block is when companies underestimate the time required and the cost to design and implement an RPA system. Similarly, the complexity involved to scale RPA technology in larger applications can also prove problematic.

RPA applications are diverse, and these are just a few practical examples where the technology excels:

 

1. Data migration and processing forms

The incompatibility of legacy and newer systems is an ideal application for RPA. Staff frequently need to manually retrieve data from legacy systems, so it can be used on the updated system. RPA can facilitate this retrieval with no risk of error. RPA can also be used in the conversion of paper data, where an RPA robot is able to read the hard copy and convert it into a digital version and store it. Enabling staff to concentrate on more pressing matters.

 

2. Supporting sales admin

Updating customer records on the CRM is time-consuming and repetitive. Each client has its own profile in billing, sales metrics, and individual requirements for monitoring. RPA is well-placed to handle such input freeing staff to devote more time to relationship building and closing sales.

 

3. Purchasing

An RPA solution can be set up to research data on the Internet, pull the relevant figures, and calculate the best deal. Scraping data off websites is another time intensive activity, which can be fraught with human error, so it makes sense to use RPA, which can address both failings.

 

4. Customer records and appointments

The healthcare environment is complex where patients have different needs and backgrounds, and where their treatment is equally involved. Even with a manual CRM, trying to coordinate all the different aspects of diagnosis and treatment is difficult to achieve.

An RPA solution, meanwhile, can schedule appointments as well as collate all relevant patient information such as the appointment request, where the patient would like to be treated, and the previous treatment schedule. This is all achieved with a much lower incidence of error, which is vital in a medical setting.

 

5. Customer call centers

Many incoming customer calls to businesses are handled using RPA technology, where the calls are routed to agents via a dashboard. If a call requires escalation to a human agent, the RPA system can search and collate all the relevant customer information and present it to the customer service agent on one screen for simplicity.

 

The benefits of robotic process automation

 

Enhanced productivity

In many commercial environments staff still must complete manual tasks, which take up a large part of the time available, so less is accomplished. RPA is ideally placed to take over these menial tasks and it’s not unusual for a team’s accomplished work to improve by 35 to 50%.

 

Improved efficiency

While the capital cost of implementing RPA is considerable, the technology does play a significant part in reducing costs in several ways. For example, in accounting, staff can spend considerable time transferring data from portals into the main business systems. This transfer is slow as well as fraught with the problems of human error. RPA can equally well carry out the same task with errors eliminated and costs reduced.

 

Reliable consistency

Errors in any part of the business are bad enough but errors in accounting directly hit the bottom line. Utilizing RPA in accounts will transform human errors and make them a thing of the past.

 

Improved data security

One of the common fears of directors looking over the possibilities of implementing RPA is that of data security. As it grows each year in its threat from external sources so RPA can be mistakenly judged as a weakness to it. However, the reality is that RPA parameters are strictly defined and managed, so the possibility of leaks or breaches is small.

 

Discovering analytics data

RPA can be programmed to help with the identification of unknown process gaps and areas where improvements need to be made. Such gaps highlight the limitations of human, and software design, and clearly demonstrate the need for augmented intelligent automation over and above RPA.

 

Final Thoughts

 

As RPA continues to spread across industries its advantages far outweigh the few disadvantages, such as high capital costs, and remedial costs on bots and scripts.

As both AI and NLP prove themselves in the marketplace, they offer a quantum leap in potential. Using the data that RPA provides AI improves its intelligence, enabling it to decide what the best action is to take formulated from the data.

More and more designers are treading the pathway to intelligent automation, and it seems such an obvious extension when combining AI, ML, and automation. At a higher level, AI enables companies to uncover valuable business insights that make them more resilient and agile. However, at the same time, it helps to automate tedious and repetitive processes, so staff can spend their time on tasks requiring a human touch.

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