The 4th Industrial Revolution is well and truly underway, and with it comes a new wave of technologies that are transforming the way we live and work. One of the most talked-about innovations emerging in recent years is robotic process automation (RPA).

RPA is a form of artificial intelligence (AI) that enables software ‘bots’ or ‘robots’ to carry out repeatable tasks that would normally be carried out by humans. This can include anything from data entry and processing to more complex activities like customer service or claims processing.

RPA has been hailed as a game-changer for businesses, offering the potential to boost efficiency, drive down costs, and improve the quality of service delivered to customers.

The worldwide robotic process automation (RPA) market was valued at roughly $2.65 billion in 2021. This market is expected to develop at a CAGR of 27.7 percent from 2021 through 2030. By 2030, the market size is projected to be worth $23.9 billion in the United States.

Robotic process automation, or RPA, is a form of business process automation where software robots are used to automate repetitive, rule-based tasks usually performed by humans. It uses automation technologies to interpret, trigger responses, and communicate with other digital systems just like humans do.

It also allows decision-makers to prioritize more complex tasks by freeing up human resources, thereby increasing the return on investment (ROI) from employees. In order for RPA to be successful, however, data management processes and data architecture must be evaluated and strong data governance put in place. RPA is reliant on high-quality data and without the right guidance, it will not reach its potential.

There are 3 major types of robotic process automation:

1. Attended automation,
2. Unattended automation,
3. Hybrid RPA.

Attended Automation

This type of bot is used for tasks that require human intervention and can only be completed with the help of a person. These are usually low-volume, high-complexity tasks such as claims processing or customer service. 

Attended bots are mostly used in the front office where there is direct customer interaction. They augment humans by providing real-time suggestions or automating tasks that would otherwise need to be performed manually. For example, an attended bot can be configured to offer recommendations to a sales representative while they are on a call with a customer.

Unattended Automation

This type of bot is commonly used for tasks that don’t need human intervention and can run on their own. These are usually high-volume, a low-complexity task such as data entry or simple rule-based processes. 

Unattended bots are mostly used in the back office where there is no customer interaction. They can be scheduled to run at certain intervals or can be set up to start running as soon as a trigger event occurs. For example, an unattended bot can be configured to automatically generate reports after collecting data from various sources.

Hybrid RPA

As its name implies, hybrid RPA is a combination of both attended and unattended automation. In this setup, there are times when a process requires human intervention and there are also times when it can be automated. 

A good example of this is in data entry where a bot can do the initial data collection but will need a person to verify the accuracy of the data before it is entered into the system.

RPA tools on the market today are incorporating features of artificial intelligence, and it is important to understand how these two concepts differ.

Artificial intelligence is a method of programming computers so that they can learn from data, identify patterns, and make decisions with minimal human intervention. AI also Incorporates Machine Learning, Natural Language Processing, and other sub-disciplines.

Robotic process automation is a way to use software bots to automate business processes.

RPA is sometimes referred to as “software robotics” because it uses automation technologies to mimic the actions of human workers.

The main difference between RPA and AI is that RPA is process-driven while AI is Data-driven.

RPA is used to automate business processes, while AI is used to make decisions and take actions that are not possible with rule-based systems.

AI can be used within RPA to make the automation process more intelligent. For example, incorporating machine learning into RPA can help the software “learn” from data so that it can make better decisions and take actions that are not possible with rule-based systems.

The next wave of automation is already upon us, and it’s called hyper-automation. Gartner defines hyper-automation as “the combination of multiple machine learning (ML), packaged software and processes to deliver work.” In other words, it’s the use of advanced technologies, like artificial intelligence and robotic process automation, to automate tasks end-to-end.

Hyper Automation goes beyond RPA in that it not only automates processes but also makes decisions traditionally reserved for humans. Hyper Automation has the potential to redefine how we work by automating entire business processes, rather than just individual tasks.

While hyper-automation may sound like a futuristic concept, many organizations have already started to implement it. According to Gartner, a new prediction, the worldwide market for technology that allows hyper-automation will reach $596.6 billion in 2022. This is up from $481.6 billion in 2020 and a projected $532.4 billion in 2021.

1. RPA tools work by providing a software “robot,” or bot, that can be configured to mimic the actions of a human user. This includes the ability to interpret and trigger responses from applications in the same way that a human user would.
2. Configuring an RPA bot typically involves recording the steps taken by a human user as they complete a task within an application, such as logging in, entering data, performing calculations, and generating reports. These steps are then converted into an automated process that can be run by the bot without human intervention.
3. When configuring an RPA bot, businesses can choose from a number of different “recorder” tools that allow them to capture the required input and output data, as well as the specific actions and steps that need to be taken. These recorder tools usually have different capabilities, so it’s important to select one that’s appropriate for the task at hand.
4. Once an RPA bot has been configured, it can be deployed on a virtual machine or server and left to run independently. This frees up human users to focus on more strategic tasks, while the bots handle the routine, mundane work.

Generally speaking, RPA bots are most effective when used for repetitive, rules-based tasks that are completed in a similar way each time. They can also be used for more complex tasks if the required input data is well-structured and predictable.

There are multiple benefits of RPA, including:

• Easy to implement and configure: RPA requires little to no coding, making it accessible to non-technical staff. User interfaces with drag-and-drop features make it easy to get started with RPA.
• Increased accuracy: Configured to follow specific rules and processes, they can help to improve the accuracy of work (particularly when compared to human error).
• Improved compliance: RPA can help organizations to stay compliant with industry regulations as it can be configured to adhere to specific standards and procedures.
• Increased data security: They can help to reduce the risk of data breaches as they are configured to work with sensitive data. 
• Operational Efficiency: automate end-to-end processes resulting in operational efficiency gains for the organization.
• Enhanced customer satisfaction: RPA-driven processes often result in reduced processing time and improved accuracy, both of which can lead to enhanced customer satisfaction.
• Reduce operational costs: help organizations save money as it can automate tasks that would traditionally be completed by human employees (thus reducing labor costs).

According to Deloitte Global RPA Survey, RPA continues to outperform expectations on a variety of dimensions, including: 

“improved compliance (92%), higher quality/ accuracy (90%), increased productivity (86%), and lower costs (59%).”

There are a few drawbacks when it comes to implementing RPA, including:

• Scaling: It can be difficult to scale RPA when the number of bots required starts to increase. This is because each bot needs to be configured and deployed individually. Forrester reports that 52% of customers find it difficult to expand their RPA program. In order to be considered an advanced program, a company must have 100 or more active working robots, but few RPA initiatives get past the first 10 bots.
• Change management: The need for certain job roles will be reduced with RPA, but it will also create opportunities for new roles to emerge that are more complex. This shift will require a workforce that is adaptable and able to learn new skills quickly. By investing in training and education, you can ensure that your staff is prepared for the ever-changing landscape of work.
• Interoperability: One of the challenges of RPA is that it can be difficult to integrate with other systems and technologies. This is because RPA is often used to automate tasks that are completed in legacy systems. In order to overcome this challenge, businesses need to have a well-thought-out integration strategy in place.

There are some cases where RPA is not the best solution. These include:

• Tasks that require human judgment: RPA bots are best suited for tasks that are rules-based and don’t require human judgment. If a task requires creativity or interpretation, it’s best left to a human worker.
• Tasks that are not repetitive: RPA is most effective for tasks that are completed in the same way each time. If a task is not repetitive, it may be more efficient to use another automation solution or to have a human worker complete the task.
• Tasks with unstructured data: RPA bots rely on well-structured input data in order to function properly. If the data is unstructured, it can be difficult or impossible for the bot to understand and act on it. In these cases, it’s best to use another type of automation solution or to have a human worker complete the task.
• Tasks that require frequent changes: If a task is likely to change frequently, it may be more efficient to use another type of automation solution, or to have a human worker complete the task. This is because changes to an RPA bot can be time-consuming and expensive.

Banking and financial services: 

The banking and financial services industry is under constant pressure to comply with regulations and protect customer data. RPA can help by automating tasks such as Know Your Customer (KYC) compliance, Anti-Money Laundering (AML) compliance, and fraud detection. 

In addition, RPA can be used to streamline processes such as loan processing, account opening, and credit card application processing. By automating these processes, banks and financial institutions can reduce costs, improve compliance, and free up staff to provide better customer service.

6 Ways to Use RPA in Finance

eCommerce: 

With the growth of online shopping, businesses in the eCommerce sector are under pressure to provide a seamless customer experience. RPA can help by automating tasks such as order processing, customer service, and fraud detection. 

In addition, RPA can be used to streamline the product listing process and monitor stock levels. It can also be implemented in content-created automated marketing workflows. This helps eCommerce businesses save time and money while providing a better experience for their customers.

How RPA Can Benefit eCommerce Companies: 7 use cases

Marketing: 

Marketing is a data-driven industry that is under constant pressure to show ROI. RPA can help by automating tasks such as lead generation, customer segmentation, and email marketing. 

In addition, RPA can be used to create and track marketing campaigns, and to analyze customer data. By automating these processes, marketing teams can reduce costs, improve efficiency, and free up staff to focus on more strategic tasks.

How Companies Can Effectively Implement RPA In Their Marketing Processes

Food Tech: 

The food and beverage industry is under pressure to meet the demands of a growing population. 

Pending reconciliations, for example, can accumulate over time and slow down operations if not managed quickly and efficiently. RPA can automate this process by extracting data from purchase invoices, matching it with supplier records, and then generating reconciliation reports. This improve accuracy, speed up reconciliations, and reduces operational costs.

Top RPA Use Cases in the Food and Beverage Industry

Healthcare: 

The healthcare industry is under constant pressure to improve patient care while reducing costs. RPA can help by automating administrative tasks such as claims processing, benefit eligibility determination, and prior authorization. In addition, RPA can be used to streamline clinical processes such as patient scheduling, transcription, and laboratory result entry. By automating these processes, healthcare organizations can reduce errors, improve efficiency, and free up staff to provide better patient care.

RPA in Healthcare: 6 Use Cases to Improve Patient Care

Human resources: 

RPA can automate various HR processes, such as performance reviews, benefits administration, onboarding of new hires, and employee offboarding. 

By automating these processes, HR professionals can spend less time on administrative tasks and more time on strategic initiatives that will help improve the company’s bottom line. 

For example, RPA can help with automating job postings, tracking applicants, and conducting initial phone screens. This allows HR professionals to spend more time developing relationships with potential candidates and understanding their qualifications.

 How RPA Can Transform Your HR Operations For The Better

Telecom: 

5G, edge computing, and the Internet of Things (IoT) are transforming the telecom industry. As demand for telecom services increases, so does the need for efficient apps and infrastructure. RPA can help telecom companies streamline their processes and share data more effectively. 

Additionally, AI processing can be used to analyze network usage data and improve the customer experience. Finally, customer recordkeeping, service affordability, and regulatory compliance can all be improved through the use of RPA. 5G services provide an additional opportunity for telecom companies to generate revenue.

Insurance: 

The insurance sector is one of the most complex and heavily regulated industries. RPA can help by automating tasks, such as claim processing, premium calculation, fraud detection, policy administration, and customer onboarding. 

This not only saves the company time and money but also helps to improve customer satisfaction by reducing the time it takes to process claims and get payouts to policyholders.

Retail:  

Retailers are turning to RPA to help them keep up with the competition and scale their businesses. RPA can automate tasks such as order processing, customer management, merchandising, and even warehouse management. 

They are using RPA solutions to speed up their order-to-cash cycles, reduce checkout times, and enhance customer engagement. In addition, RPA can help retailers improve back-end operations such as supplier management, inventory control, and store data analysis.

Why RPA Is Essential to The Future of The eCommerce Industry

When implementing RPA, it is important to keep the following best practices in mind:

1. Define the business process: 

The first step is to understand what the business process is, what steps are involved, and how it is currently being performed. This will help you identify which parts of the process can be automated and where robots can be deployed. Process Design Document should be created which will act as a blueprint for the implementation.

2. Assess the technical feasibility: 

Once you have defined the business process, you need to assess the technical feasibility of automating it. This includes understanding the technology requirements and whether the current IT infrastructure can support it. Process variations, exceptions, and edge cases should be identified and documented.

3. Build the business case:

 The next step is to build the business case for RPA. This includes understanding the cost savings, efficiency gains, and other benefits that can be achieved through automation. Additionally, you need to understand the risks associated with implementing RPA and how they can be mitigated.

4. Pilot test the solution: 

Before roll-out, it is important to pilot test the RPA solution to ensure that it works as expected and that there are no unforeseen issues.

5. Manage change: 

RPA can significantly impact organizational structure and culture. It is important to manage change effectively to ensure the successful adoption of the technology. You can do this by communicating the benefits of RPA, training employees on how to use it, and providing support during the transition.

6. Monitor and optimize performance: 

Once the RPA solution is up and running, it is important to monitor and optimize performance to ensure that the benefits are being realized. This includes regular monitoring of KPIs, such as throughput, accuracy, and cost savings.

How much does RPA cost?

The cost of RPA depends on a number of factors, including the complexity of the process being automated, the number of bots being deployed, and the length of the deployment. Generally speaking, RPA can be deployed for a fraction of the cost of traditional software solutions.

What is the difference between Chatbot and RPA?

Chatbots are software applications that simulate human conversation. RPA is a type of software that automates repetitive and time-consuming tasks. Chatbots can be used to automate customer service tasks, such as answering commonly asked questions. RPA can be used to automate any type of task, including those that are not well suited for chatbots.

How long does it take to implement RPA?

The time frame for implementing RPA depends on the complexity of the process being automated and the number of bots being deployed. Generally speaking, RPA can be deployed much faster than traditional software solutions.

Robotic Process Automation and Kiimkern

Capitalizing on RPA requires the ability to quickly and easily deploy bots. Kiimkern is a leading provider of RPA software that helps organizations automate their business processes. With Kiimkern, you can define the process you want to automate, deploy bots in minutes, and monitor performance in real-time.

In addition, you’ll get access to a number of features that make it easy to manage your RPA deployment, including an intuitive user interface, pre-built connectors for popular applications, and integration with leading ITSM platforms.