Across industries, automation has made it possible for organizations to do more with less, reducing expenses while improving accuracy and output. But traditional automation is generally built on programming, using high-code applications to integrate with relevant systems. RPA takes a different approach, performing tasks at the user-interface level. And, because RPA bots are designed to copy and learn from user actions, there is no need to make any changes to the underlying IT infrastructure. RPA robots can be attended or unattended, depending on whether they require any assistance or oversight from human operators.

In essence, RPA automates specific kinds of actual human activities and large-scale data movement activities, capable of handling repetitive, monotonous, and rule-based tasks and duties, quickly and accurately.

In many organizations, it is not uncommon for employees to spend most of their time engaged in repetitive, monotonous tasks. While essential to the business, these tasks tend to pull worker focus away from other jobs that require intelligence and creative thinking. RPA can assume responsibility for many of the mundane tasks that would otherwise monopolize employee time.

Because RPA robots are capable of learning from human users, they are also capable of recreating a range of user actions. This includes the following:

• Logging into applications
• Filling out forms
• Scraping browsers
• Collecting data from applications
• Extracting content from emails, PDFs, and forms
• Copying and pasting information
• Processing files
• Making calculations
• Opening emails and attachments
• Moving documents and files
• Many other rule- or schedule-based tasks

Again, RPA bots take the role of the human user in performing rule-based tasks. As such, they can be employed to interact with nearly any application or website.

Traditional automation has created efficiency for structured and large-scale organizational processes. RPA is smaller scale, more individual, and—most importantly—task oriented as opposed to process oriented. More specifically, RPA integration provides the following advantages:

Improved accuracy

Although RPA robots are designed to mimic human behavior, there is one area where they don’t: they never make mistakes. RPAs are completely rule based, never deviating as they perform their tasks. And if the rules are sound, the bots are completely accurate in all their work.

Reliable compliance

Many mundane, repetitive employee tasks exist to ensure compliance with rules, laws, and regulations. Unfortunately, repetition can breed inattention, and when human employees make errors, it is often the business itself that suffers. RPA robots don’t get complacent; they approach every task with the same attention, significantly reducing the risk to the organization. And because everything they do is monitored and documented; businesses are kept firmly in the loop regarding compliance with related regulations.

Reduced costs

Human-led processes don’t only take up valuable time from employees, they can also be very expensive. RPA can reduce the wage bill wasted on simple tasks, while also allowing businesses to get more done in less time. As a result, RPA significantly reduces processing costs, often providing a positive return on investment within one year.

Enhanced scalability

As businesses grow, additional RPA bots can be easily employed in parallel to address increased needs. They may be deployed extremely quickly and at relatively low cost, freeing up businesses to expand as far and as quickly as they are capable.

Increased speed

As previously stated, RPA bots do not get tired, nor do they make mistakes. They are also capable of moving through processes very quickly without having to pause. Together, these factors allow for more processes and tasks to be completed in a shorter amount of time.

Better utilization of human employees

By taking on the responsibilities of employees’ non-value-add activities, RPA allows talented workers to apply their skills in more-valuable tasks. Employees have the time and freedom to accomplish more, improving productivity across the business.

Integration with legacy systems

Because RPA takes the position of the user, rather than having to interface directly with system back-ends, it integrates easily with most legacy systems. This seamless integration allows businesses to freely invest in and employ RPA, without having to worry about upgrading everything all at once. At the same time, RPA empowers businesses to unlock the value of trapped legacy data in systems that were previously inaccessible.

AI compatibility

Standard RPA can perform simple, rules-based tasks. AI-enhanced RPA robots can do even more. With the right AI technology, RPA can process unstructured data, recognize speech, apply machine learning (ML) models and natural language processing, and more. This enhanced intelligence makes it possible to automate not only repetitive tasks, but also higher-order, cognitive ones.

Robotic process automation goes beyond simply being another tool in the automation toolkit—it is a transformative technology that has the potential to revolutionize how organizations achieve their strategic goals. Its unique characteristics empower organizations with the flexibility and agility to solve problems and adapt to market changes like never before. RPA’s transformative power is tied directly to the following:

RPA allows organizations to tackle extensive operational challenges

RPA's versatility extends from automating simple tasks to integrating with AI for complex operations, such as data analysis, customer service, and various essential back-office tasks. This adaptability breaks down barriers to what can be automated, allowing organizations to address a wide range of operational challenges without disrupting existing systems.

RPA big data analytics provide insights into business patterns and workflows

RPA, especially when enhanced with AI, can collect, organize, and analyze Big Data at an unprecedented scale and speed. This real-time analytical capability transforms organizations from being reactive to proactive, shaping their business strategies based on data-driven insights. The resulting clarity in understanding business patterns and workflow performance makes it possible for businesses to optimize their current processes and operations, and even discover new revenue streams.

RPA makes achieving transformation quick and straightforward

RPA minimizes common challenges in digital transformation, such as system compatibility and employee training, by operating at the user-interface level. Its rapid deployment and flexible scaling make it a low-risk, high-reward solution, often showing a complete return on investment in as little as a year. This combination enables organizations to adapt quickly to market changes, implement new processes, and stay competitive without the typical setbacks of traditional digital transformation pathways.

RPA offers a competitive advantage through increased efficiency and lower costs

Used correctly, RPA not only boosts overall productivity but also significantly reduces operational costs. With tasks completed faster and more accurately, organizations can deliver better services and products to their customers, thereby gaining a competitive edge.

Robotic process automation is an invaluable tool that helps companies break free from the redundant, inefficient processes that consume vast amounts of an organization’s time and resources. By automating these tasks, businesses can regain those valuable resources, refocusing their efforts on core competencies and strategic initiatives. This is made possible thanks to a host of features and capabilities intrinsic to RPA technology. These include:

• Security
  Security is paramount when automating business processes, especially those that handle sensitive data. RPA platforms are designed with stringent security measures, such as encryption and role-based access controls, to ensure that data integrity and confidentiality are maintained even when accounting for multiple users at different levels.
• Automation lifecycle management
  Managing the entire lifecycle of automation, from bot creation to deployment and maintenance, becomes easier with built-in features specifically designed for automation lifecycle management. This ensures that automation projects remain aligned with organizational goals and efficiently adapt to changes in the business environment.
• Automation/business goal benchmarking
  Advanced RPA platforms offer features that enable organizations to benchmark their automation initiatives against specific business goals. This capability helps in aligning automation objectives with overall business strategies, ensuring a greater return on investment.
• Bot creation
  Ease of bot creation is a significant factor in RPA's popularity. With user-friendly interfaces and drag-and-drop functionalities, even non-programmers can create bots for a variety of tasks. Some advanced platforms also offer AI capabilities to create intelligent bots that can perform complex operations.
• Native computer vision
  Native computer vision capabilities within RPA platforms enable bots to interact more naturally with applications just as a human would, making them more effective in complex environments. This feature enhances the range of tasks that can be automated, further increasing efficiency.
• Source control
  Source control (also called version control) is vital for large businesses that wish to scale automation across their organization. It ensures that multiple developers can work simultaneously on different parts of an RPA project without conflicts, enabling better tracking of changes, the ability to reload previous versions, and seamless updating.
• Options for hosting and deployment
  RPA solutions generally come with a variety of hosting and deployment options, from on-premises servers to cloud-based solutions. This flexibility gives businesses the power to select the option that best fits their budgetary, regulatory, and scaling needs.
• Error and exception handling
  RPA is able to efficiently handle exceptions and errors during automation. When a bot encounters an issue it can't resolve, proactive exception handling features ensure that the bot either retries the task, assigns the task to another bot, or raises an alert and reports the issue to a human operator so that it may be resolved.
• Optical character recognition
  Optical character recognition (OCR) technology within RPA allows bots to read and interpret text from unstructured documents and images. This functionality enables automation in areas like data extraction from invoices, forms, and emails, thus broadening the scope of tasks that RPA can handle.
• Scriptless automation
  One of the most user-friendly features of RPA is the ability to create automated workflows without writing a single line of code. This feature makes automation accessible to a broader audience within an organization, enabling even those without technical skills to contribute to automation initiatives.

Robotic process automation and intelligent automation (IA) are closely related, but they are not, strictly speaking, the same thing; each serves a different function within the automation landscape. By itself, RPA excels at handling repetitive, rule-based tasks, such as data entry and basic calculations. It can mimic human actions, making it a valuable tool for automating mundane processes. However, its functionality is generally limited to tasks that are straightforward and do not require complex decision-making or understanding context.

IA goes beyond these limitations. By integrating sub-disciplines of artificial intelligence like machine learning, natural language processing, and computer vision, IA systems are capable of handling more nuanced tasks that require cognitive abilities, such as understanding human language or making decisions based on data analysis. In essence, IA is like RPA with an added layer of intelligence, offering a more comprehensive solution for automating a wider range of business processes. This advanced capability makes IA an ideal element within the RPA toolkit, providing organizations with a more versatile automation solution.

Much like the relationship between RPA and intelligent automation, RPA and AI also serve different-yet-complimentary roles in terms of automation. Although AI can help RPA address more complex tasks and RPA can improve AI effectiveness by automatically implementing AI insights, the major distinction is that AI is data-driven while RPA is process-driven. RPA bots must adhere to pre-defined processes, while AI can employ machine learning to become more intelligent with experience.

When it comes to choosing the best possible RPA solution, organizations need to consider several factors that can impact the tool's effectiveness—and determine what kind of an ROI the company can expect. The following questions can help ensure that the RPA journey gets started off on the right foot:

• How easy is it to implement?
  Opt for an RPA solution that is easy to deploy within an existing IT infrastructure. A steep learning curve can delay ROI and make adoption challenging.
• What is the expected time to value?
  Every tool is an investment; the best tools are the ones that repay that investment quickly and then begin generating revenue. Research how quickly the RPA solution is likely to deliver measurable results, contributing to a faster ROI.
• How intuitive is it?
  The tool should be user-friendly, allowing both technical and non-technical staff to design and manage bots with minimal training.
• Is it competitively priced?
  While cost should never be the only determining factor, a solution that offers competitive pricing without compromising on quality is always a smart choice.
• Does it offer a comprehensive set of feature?
  Features like security protocols, analytics, and bot creation capabilities are vital. The more comprehensive the feature set, the more versatile the RPA solution.
• How fast is it?
  The bots' ability to perform tasks quickly can have a direct impact on operational efficiency, so evaluate the speed at which bots can be developed and run.
• Can it scale with the business?
  As the business grows, the demands on the RPA solution will grow too. Choose a solution that can easily scale to meet increased demand.
• Can it leverage API and IDP technology when needed?
  Ensure the RPA tool has the flexibility to integrate with Application Programming Interfaces (APIs) and Identity Provider (IDP) technologies, as these can be critical for advanced automation and secure access management.
• Does it provide a smooth handling process?
  The RPA tool should be capable of managing errors or exceptions smoothly, alerting human operators when necessary.
• Is it properly supported by the vendor?
  Ensure that the vendor provides reliable customer support and post-implementation services to help resolve any issues and maximize the utility of the tool.
• How effective are its governance features?
  Proper governance features should be in place for compliance, auditing, and management of the digital workforce, ensuring that the bots are adhering to both internal policies and external regulations.

Although there are different paths to incorporating RPA technologies in an organization, many top companies follow a similar journey. This journey can be broken down into the following steps:

1. Conceptualization

Organizations must first identify and fully define their vision for incorporating RPA. This exercise involves asking questions of employees and stakeholders to determine what business needs should be fulfilled by the RPA. It also includes speaking with other organizations (partners, vendors, etc.) that may already be utilizing RPA, to provide an insider’s perspective and help establish a roadmap towards digital transformation. Because RPA sits within a broader hyperautomation toolkit, the goal is to know when to apply RPA to the right business problem and when to apply other automation technologies to maximize business value.

2. Leadership organization

The next step is to assign leadership roles, with the two most important being RPA sponsor and RPA evangelist. The RPA sponsor is the top-level manager over RPA initiatives, handling most of the responsibility associated with budgeting, as well as establishing overall RPA strategy. The RPA evangelist takes the role of project lead, assigning other leadership positions, and aligning departments and business units to help identify high-value processes and criteria for RPA success.

3. Evaluation and selection

Traditionally, consumer IoT devices are more difficult to manage. IoT device management facilitates effective governance of devices already deployed in the field, allowing organizations to send updates and patches, and to improve device functionality without negatively affecting the user experience.

4. Proof-of-concept testing

Next, the organization will need to develop a proof of concept and put it to the test. This includes the RPA business case, implementation model, and any relevant assumptions. The proof-of-concept test will demonstrate within a closely monitored environment whether the assumptions were accurate and if the implementation model is effective. Although this is only a test phase, organizations are capable of learning more if the test processes relate to a range of systems and applications. Likewise, organizations will get more out of their tests if they eschew low-risk processes for ones that will have a more significant impact on business value.

5. Real-world testing

With the proof-of-concept validated, the company in question can now deploy their RPA solutions in the real world of their everyday business operations. Assessing the performance of these RPA pilot programs and comparing them to established success criteria and exit requirements, organizations can determine the actual benefit of employing robotic process automation. They can also make any final revisions that may be necessary prior to full rollout.

6. RPA center of excellence

Organizations that are fully committed to RPA and digital transformation will next want to plan for full-scale adoption. To facilitate this, they may decide to create an RPA Center of Excellence (CoE). The CoE will help establish and govern RPA best practices, standards, support, and tools and templates throughout the company. Simply put, the CoE becomes the primary resource for RPA expertise, helping business units establish and get the most out of their automations. However, essential though RPA is, it is only one of many automation-technology options COE may wish to consider when faced with specific use cases. In addition to RPA, businesses may utilize intelligent business processes powered by machine learning, advanced analytics, and business process management (BPM). By relying on a complimentary combination of these and other tools, organizations can adopt a hyperautomation strategy to deliver end-to-end automation beyond RPA capabilities.

7. Expansion and adoption

At this point, the organization should be up and running with their own RPA solutions. The next step, therefore, is to expand upon those solutions and help the workforce begin to use RPA on their own. The CoE will take a lot of the responsibility here, guiding departments in employing bots, monitoring progress, and using their expertise to further enhance RPA solutions.

8. Monitoring and improving

With RPA fully adopted, the final, ongoing step is to continually monitor and refine. As businesses become more familiar and comfortable with robotic process automation, they will naturally be able to identify areas of improvement, creating a more effective approach to automation as they go.

Because RPA is so easy to employ and can be used in such a range of tasks, there are RPA success stories among essentially every industry. Industries that have seen the most significant advantages of RPA include the following:

• Insurance
• Telecom
• Banking
• Healthcare
• Business process outsourcing
• Finance
• Manufacturing
• Life science

While RPA offers numerous benefits for automating repetitive tasks and improving operational efficiency, it also comes with its own set of challenges. Here's how you can tackle some of the most common issues:

• Challenge: Scaling RPA across different departments can be a difficult, time-consuming process.
  Solution: Opt for RPA platforms that offer effective scalability features, including the ability to easily add new bots and integrate with existing systems.
• Challenge: Basic RPA tools can only handle structured data and simple tasks.
  Solution: To address more complex processes, choose an RPA tool that supports intelligent automation features, such as machine learning and natural language processing.
• Challenge: RPA may carry certain security concerns, including unauthorized access and data breaches.
  Solution: Make sure the RPA tool has strong security protocols and integrates well with your existing security architecture.
• Challenge: Bots can break if there are changes in the underlying applications they interact with.
  Solution: Select an RPA platform that offers reliable exception handling and quick adaptability to changes in the application landscape.
• Challenge: Implementing RPA can introduce new quality assurance challenges.
  Solution: Rigorous pre-implementation testing and ongoing monitoring can help maintain quality.
• Challenge: Handling sensitive data poses a privacy risk.
  Solution: Make sure your RPA tool complies with data protection regulations like GDPR and has features to anonymize and secure sensitive information.
• Challenge: Sometimes RPA can lead to over-automation, where the maintenance of bots becomes cumbersome.
  Solution: Regularly audit and assess your RPA implementations to remove redundant bots and streamline processes.
• Challenge: Team members may be reluctant to embrace the new technology.
  Solution: Conduct comprehensive training and offer ongoing support to ease the transition. Regularly collect feedback for continuous improvement.

Robotic process automation is a transformative technology that allows businesses to automate repetitive tasks, streamline operations, and free up human capital for more strategic, value-added work. From bolstering security to offering rich analysis and exception handling, RPA provides a range of features that can help companies break free from the shackles of inefficiency. Unfortunately, there are obstacles that can stand in the way of effective RPA implementation.

ServiceNow, the leader in IT management, provides the solution: RPA Hub.  

Designed to accelerate automation and simplify workflows, RPA Hub offers a centralized management hub to orchestrate and manage your bots. It features:  

• A user-friendly desktop design studio
• Easily configurable robotic flows
• Native integration for seamless task automation
• A wealth of out-of-the-box components to help make your hyperautomation initiatives a success.

ServiceNow Workflow Data Fabric takes things even further, creating a secure foundation for scaling RPA. It connects structured, unstructured, and streaming data across your business without duplication or complex integrations. This enables RPA bots to interact with accurate, real-time data, improving task execution and effectively eliminating errors. Workflow Data Fabric also brings together tools like Process Mining, and Boomi API Management, empowering teams to identify inefficiencies, automate across legacy and modern systems, and manage compliance more effectively than has ever been possible. Ready to extend the reach of your RPA strategy? Explore how ServiceNow Workflow Data Fabric can help you manage bots, improve data access, and accelerate automation at scale. Request a demo today!