Robotic process automation (RPA) is the creation and deployment of software ‘bots’ designed to learn, mimic, and execute business processes.
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’s 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’s 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 this includes the following:
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:
Although RPA robots are designed to mimic human behavior, there’s 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.
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’s 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.
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.
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.
As previously stated, RPA bots don’t get tired, and they don’t 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.
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.
Because RPA takes the position of the user, rather than having to interface directly with system back-ends, it may be integrated with essentially any platform. This allows businesses to freely invest in and employ RPA, without having to worry about whether it will function with their already-established systems. At the same time, RPA empowers businesses to unlock the value of trapped legacy data in systems that were previously inaccessible.
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 models and natural language processing, and more. This makes it possible to automate not only repetitive tasks, but also higher-order, cognitive ones
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:
Organizations must first Identify and fully define their vision for incorporating RPA. This 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 hyper-automation 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.
The next step is to assign leadership roles, with the two most important being RPA sponsor and RPA evangelist. The RPA sponsor is the most 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.
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.
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.
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.
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.
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.
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:
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