Robotic process automation (RPA) technology uses software bots to automate simple, high-volume, and repetitive tasks that would otherwise require manual labor by humans. You’ll often find RPA assisting with back-office work, such as data entry, and improving customer experience, for example, by routing a customer support inquiry. One benefit of RPA bots is they work non-stop, based on a predefined schedule or trigger within a workflow.
Automating routine tasks with RPA can not only save businesses time and money but also reduce errors. What other benefits can RPA deliver? Perhaps most notably, RPA can free employee time for more innovative work—for example, digital transformation projects that improve customer satisfaction. Additionally, leaders can realize talent retention benefits when people are freed from mundane work and put on more forward-looking projects.
Speed is often the pain point that drives organizations to investigate RPA. Using RPA to automate certain tasks within workflows can speed up business processes and increase team agility. But RPA can also prove helpful in connecting older, legacy systems when no application programming interfaces (APIs) are present.
RPA has its limits, however, especially when the workflow hits a point where you need a cognitive decision. That’s why RPA proves most powerful as part of a broader automation strategy that includes other automation software and techniques. Let’s take a look at RPA examples, typical benefits, how it compares to related technologies, such as artificial intelligence (AI), and how RPA fits into your broader tool set and strategy for business process automation or hyperautomation. It’s important to remember that RPA is an automation point player, not a holistic automation solution.
Let’s take a look at how RPA works for teams and organizations. People can program RPA software bots with data that instructs them to complete tasks based on the presence of specific conditions or triggers. For example, think of all the data that must be routed around an organization’s accounting, inventory, billing, and logistics systems as soon as a customer places an online product order. Bots can fetch the buyer’s information to populate a confirmation email with details regarding estimated taxes, delivery date, and loyalty perks, among other pieces of data.
In terms of visual interface, many RPA tools let you record actions and then drag and drop them into workflows. The actions and workflows are then reusable by other people and teams, which paves the way for faster software development and better collaboration.
RPA does not have the visual appeal or cool factor of robots that do human jobs, like deliver room service items in a hotel or medicine in hospitals. But RPA software bots, running quietly in the background, can significantly change how teams work in functions including customer service, finance, human resources, IT, and many more.
One Gartner study found that in modern accounting departments, 30% of a typical employee's work could be avoided by implementing RPA.
RPA bots can help teams improve not only speed and efficiency but also accuracy. As an organization’s data sets grow, legacy technical debt becomes more and more costly. People develop workarounds and tricks to get around their problems. Think of all the places in your organization where people are still using spreadsheets, cutting-and-pasting to ease a pain point in a workflow. RPA bots can facilitate faster, more accurate data flow between people and teams.
To get the best results from RPA, explore using it as one of several technologies in a broader process automation strategy. Business process automation tools that often complement RPA include artificial intelligence (AI) and intelligent document processing (IDP).
Artificial intelligence applications can do simple cognitive decision-making, without people being involved. More nuanced AI applications also utilize machine learning to improve over time, using experience and data. Intelligent document processing can be used to automatically classify and extract information from paper-based forms and turn it into structured, usable data.
These automation tools can work alongside RPA tools. For example, many organizations want to get more value from their customer data using AI solutions that get smarter over time as data sets get bigger. But RPA technology does not learn as it goes. In this example, a combination of AI and RPA is best. AI can deliver new insights, and then RPA can carry out actions your team designates based on those insights.
At the same time RPA improves speed and accuracy throughout an organization, it also relieves people of the tedious parts of their jobs. As noted earlier, that’s good news for leaders worried about talent turnover, which has been a particular concern since the beginning of the pandemic for many industries.
But RPA is not about cutting jobs from your organization: that’s a message leaders will need to stress as they prepare teams for the culture changes associated with RPA implementations.
“Once a process or task begins to require more advanced capabilities, such as cognitive decision making, RPA is no longer suitable on its own,” as Appian Product Marketing Director Michael Rahm wrote in a recent blog.
While RPA can eliminate drudge work for many people, you still need humans in the driver’s seat of processes. For example, you can free customer support staff from routine product return processes and give them more time to handle inquiries or escalations that require one-on-one help.
What is RPA used for? RPA best suits processes that are repetitive and high-volume. Let’s look at some examples of how organizations apply RPA to improve efficiency, speed, and team agility across several functions and industries:
RPA examples for customer service.
From returns processing to curbside pickup in retail settings, customer service expectations changed radically for many organizations during the pandemic. That’s one reason why customer experience leads the priority list for many leaders doing digital transformation work. Improved customer experiences lead to increased customer satisfaction and loyalty.
For example, RPA can play a big part in the workflow associated with onboarding a new customer. “Businesses have reduced the amount of time it takes to onboard new clients by as much as 90% (from 10 minutes to under one minute),” Forrester noted in “The Three Customer Service Megatrends In 2021: Post-Pandemic Customer Service Excellence.”
Consider these additional areas where you can use RPA to ease pain points in customer service:
Chatbots
Customer self-service
CRM integrations
Compliance and privacy
Complaint resolution
Meeting/Meeting room scheduler
RPA examples for financial services and insurance.
In the financial services and insurance industries, the competitive demand for speed and agility is fierce. Consider these areas where financial services and insurance organizations currently use RPA.
Financial services RPA use cases:
Loan processing
Same-day fund transfers
Account opening/closure
Customer lifecycle management
Building profit and loss reports
Building cash flow statements
Creating account statements
Distributing account statements
Insurance RPA use cases:
Appeals processing
Policy renewals
Customer self-service/contact center automation
Agent and broker channel automation (portals)
Agent lifecycle and performance management
Policy/Pension servicing
Underwriter case management
Complex policy quotation
What are the benefits of using software bots to do these types of tasks? As you can see from the RPA use case examples above, organizations will realize multiple RPA benefits beyond speed and cost.
For example, in life sciences organizations, RPA not only helps speed up the pharma development cycle, but it also helps global teams document processes in ways that ensure regulatory compliance. That being said, the top benefits businesses can gain from RPA typically fall into these categories:
Speed
Productivity
Accuracy
Employee satisfaction
Customer satisfaction
Compliance and risk management
Connections to legacy systems
Cost savings
How might RPA fit into your organization’s broader automation goals? How does it relate to other automation tools and techniques? For many businesses, RPA is one component in a larger business process automation (BPA) effort, which is often part of a digital transformation initiative.
Business process automation simply refers to tools and techniques that help organizations improve their workflows to be more efficient and productive. BPA tools and techniques may include RPA, AI, IDP, and business process management, among others. Business process automation may also be called digital process automation (DPA) or workflow automation. It’s the same set of automation tools and methods. (Analyst firm Gartner prefers the term BPA, while Forrester Research prefers DPA.)
But RPA does not suit every use case. And RPA on its own will get an organization only so far. As noted earlier, once you need a human to weigh in with a cognitive decision, RPA no longer suffices. Automating pieces of a workflow in isolation will get you quick wins, but it won’t solve the organization’s more complex process problems. For these, you’ll need a combination of solutions.
As we noted in a recent BPA article, “The more complex the process, the more dependencies that can arise. This in turn equals more documentation, chance for error, and often, technical debt. That’s where business process automation solutions that take advantage of both bots and AI, such as a low-code automation platform, can flip the script in terms of speed, accuracy, and other advantages.” (For more detail on this topic, read our related article: Business Process Automation (BPA): 6 Key Benefits.)
Also known as a hyperautomation tool, a low-code automation platform provides visual tools that let people sketch out processes as easily as drawing a flowchart. Pre-configured components representing workflow activities and automations can be dragged and dropped into a visual process model. Because these components are reusable for building future workflows, teams can gain agility—a key goal of digital transformation work. This also supports cross-functional collaboration.
In this kind of holistic automation approach, RPA plays a role, but it must be augmented by other tools and techniques where they fit best. Taking a big-picture view of your automation strategy will help you identify the best automation opportunities to create compound, long-term benefits.