Skip to main content

Business Process Automation (BPA) vs. Robotic Process Automation (RPA): What’s the Difference?

Laurie McLaughlin, Appian
April 12, 2023

Business process automation (BPA) refers to the use of computer systems and software to automate business processes or tasks. These days, many people simply refer to BPA as process automation: a set of tools that automates entire business processes, end to end. Robotic process automation (RPA), on the other hand, is a single part of a process automation toolset. RPA fits into a process automation strategy by automating repetitive tasks within a process. Data entry and customer support routing are two common examples of processes that use RPA.

Business process automation (BPA) vs. robotic process automation (RPA), explained.

IT and business leaders will certainly encounter confusion about BPA vs. RPA. Some people will need education to get past the common misconception that RPA, BPA, and process automation all mean the same thing and refer to the same business process management tools. The truth is, RPA tools go only so far on their own. Here’s some practical advice on explaining the terms and comparing the technologies.

[ Learn how to successfully implement end-to-end process automation strategies. Get the Process Automation Guide. ]

 

Where does RPA work best? 

RPA does its best with task automation, either for individual tasks or a small group of tasks. RPA can be thought of as software robots, or as some people like to say, digital workers, that take care of work that people would otherwise have to do. RPA bots work around the clock, on a schedule, or according to pre-set triggers in a workflow. RPA can also be helpful for connecting legacy systems where no APIs exist. 

RPA is most effective for:

  • Tasks with few variations or exceptions.
  • Repetitive, high-volume tasks.
  • Consistent, rules-based tasks. 
  • Tasks in mature, well-defined processes. (If systems and processes change often, you’ll need to make frequent changes to the RPA workflow, which defeats the purpose of letting it run on its own.)
  • Tasks with structured data and readable inputs.

What does RPA look like in action, in business functions from accounting to HR and beyond? Some common examples of where companies apply RPA are reconciling transactions, billing, and customer service. For a closer look, see our related article: 6 RPA Real-World Examples.

[ Want to learn more about automation strategy? Get the Gartner® report: Beyond RPA: Build Your Hyperautomation Portfolio.]
 

Where does RPA fall short?

RPA can’t help an organization solve challenges that demand content extraction or email classification. RPA can’t make cognitive decisions or learn over time the way AI and machine learning technologies can. Most importantly, RPA can’t automate a complex business process, such as managing the customer lifecycle in banking, from start to finish; these processes cross people, departments, and multiple systems and sometimes require human intervention. Indeed, many organizations learn the limits of RPA when they try to scale automation projects widely across the enterprise but hit capability roadblocks or data silos. That’s why a broader process automation strategy is needed to automate complex business processes like onboarding a new customer. 

A modern platform for process automation has technologies including robotic process automation (RPA), intelligent document processing (IDP), workflow orchestration, artificial intelligence (AI), system integrations, and business rules. And a comprehensive platform will be able to escalate tedious tasks or exceptions to human employees when needed. Because process automation needs the support of a strong data architecture, you will also want to seek out a process automation platform with data fabric capabilities. A data fabric connects data sets across disparate software systems, whether they’re on-premises or in the cloud, ending data silo headaches and improving security and compliance as you scale automation. A process automation platform also offers flexibility to add and orchestrate future automation tools and gain new capabilities, such as natural language processing (NLP).

For more on process automation and how to implement tools and a strategy, read our in-depth resource: ​​What is process automation?
 

Digital process automation vs. robotic process automation.

In researching forms of automation, people in your organization may also come across the related term “digital process automation” (DPA). DPA refers to the same collection of technologies as process automation, intelligent automation, or business process automation and is often part of broader digital transformation efforts. 

Analyst firms have used various terms to describe this kind of toolset over the years; the most common terms right now are process automation and hyperautomation. And RPA, again, is one tool in this more holistic approach to automating entire workflows.
 

BPA vs. RPA: Key takeaways.

Remember these essential facts about how to explain and compare these automation technologies as you shape your automation journey:

  1. BPA is for end-to-end automation. BPA tools, also known as process automation or hyperautomation tools, automate an entire business process, end to end. 
  2. RPA is one of the multiple automation solutions included in a modern process automation toolset. RPA automates repetitive, manual tasks. 
  3. A platform for BPA, also known as process automation, can unify automation tools. Using multiple process automation technologies that don’t work well together can create islands of automation. This creates isolated wins followed by substantial challenges as you try to scale automation across the enterprise. A process automation platform can solve that problem, unifying work and cutting through data silos.
  4. Look for an automation platform with an orchestration layer to coordinate work between automation tools and seamlessly pass off tasks between people and RPA bots.
  5. A process automation platform delivers a much wider set of benefits in terms of efficiency, resiliency, accuracy, and scalability than using RPA alone. 

Want to learn how process automation and data fabric help organizations reach their automation goals? Get the eBook: The Data Fabric Advantage.