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Process Automation Types, Explained

Laurie McLaughlin, Appian
April 4, 2023

Are you confused about the multiple types of business process automation? You’re not alone. Automation tool vendors seem to have created more flavors than a contestant on Top Chef. Let’s get to the bottom of the differences between the various types of process automation and find out what they can and can’t do, in plain terms.

4 types of process automation.

Here’s a starting hint: Get ready for synonyms. In some cases, different analyst firms and tool vendors use different terms for the same ideas. That’s not a new phenomenon in tech, but it can be especially vexing when you’re trying to explain automation technology options to other people in your organization.  

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Let’s delve into how some key types of process automation stack up against each other.

1. Robotic process automation (RPA)

RPA may be the most widely-known, yet misunderstood, variety of process automation. Ask any IT leader: When many people hear “RPA”, they still think “job-stealing robots.” RPA in fact does not involve any Jetson-style robots, but it is automation technology that takes the place of humans doing repeated tasks inside software applications. 

RPA works best for  simple, high-volume, and repetitive tasks that would otherwise require manual labor. Think data entry or customer support request routing, for example. Unlike human beings, RPA bots work round the clock, according to a predefined schedule or a trigger within a workflow. RPA can speed up a workflow and improve team agility, to save time and money, and prevent errors.

However, RPA alone will only get an organization so far. It can’t make cognitive decisions. Nor can RPA learn over time, the way artificial intelligence (AI) and machine learning (ML) tools do. And RPA can’t solve the longstanding data silo problems that often get in the way of automating business processes. RPA works for automating a task or handful of tasks but not for automating an entire business process end to end, as many organizations learn when they try to scale automation efforts. RPA works best as one part of a broader automation strategy. 

Put another way, you can have the best cake mixer in the world, but on its own, that cake mixer won’t bake a dessert that will help you win on Top Chef. 

That’s the key takeaway: RPA is just one part of process automation.

2. Process automation

Process automation refers to tools that automate entire business processes, start to finish, cutting across multiple people, systems, and business functions. We’re talking about process automation examples like approving a mortgage application or onboarding a customer. A modern platform for process automation does this using not only robotic process automation (RPA) but also intelligent document processing (IDP), workflow orchestration, artificial intelligence (AI), system integrations, and business rules technologies.  

For IT and business leaders, the goals of process automation often start with speed: more efficient, effective processes help teams meet objectives faster. But process automation also gives teams new power to adjust to change, whether those changes are due to regulations, economic conditions, or supply chain issues. And that agility equals competitive advantage.

A strong process automation strategy and platform supports continuous improvement in three main ways:

  • Design: Quickly design and update processes with low-code development so that business users and IT teams can easily collaborate on process improvement.
  • Automate: Automate your process where needed with a unified platform for process automation that provides the best-fit technology or worker for the challenge.
  • Optimize: Optimize business efficiency with process mining. Leverage the insights necessary to identify the value of your digital solutions and where to apply your efforts for maximum benefit.

Why is process automation gaining popularity even amid economic uncertainty? The bottom line is that inefficient, broken, or non-compliant processes put organizations at risk for poor customer experience, fines, lost productivity, frustrated employees, higher costs, and weak competitive positioning. 

To learn more about process automation and how to implement tools and strategy, read our in-depth resource: ​​What is process automation?

3. Business process automation (BPA)

This one is easy: the terms BPA and process automation are pretty much interchangeable. BPA is a slightly older term, and one you will hear less often. But we’re talking about the same work and the same collection of automation technologies here. 

By the way, if you’re researching automation, you may also encounter a similar term: Digital process automation (DPA). Again, it refers to the same body of automation tools and methods. 

But these days, you’ll hear most analysts, vendors, and IT practitioners using the term “process automation” or “hyperautomation.”

4. Hyperautomation

Hyperautomation, a term made popular by Gartner, is synonymous with process automation. It includes the same variety of automation technologies, including RPA and AI. According to a recent Gartner report, "Hyperautomation refers to effective combinations of complementary sets of tools that can integrate functional and process silos to automate and augment business processes.”

As we noted earlier, you can explain the difference between “automation” and “hyperautomation” as a matter of scope. Going back to our cooking metaphor, a single automation technology can improve how you cook one dish, but hyperautomation can improve how you deliver the whole menu to a crowded restaurant.

Process automation: Parting tips.

Here’s the bottom line: Whether you call it process automation or you call it hyperautomation, the business results are clear. This set of technologies is delivering huge dividends to companies dealing with even the world’s most complex, regulated processes, like banking customer onboarding processes.

Process automation success requires the support of a strong data architecture. Look for 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. Users interact with the fabric view; the data stays in its source systems. Data fabric centralizes data management for improved security and compliance as you scale automation, even for data silos associated with legacy systems. 

For more advice on tool selection, read our related article: Process Automation Tools: 4 Questions to Ask.

[ Want to learn more about how to succeed with hyperautomation? Get the Gartner report: Gartner® Emerging Technologies and Trends Impact Radar: Hyperautomation Report ]