IPA vs RPA – What’s the Difference?

There’s nothing the tech industry loves more than a three-letter acronym. 

But when you’re looking for ways to automate processes to improve efficiency, lower costs, and free up more time for your teams, it can make things hard to navigate. Should you be looking for robotic process automation (RPA) or intelligent process automation (IPA)?

As it happens, it’s not quite as simple as IPA vs RPA, but more about understanding how the two technologies are related. 


What is Robotic Process Automation?

RPA is a technology that makes it easy for you to build and manage software robots (or bots) that can act like humans working at a computer. These robots can understand what’s on a screen, identify data, and take a wide range of actions that would otherwise have to be completed by a person such as filling out forms or scraping data. 

The advantage of using RPA bots (instead of humans) is that the tasks they are used to complete are mundane, repetitive, and time-consuming – which frees up your team to do the more valuable, interesting, intelligent stuff that we can’t leave to machines.

It’s a really important part of business process automation – but it’s not the only thing you need to maximize efficiency. 


What is Intelligent Process Automation?

Intelligent process automation includes RPA – but goes much further. IPA also incorporates digital process automation (DPA) and Artificial Intelligence (AI) analysis to enable your RPA bots to execute tasks more efficiently – as well as helping all the humans in your business too. 

Essentially, IPA adds in the data layer. So, where RPA automates specific tasks and actions, DPA acts as an orchestrator, automating the flow of data between humans and bots across your organization. It connects all the people, applications, devices and disparate pools of information across your business on one secure platform. 

And once the data is all in one place, you can use AI technology to glean deeper insights, allowing smarter, quicker decision making – which can either be used by your employees to enhance their day-to-day performance, or for programming your bots. 

Discover how pairing Bizagi's Intelligent Process Automation platform with RPA technologies can accelerate your automation efforts.

What’s the difference between RPA and IPA?

The difference between Robotic Process Automation and Intelligent Process Automation is that RPA is a component of IPA rather than an alternative to it. RPA is used to perform repetitive tasks with minimal variation whereas IPA (RPA + DPA + AI) is used to tackle more complex end-to-end processes. 

RPA is rules-based and applies rules stipulated by humans to perform a task, for example, sending an automatic reply to an email. IPA, meanwhile, incorporates AI technologies such as machine learning and so it can perform tasks that require judgement and analysis (a loan approval is a good example), without the need for human intervention. Plus, IPA is capable of handling exceptions and continuously learns from patterns in data to improve performance.

Additionally, RPA can only deal with structured data whereas IPA can handle both structured and unstructured data.

Although RPA alone can do wonders for productivity and cutting costs in a short timeframe, IPA’s extended capabilities provide insights into process improvement opportunities across the enterprise enabling you to transform the way you work for long-term success.

How does it work in practice? 

Here’s how Bizagi used IPA to help Deutsche Post DHL Group automate their business processes to improve user experience for their employees and their customers. 

They needed to orchestrate processes across their enterprise including their intranet, RPA, and a complex stack of technologies and applications, including SAP, Oracle, and SharePoint.

IPA was used to fill the gaps between those systems and make sure they were all connected. The project began with a proof-of-concept by automating their Duty VAT Billing process, working alongside other tech providers like ABBYY (for capturing information from paper documents) and UiPath (for task automation) to make sure the process of billing VAT on shipments was automated end-to-end. 

Though this was an ambitious and complex project, it was also one that would show immediate results. The process was previously entirely manual, but within six months, 95% automation had been achieved, making tangible time and cost savings. 

This is just the short version of the story, so you can read the full case study, including how they automated other processes, including vendor master data management. 

DHL tech stack.PNG