Before getting into Intelligent Process Automation (IPA), it’s important to first define what is RPA: Robotic Process Automation (RPA) refers to the use of software bots to carry out repetitive, mundane, and frequently high volume tasks in the workplace. These are typically tasks that have to be done in order for a business to function effectively, but which no-one relishes doing.
Think about scraping data from a variety of sources and software packages, then compiling them into a spreadsheet and sending them to the correct stakeholders in a business. Explaining that data and figuring out what to do with it may very well be a valuable job, but the simple (if time-consuming) act of copy and pasting it into a new document probably isn’t anyone’s favorite activity.
This is where RPA enters the picture. These are software tools that are able to perform simple, rule-based tasks at scale, rapidly, and without error. In doing so, it frees up human workers to carry out other, more valuable tasks, enhancing productivity and job satisfaction.
RPA has become an increasingly present part of many workplaces over the past decade. But there’s another new automation solution on the scene: IPA. Does its appearance spell the end of RPA just as it’s starting to really gain momentum?
Meet Intelligent Process Automation
The chief difference between RPA and IPA can be summarized by the latter’s use of the word “intelligent.” RPA tools are designed to follow rule-based processes involving structured data. The tasks RPA excels at may be time-consuming for human workers, but are nonetheless simple and repetitive. The time-consuming part relates more to the frequency and quantity than the difficulty carrying out these tasks.
IPA, meanwhile, leverages artificial intelligence and machine learning algorithms to take RPA automation to the next level. Unlike RPA, IPA can deal with semi-structured or unstructured data — meaning data that, while having an internal structure, is not stored in a structured format such as a database. Using cutting-edge cognitive technologies, IPA can deal with more complex tasks. It can use technologies such as Optical Character Recognition (OCR) or Natural Language Processing (NLP) to perform tasks that previously would have required a person to be in the loop.
Automating more complex tasks
This is not about replacing the higher level, value-added tasks that RPA frees up human workers to spend time on. However, it does allow these tools to carry out more complex work. Unlike RPA, IPA can also learn and adapt to new information it learns along the way. It can additionally deal effectively with scenarios based on edge cases or exceptions to rules. This means that it can help adapt to different workflows and learn to carry out more complicated, human-like tasks.
The best way to illustrate the potential power of IPA solutions is with some example use-cases. For instance, in the insurance industry, IPA could be an invaluable tool within a claims department by scraping data from claims forms in a variety of formats (both completed digitally and scanned documents) and then entering this in the department’s Customer Relationship Management (CRM) system. This is a task that, currently, might take a claims department hundreds of hours each year entering data. It may be repetitive work, but it’s also complex enough that it can’t easily be handled by traditional RPA.
Does IPA spell the end of RPA?
In short, the answer is no. There’s no doubt that IPA is smarter technology than RPA. Over time, it is clear that technological advances mean that RPA tools with the added power of AI and machine learning capabilities will grow in popularity. IPA is able to help automate in scenarios in which traditional RPA is not, enabling businesses and organizations to automate processes that previously seemed un-automatable.
But viewing this as a competition, whereby in order for IPA to win, RPA must lose, is a mistake. These aren’t competing formats so much as one is the next iteration of the other. It’s like comparing the newer iPhone 12 to the older iPhone 6. Is one model better than the other? Of course it is. But they’re both part of the same technological throughline, and, while one might be superior, there’s still plenty that can be done on an iPhone 6 — depending on what it is needed.
Looking long and short-term
In the longer term, IPA can benefit organizations by helping them automate increasingly complex tasks according to a more adaptable workflow. This doesn’t negate the usefulness of modern RPA today. Many tasks can be efficiently automated using the simple, step-by-step processes involved with RPA. Organizations can begin by automating the repetitive, simple tasks they wish to hand over to machines, and then scale efforts to attack other problems and tasks as well.
Think of it a bit like picking fruit on a tree. There’s plenty that can be picked from lower branches without the need for a ladder. However, once these have been picked, a ladder will allow you to pick the fruit from the higher, harder-to-reach branches. By consulting experts in RPA and IPA, businesses can get a good idea of which tasks can be automated — and how they should best be automated — in order to maximize return-on-investment. The results can be a game-changer for businesses, both in the short and long-term.