By Some things are meant to be together: peanut butter and jelly, macaroni and cheese, Bonnie and Clyde, Mario and Luigi. I’m sure you thought of many others, but I doubt low-code technology and robotic process automation (RPA) crossed your mind. Their names don’t necessarily roll off the tongue, but when it comes to augmenting your digitization efforts, this tech team can’t be ignored. However, the tale of these star-crossed lovers hasn’t always been sweet. Before finding low-code, RPA felt incomplete.
RPA: The bachelor days
In 2000, the term RPA was coined1, but its technological roots of screen scraping and workflow automation date back to the 1990s. When RPA emerged in the automation space, there was lots of hype around it. A 2013 report predicted that RPA would be one of 12 disruptive technologies that could have an economic impact of $33 trillion per year by 2025.2
At the time, many businesses were just starting to seriously discuss automation and found that leveraging RPA could be the answer to improving efficiency and saving resources. Instead of making incremental updates to larger enterprise systems, businesses could use RPA to automate transactional processes.3
How to identify which processes should use RPA
Business leaders have since understood the value of task automation, and the adoption of RPA has continued to skyrocket. A recent study polled 270 business leaders and found that 66% of their companies would be increasing their spend on RPA by at least 5% in the next 12 months.4 The hype was true. But underneath the glitz and glamor and analyst praise, RPA secretly struggled on its own.
RPA roadblocks: Something was missing
As with most technologies, RPA isn’t the silver bullet for automation at scale. Though it had early adopters and is continuing to gain popularity as a digital transformation tool, companies have quickly realized some drawbacks when RPA is implemented on its own.
One shortcoming is that bots aren’t as smart as humans. And, while they can learn repetitive tasks, they rely on very specific guardrails to do their job. They can’t adapt to changing requirements or processes very easily, so organizations that implement RPA have to ensure that whatever systems RPA feeds into is providing clean, structured data.
To scale RPA, organizations need:
🔸Proper integrations
🔸Defined processes
🔸Structured data
The problem is, many organizations that have implemented RPA are still tying it to legacy systems. This causes friction, like figuring out how to integrate RPA with the older technology, and requires a skilled developer to troubleshoot—defeating the goal of automation.
Another challenge is that many large organizations still rely on manual and paper-based processes, which are error-prone and don't provide the clean, structured data that RPA needs. Despite these drawbacks, there’s no need for organizations to “rip and replace” their RPA investment; when paired with the right low-code solution, RPA becomes its best self.
The low-code love affair
Low-code platforms started gaining traction in 2014, when Forrester coined the term. Low-code platforms enable non-technical employees to develop digital experiences and/or solutions in a very short period of time, using a visual approach to development with minimal coding.
Without relying on business and technical requirements to be written and UX designs to be completed, low-code platforms can be spun up in days by knowledge workers to solve organizations’ complex processes.
If your organization has already invested in RPA, layering on a low-code solution can help you create an intuitive and personalized front-end experience while generating clean data to fuel RPA and task automation down the line.
The perfect match
Organizations that pair RPA and low-code platforms together accelerate their digital transformation and digital business initiatives. Instead of worrying about not having structured data for RPA to use, the low-code platform ensures clean data is generated so that end-to-end automation can be achieved. When RPA falls short, low-code takes the reins.
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The challenge |
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A hospital was processing patient data from spreadsheets and other paper-based processes that required a lot of resources to complete. Too much time was being spent keying data into its legacy systems from the spreadsheets and forms, leaving lots of room for error. |
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The RPA solution |
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RPA was implemented so that bots could take over the repeatable task of patient data entry into the larger hospital system. The hospital soon realized that RPA was only solving part of its process. It needed clean data, and employees were still spending a substantial amount of time verifying the patient data that went into the spreadsheet that RPA leveraged. |
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Layering on low-code |
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The hospital decided to implement a low-code process automation platform to ensure the data was clean from the start. An intuitive, front-end solution was created to capture patient data, with rules that flagged errors or omissions. The data was passed directly to the RPA bots who were able to enter it into the legacy system, saving hospital staff time and leaving them with bandwidth to better serve patients. |
While RPA and low-code aren't the most riveting dinner guests, they truly bring out the best in each other, like any good couple would. Automating processes with RPA is a good start, but RPA is lonely—and limited—on its own. To bring out the best in your RPA solution, consider pairing it with its perfect match: the right low-code process automation platform.
Sources
1 https://www.javatpoint.com/history-
3 Deloitte: The Robots Are Coming
4 Forrester, Jan. 2020: The Future Of Work Is Still Being Written But Who Is Holding The Pen?
