The Present and Future of RPA for Devs
How robotic process automation succeeds today and how to stay successful in the future.
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We've touched on what goes into building a good RPA flow, so let's pull back a bit and look at the technology as a whole. Again, we're going to be tackling this from a developer's point of view, and again, we're going to rely on our friends from UiPath's community to help out.
(By the way, this is going to be a useful, but higher-level look at RPA. If you're looking for more of a tutorial, check out our Refcard Getting Started With Robotic Process Automation.)
The Changing Landscape of RPA
RPA certainly doesn't have a monopoly on being a changing technology, but that doesn't mean it isn't growing and adapting fast. With that in mind, let's look at some recent trends a UiPath community member (and executive RPA lead at that!) has experienced and what they see on the horizon.
- The merging of RPA and AI: "One of the biggest trends I see is the combination of AI and RPA in many automation solutions we build today," one UiPath community member said. "The solutions we create today are more dynamic and have a lot of decision points that require AI and machine learning." And as solutions get more complex, customer expectations just get higher. Everyone wants more complicated, dynamic processes to be automated. The only way to stay on top of those demands is to always be learning.
- The merging of RPA and analytics: Everything boils down to data. As RPA grows more and more closely aligned with AI, ML, and NLP, automation is being used for large-scale data analytics. Data analysis tools (e.g., Alteryx) make that even easier. "Soon, we will be working on more state-of-the-art technologies and RPA to automate more complex processes more efficiently," that same community member said. "It is always important to stay in touch with modern technology trends and learn innovative technologies and programming languages such as Python." Again, always be learning.
- Modernizing legacy apps with RPA: Another trend the community memberr has seen is clients asking for old or outdated applications using process mining, task mining, and RPA. "So, today, it isn't just about automating a process — it's also about changing, upgrading, and standardizing existing processes using state-of-the-art technology."
Ideal Use Cases for RPA
If you read the last post, you'll remember the line:
RPA isn't the solution to all problems.
Not every process is a good candidate for automation. You need to evaluate each process you come across to understand its automation potential.
Here are some excellent questions you should ask each time you examine a process.
- Is the process rule-based?
- Do we handle digital and structured/semi-structured data?
- Do we have standardized input for the process?
- Does the process have a low exception rate?
- The process should not undergo any change soon?
- How complicated are the decision points in the process?
Those questions will help determine a process's automation potential. The more the answers point toward standardization and automation, the better a fit RPA becomes. With that in mind, the Finance industry tends to lend itself very well to RPA, specifically tasks involving accounts receivable, account payable, invoice processing, etc.
When Shouldn't You Use RPA?
Well, I'll say it again:
RPA isn't the solution to all problems.
Sometimes, a process just can't be standardized or automated, at least not in any meaningful way.
One community member and executive RPA lead recalled connecting with a client to analyze a process. One of the process's inputs was a highly complicated diagram with a lot of information in it. Except the diagram didn't have a standard representation. It varied based on the requirements. The client needed to extract the required information and populate a couple of downstream apps just to send out purchase orders.
"The input was so complicated, and even with AI, it's very difficult to extract the data, as it requires a lot of human experience and decision-making," they said. Those kinds of processes just aren't doable with the tech available today.
Keeping Users Calm
One of the big concerns you'll probably run into when building RPA flows is users worrying about "software robots" or "digital workers" taking their jobs. [Insert South Park .gif here.] People worry they'll be automated out of a job or will have to do drastically different work to stay employed. There's also just the fact that humans are creatures that love routines, so having to change that makes people uncomfortable.
To get ahead of that, the UiPath community recommends holding one or several awareness sessions before even starting the project. The goal is to educate users about what RPA is, what it can do, and why they shouldn't be afraid for their jobs.
Yes, I have encountered this fear in users. They think that introducing software robots will take out their job. The users also don't like to change the way they work as they are used to a process—they're comfortable with.
"The awareness session usually includes the details about RPA, how it's applied to their projects, how processes are standardized, what they can do to help the automation initiative, and how their daily tasks will change after implementing the solution," the community member said.
So, perhaps unsurprisingly, the solution is to treat users like humans, take their concerns seriously, and explain as much as possible how they might be affected by the changes. It's a bit of extra work, and you'll probably need a bit of help from the client company, but it goes a long way toward making users' lives easier (and getting repeat business).
Combined with my other article, you should now have a solid understanding of what goes into RPA — not just a high-level look at the technology, but practical advice for working with it and your clients/users. You should also know when RPA isn't going to work (or at least isn't worth the effort to make it work) and some questions you can ask to gauge a project's prospects. Lastly, you should also be positioned to see how RPA is changing and how to position yourself for future success in the field. So, good luck, and good automating!
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