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Business Process • Automatization • RPA
Last week, we wrote our first piece on RPA. In that article, we explained the basics: what is RPA, how does it help businesses, and how to determine if it’s a good solution for the process you’re looking to optimize.
RPA has significantly grown in popularity over the last 12 months. Enterprise-level businesses from various industries have started to invest heavily in this tech and, as the above-linked study suggests, their investments are starting to pay off. Over 30% of the businesses that were part of the AI Multiple survey reported significant boosts in productivity and compliance in the last couple of quarters.
This data alone proves what we have been talking to our customers for a some time - if executed correctly, RPA bots possess the power to automate mundane tasks and banish unnecessary manual work from your team’s plate.
However, selecting which processes to automate and how is not simple. It takes some deeper thought to figure out what processes are a good fit for a bot and what needs to stay under a human. To help you make smarter decisions when it comes to using RPA bots, we decided to create a checklist of key factors you need to consider before you give your development team the green light.
As we explained in the previous article, robotic process automation, or RPA in short, is a technological solution that enables seamless building, deploying, and managing of software robots that replace human actions interacting with digital systems and software.
The main business benefit of such a solution is to eliminate tedious tasks from the day-to-day life of people in a company and free them up to focus on their areas of genius.
RPAs are built to increase productivity, speeding up work, eliminating unnecessary human errors from processes, cutting costs down to size, reducing risks, and the stress from the talent in the company.
For maximum efficiency, the jobs that RPA should replace have to be rote and low-level. And by rote and low-level, we mean pre-defined and structured, typically built around filling in electronic forms, processing transactions, or sending messages.
RPA is a perfect solution for data entry, billing, order management, HR onboarding, and other areas that require lots of repetitive work.
Robot process automation is huge in the financial sector. Banks use RPA for loans reviews, invoice processing, and customer checks. Sales organizations use RPA to automate quotes and invoices. Businesses in the insurance sector use RPA to speed up claim adjudication.
Yes, at this point, robot process automation sounds like a solution for literally everything, but it’s important to first dive deeper into the subject before we begin to think about it as our savoir.
It’s important to keep in mind that RPA bots are not all-knowing and all-powerful. The level of intelligent you can expect from the bots has a limit. There have been some disappointments when people that to over-rely on the bots.
If you want to keep your bots usable, you have to properly plan and execute rollouts. If you want to avoid failed RPA deployments, you need to be clear about what you want to automate before you opt for a RPA product.
Every single RPA solution uses its proprietary file formats.
Yes, all of them bring benefits to the table, but you need to understand the pros and cons of every single one.
You have to think about all the limitations and concept proof your “favorites” before you go for a rollout. If you make a mistake and go down the wrong path, fixing things later is going to be painful and expensive.
Your no.1 objective here is simple:
Once you understand how to process of creating an RPA bot should look like and how to full-proof it, there are still a couple of other factors you need to pay attention to when deciding whether or not to invest in the development of a specific RPA solution.
How will the setup process look like? - To make this work, you should focus on making it super easy to set up your bot for different personas. Your employees shouldn’t waste time learning how to handle a complex implementation process. To maximize everyone’s time, the installation process should come in a point and click form.
What does the learning curve look like? - It should be relatively easy to use the bot. It should function on a drag-and-drop principle or something equally simple.
Does the bot work in a way that the user needs it to? - Some bots make sense only if they run on-demand (attended) when a business user needs them to perform a well-defined task—for example, "turn this graphic into text and put it on the clipboard." Other bots make more sense if they run in response to an event (unattended), such as "perform due diligence on each loan application submitted from the website." You need both kinds of bots.
Does the bot have machine learning capabilities? - Your bot needs to be able to find the required numbers, and return them to the user. Some vendors and analysts call this hyper-automation, but the fancy language doesn't change the functionality.
Is it possible for a human to review the bot’s work? - Yes, RPA automates processes with machine learning and eliminate human error from the equation. However, a piece of software can also make mistakes. When you build such a solution, you should make it possible for people in your team to submit cases for review.
Thank you for taking the time to read our latest blog post in its entirety. As you can see from everything written above, the success of your RPA implementation will depend on identifying the highest-reward processes and tasks for automation. For instance, if the highest-reward process for your businesses is to build a stronger customer service, make that your north star and ideate what processes under that part of work can RPA bots automate/improve for you and your team.
Our biggest advice when tackling with RPA is to focus heavily on testing. You have to foolproof your investment. If it turns out the RPA solution is not a 100% good fit - don’t be afraid to pivot. But pivot early! and you need to switch, you’re in for a world of hurt. Yeah, you will lose momentum and put more pressure on your development team, but by doing this - you’ll avoid bigger problems. Problems that will cost you a lot of time and money to fix.
