The buzz around Robotic Process Automation (RPA) and Artificial Intelligence (AI) has never been more popular than now. RPA and AI are the future. Some companies are faster than others to adopt these technologies but they are certainly making their way into the business world. They open a world of mind-boggling possibilities and yet, like everything else, come with their own pros and cons.
Here are the most important benefits and limitation of using RPA in fully operating organizations.
Advantages of Using RPA
Ensures error-free data collection
With RPA, the quality of data collected and sorted increases manifold, especially if the data is coming from various sources. RPA helps in tapping the information completely and correctly from all the varied sources, leaving no scope for gaps and errors. RPA has really helped improve data quality in the fields that require high accuracy.
Improved management
RPA helps centralize management, thus making it easier to monitor and control different processes and functions in an organization. You can manage, schedule and execute a lot of tasks just with the press of a button and be assured of quality and accuracy of the highest standards. It also helps organizations to utilize their human resources in a better manner.
Improved customer experience
RPA has been instrumental in improving customer experience. A key reason behind this improvement is systemizing processes where a clear cut process can be mechanized to perform on loop. It reduces response time and improves accuracy of the information shared by robots and software. Alongside, the resultantly freed human resources are being utilized to perform functions that cannot be managed without human interaction.
Limitations & Challenges in Adopting RPA
Getting the team onboard
RPA adoption comes with a notion of threat for employees currently working in the organization. It is a big challenge to get the entire workforce to a common level of understanding and assurance before you move towards automation.
Implementing RPA wisely
Deciding which functions to invest in is a tricky call. You want to systematize verticals that work on repetitive processes or organize processes that are not standardized yet.
All you need to overcome these limitations and challenges is farsightedness, complete knowledge and belief in what you are getting into with proper research & planning.
Genericcialisonline
My question to RPA vendors is how robust are your scripting technologies? Software testing of enterprise applications has used RPA techniques. For robustness RPA for QA has always required specialist QA engineers to develop and build tests for the tests. Early on even pixels instantiated on different Windows boxes due to different graphic card and resolutions could throw long running RPA test results into the bin. Later resource IDs behind the UI were used, more so after Microsoft provided Visual Test with Visual Studio/MSDN. Screen scraping came with web browsers, used by data scientists” to harvest content without API”s. Screen scraping is often fragile needing developer attention to fix scripts. Is RPA another technology for giant consulting firms with developers working alongside business people? Is RPA”s main value the ability to interface cloud-based AI? Is RPA another rat race like EDI?
Prateek Khurana
Hello, thanks for your interesting query.
Before I respond to the questions, I’ll like to share a brief about how RPA differs from old automation methods. Firstly, RPA is system agnostic, which is one of the key differences from the old automation processes. RPA enables several tangible and measurable values such as low investment cost, non-disruptive system integration, and rapid implementation.
There were generally two types of automation:
1. Screen scraping/capture
2. Product specific workflows
The modern-day RPA platforms are enterprise scalable. Processes are built by showing the robots what to do, step-by-step, rather than coding or scripting them, in exactly the same way as a human would use the end-user systems.
The tools also ‘recognize’ the fields or pop-up screens they are working with rather than relying on a location on the screen. The software robots used in RPA ‘read’ the applications using APIs or the operating system itself. It is part of the training of the robot where it is shown how to read the various screens it needs to work with.
As a result, RPA tools today are business tools for non-technical users. In the past, this was not the case, with many of the older automation tools being bespoke to a specific product, they could not easily be deployed on a large scale, and required specialist technical resources to setup and maintain them.
To sum it up:
· RPA tools today are business tools for non-technical users and flexible enough to work in different models
· RPA is system agnostic, making it interesting to work with any kind of technology and will easily work on cloud-based AI too
· RPA is far more advanced than EDI. In fact, RPA is the first step to AI. Cognitive learning and AI are a part of the immediate roadmap for all platforms
I hope this has answered your queries. If there’s anything else, I’d be happy to connect with you over email as well. You can write to me at prateek.khurana@gridinfocom.com