Robotic Process Automation vs Machine Learning
Robotic Process Automation (RPA) is being integrated with Machine Learning (ML). They can be mixed up and used interchangeably especially if one person is not into technology and has limited knowledge of the true definition of these two. Knowing that RPA is different from ML is one of the most important things a person should know. Let’s try to get a better understanding and differentiate these technical terms.
Let us first talk about RPA or Robotic Process Automation or “bots”. Bots can be programmed to do basic, repetitive tasks across applications. Bots have the ability to launch and operate other systems. interpret, trigger responses and communicate with other systems in order to perform a variety of repetitive tasks. RPA is process-driven. Meaning, it works by being given pre-built processes or instructions, rule-based, and usually requires the end user to interact with more then one line-of-business system.
With just a click, you can accomplish a task as it is pre-programmed and is designed to follow a rule-based path. Some may speculate that there will come a time that some areas of work won’t need humans. But that won’t happen. It will definitely make our lives easier but it can’t eliminate human intervention. Automation is intended to make people more productive and effective at their jobs.
Some commonly used examples of RPA are call center operations, data migration or entry and forms processing, onboarding employees, automated help desks, claims administration in healthcare and insurances, credit card applications, online scheduling systems, and many more.
Now let’s discuss Machine Learning. Unlike RPA that is process-driven, Machine Learning along with Artificial Intelligence is data-driven. It can process data and learn from data on its own, without any supervision from programmers or anyone. It has similar traits but it is not entirely the same. Its primary objective is for a technology to mimic human operations. It does not require programming from humans and is designed to be self-sustaining.
Observe your Spotify, YouTube or any other account. Everyday, it creates a playlist and recommends it to you. Recommendations are based on your previous browsing. It analyzes what you usually pick and creates a list of the videos/songs that you may like. This happens because of ML or machine learning. Through data input and certain commands, the computer is enabled to learn to identify certain patterns and to distinguish between them.
Another common application of Machine Learning is the detection of spam messages in our email. Within the scope of spam detection, the data contained in the e-mails is analyzed and categorized. The "spam" and "non-spam" patterns are used in this respect. If an email is recognized as junk mail, the program learns to identify spam mails even more efficiently.
About Formulated Automation: Our mission is to make the workplace a more meaningful environment for the entire workforce. We achieve this by automating robotic work. This frees up humans to do human work. If you find your company does the above, reach out, and let’s see if automation can deliver value to your organization.
