Introduction to RPA Technology

RPA Technology A Deep Dive

When I graduated from my university, there was a lot of noise for new technologies and RPA was among them. RPA or Robotic Process Automation is one of the widely used technology in today's world. Even though some people think little of this technology which seems fair on some ground but let's not just jump into this quiet yet,

Robotic Process Automation has multiple definitions few of them are mentioned below:

"Going from simple, back-office task automation to scaled automation to handle time-consuming business processes can be a challenge."

Robotic process automation (RPA), also known as software robotics, uses automation technologies to mimic back-office tasks of human workers, such as extracting data, filling in forms, moving files, et cetera. It combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. By deploying scripts which emulate human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems.

Now, in more simple terms,

Robotic Process Automation simply implies to get robots (not the terminator kind) but virtual machines and servers to perform a certain process or series of steps repetitively to achieve a target. We can complicate this with deep functionalities and critical grammar but in essence, RPA revolves around automating manual human tasks to save time, resources and money.

RPA Vs Artificial Intelligence

RPA faces criticism from AI developers as they distinctively consider RPA as a very rigid and directed flow of actions which in effect is not what artificial intelligence is about. The AI developer tends to construct and mimic the human behavior of learning and judging outcomes. Using machine learning algorithms and complex data sets they train a computer to make analytic and accurate decisions, on the other hand, RPA developers design an optimum process flow to do something redundant and time consuming.

Why RPA?

Well, it's crucial to know that AI developers are not wrong, RPA is rigid in its ways and tends to have a more directed simplistic flow compared to AI automated machines but it cannot be denied that many of our jobs can be automated using these simplistic techniques. Though complex learning designs are capable to make better judgments after learning basic rules from huge sets of data they still face accuracy issues from time to time and thus require human monitoring. And even though we are using such advanced technology these days the accessibility and discrepancy between the real time workflow and machine oriented workflow are still pretty high. What I mean is that even after having such smart systems at the touch of our fingertips we still are pretty new to automated design of workflow. There are so many tasks which are still accomplished using primitive methods which can be hugely benefited by RPA 

Many multinational corporate conglomerates are working on this technology because a potential exists in the market for it now. Many business forms are shifting towards it to reduce costs and thus promote digital management and accomplishment of goals. Though there are many limitations to RPA that we do need to modify in the next versions so as it doesn't go obsolete in the future but for now it's a jumpstart to the new world we want to achieve.

For some it might seem like a tool accomplishing a task using a flow diagram but the logical ability that goes in the background to achieve this little army of virtual machines to accomplish tasks in an integrated environment is exciting to work with and complex enough to get lost in its own way. 

Popular RPA Tools

There are many tools available in the market for developers in RPA,

Including few of them down below:

1. UI Path

  • Open source
  • Huge community available
  • It includes scrapping solution

2. Automation Anywhere

  • Paid Tool
  • Offers scriptless automation
  • It combines RPA, AI, ML, and analytics assisting organisations in scaling business process automation

3. Pega

  • Paid Tool
  • Provides cloud-based solutions or services only
  • Execution data stored with an event-driven approach

4. Blueprism

  • Paid Tool
  • Easy implementation
  • Wide Community

5. Nice Systems 

  • Empowers desktop Analytics and machine learning
  • Optimal business processes to automate with accuracy
  • Paid Tool

[check out references to know more about these]

Please note some of these tools are open source while others are paid products each having its own features and limitations.