What Did We Do Before Automation Technologies Like RPA?

October 19, 2020

Though it is a well established (and billion-dollar) industry today, Robotic Process Automation, or RPA, is still relatively new. RPA tools originated in the 2000s with the world of automated system testing.

In 2020 it's hard to imagine a business with no automation whatsoever. For example, how archaic does it feel to have to do your expenses manually? And then, to make it worse, you have to wait two weeks (or more) until the finance department manually processes them for you to get your money back. No, thanks!

In this article, let's take a brief walk down RPA- memory lane. We'll review common mistakes and see how the world of automation has evolved.

Why does RPA exist?

RPA software exists to save money and time, streamline business processes, avoid human errors, automate data entry, and repetitive work. Essentially, it replaces work that can make humans feel like robots. Ultimately, it exists to make businesses more efficient. The benefits of RPA, and modern automation software in general, provides incredible cost savings and efficiency in business operations.

What were the business efficiencies before RPA?

A common practice was to outsource teams to another part of the world. An example of this is the IT support team for a large global company moving to a different country. While it saves money initially, it isn't without problems. These issues include language barriers, lack of control, a new system for employees to learn with countless teething-problems, and a high personnel turnover at the outsourcer site.

Due to the inconvenience of a team being outourced and on different time zones, tasks generally take longer to complete. Hidden costs are then manifested as ‘lost time’ and once the issue in hand is resolved, it may as well have been given to specialist in the HQ office. Companies then started using RPA to take back control and have more flexibility over their operations.

Common mistakes to avoid/Learning from previous mistakes

An EY study from 2018 states that the initial RPA failure rate is between 30-50%. There are several reasons for this:

  • Unrealistic expectations. As with any project, it's crucial for all stakeholders to align on the business problem to solve. Misalignment causes unrealistic and impossible expectations of the outcome.
  • Failure to integrate with an IT support team – a solution designed to help business efficiency could do the exact opposite if no one can manage, maintain, and understand the process.
  • The process isn't fit for RPA. To be most effective, the tasks need to be high volume and rules-based. Ideal examples are data entry, cross-checking documents, and spreadsheets. Any jobs that require creative thinking and problem solving are best left to humans.

How has automation evolved?

  • Low-code solutions – RPA is no longer only for those with a Computer Science degree or Engineering background. These might be an advantage, but much of the software now lends itself to non-tech people. Drag and drop elements broaden the possibilities for automation
  • Enhanced capabilities of bots – integrating Optical Character Recognition (OCR), Natural Language Processing (NLP), and leveraging Application Programming Interface (APIs) to communicate are critical ways in which RPA has evolved.
  • Tech-savvy – many professionals in audit and regulatory roles now have a better understanding of the technologies, the value they provide, how they benefit organizations, and support business goals. As a result, the regulatory bodies are more open and lenient with new software
  • RPA and intelligent automation – if RPA exists for bots to follow the steps, intelligent automation goes a step further. It allows for simple decision making and the ability to learn from straightforward tasks. This is the beginning of creating a more human experience, not just a robot following processes.

It's an exciting time for RPA and automation. It's time to free your workforce from focusing on mundane and repetitive tasks and allow them to progress and grow through stimulating work. It's time to take back control of operations with efficient bots who will learn from their human counterparts.‍

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