Robotic Process Automation (RPA) certainly seems to be the topic du jour as of late.
Many of our clients are asking questions about it, and some management consulting firms are taking to social media to describe how RPA is an absolute business priority.
As a result of such dialog, I wanted to create a multi-part blog to offer more information about RPA and perhaps cut through a lot of the noise that’s been floating around about it. This first post will define and discuss the various items that fall into the overall bucket of RPA.
The next blog will be about why RPA is important and why it matters to you. And finally, the 3rd blog will provide some steps to focus on for a successful RPA implementation.
What is RPA?
The Institute for RPA and AI (of which I am a member) defines RPA as “the application of technology that allows employees in a company to configure computer software or a ‘robot’ to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems.”
So, what does that actually mean? I simply define RPA as automation that removes or reduces manual intervention in a process or processes. And it can be as simple as just automating the repetitive, routine tasks within a process flow.
For example, RPA can be removing the redundancy of reentering data into multiple systems or removing frequently updated items based on simple logic.
Using RPA can enable processes to become more accurate and predictable, and as a result, free up human intervention for more significant tasks such as analyzing and interpreting data.
Continued process improvement
RPA really just is the next iteration in a long line of strategies organizations have deployed to improve their technology and business processes.
In the late 1980s and throughout the 1990s and 2000s, organizations used enterprise software to improve processes by creating consistent, accurate and integrated data. In this scenario, they had a singular setup for both their purchasing and accounts payable applications – thus limiting redundant data management.
Process improvement also has been the argument for moving enterprise ERP or HCM solutions to the cloud. The platform helps improve the process of supporting large enterprise applications by enabling a third-party to manage them.
Now RPA has become the next iteration of an organization’s process improvement quest because it enables an entire process flow to become seamlessly integrated with little or no manual intervention.
My good friend Paula gave me a great example I love to use about telephone operators. Many years ago, you couldn’t call someone without the manual intervention of an operator. Eventually, telephone systems were automated, and now you simply dial the number you want and it’s connected without any manual intervention.
This is significantly more efficient and cost effective, and as a result, telephone use exponentially grew. This is the same as RPA, but for organizational processes.
Automating pieces and parts
RPA can include “bots”, which are small, automated pieces of a process. An example would be an organization I recently worked with that automated the process of answering various human resources (HR) questions from employees. Its bot (short for robot) knew the identity of the person asking the question based on their active directory authentication when they logged into the network.
The organization’s employees can ask the bot for the amount of vacation they have left, then the technology queries the HR database for the balance and displays it as well as the last time they took time off. The bot also can answer simple questions like providing contact information for their benefits insurance provider or which benefit plans they had selected.
All of this has helped reduce the time HR staff is spending answering routine questions and allowed them to work on other tasks or answer more complex employee questions. The Chicago Tribune just wrote about West Monroe Partners utilizing bots in its HR department.
RPA actually has been around for about 10 years, but has significantly picked up steam in the last 12 to 18 months. It’s commonly perceived as the first stage in the evolution of automation and artificial intelligence.
These stages include:
- Autonomics - automation augmented by humans
- Cognitive Computing - end-to-end automation with human oversight
- Artificial Intelligence (AI) - fully automated with computers “learning” by analyzing trends in repeated processes over large numbers of transactions
I will address the items on the “AI Spectrum” in future blogs where intelligent automation services blurs the lines between RPA and AI.
Next Ashling Insight: Why does RPA matter and what's in it for you?