A five-stage approach to rationalize your business applicationsRead More
Authors: Regina Rider and Gabe Villa
Signals from the financial market don’t paint an optimistic picture for the near term.
The COVID-19 crisis has not only led stocks to plunge but has also resulted in consumer and business behavior changes that may be lasting. As businesses face the realities of working through an economic downturn, they’ll be looking to efficiency and productivity-enabling technologies such as RPA to adapt their business models. Automating manual processes at scale will enable businesses to deploy workers to top priorities, and concentrate on strategic approaches that will get them through economic uncertainty.
Robotic Process Automation (“RPA”) refers to software that can be easily programmed to do typically basic (and advanced in certain cases), repetitive, rules-based tasks across applications.
RPA offers a non-invasive alternative to traditional IT integration. It uses a machine-based automation technology (bot) that possesses data entry, interchange, and manipulation between applications, humans, and processes. RPA does this by mimicking human interactions with web applications, desktop applications, web sites, portals, Excel worksheets, legacy green-screen apps, etc.
The use of RPA technologies is growing at a rate like no other.
Gartner has coined RPA as ‘the fastest-growing segment of the global enterprise software market’ – and predicted that the global market for RPA services will hit an estimated $98 billion in 2020.
Robotic Process Automations has evolved with time. All types of RPA promote cost savings, increased performance and error reduction. Modern technology plays an important role in the evolution of RPA, from cloud auto-scaling and load balancing to using AI for automating judgments in tasks.
The most common type of RPA is Assisted RPA. This is when automation can perform tasks and activities on a person’s desktop, laptop, etc. A perfect example of this would be recording a function on RPA software to perform a calculation, query, even cut and paste on-demand. The user would playback the function as needed to simplify routines and increase productivity.
This type of RPA is also referred to as RPA 1.0 and is practical only when users have the ability to invoke the RPA themselves on-demand. Although, assisted RPA will improve user performance, it is not typically practiced at enterprise scale.
Automation that can run without users and can run at any time (on a schedule) is called Unassisted RPA. In this type of RPA, referred to as RPA 2.0, the software is deployed on one to multiple servers for scale. It does not require user interaction and is used to automate an end-to-end business or IT process. Dashboards are commonly used to orchestrate tasks and monitor performance. The development of this RPA requires precision, keeping in mind there is no human interaction throughout this process.
The newest of RPA types is referred to as Hyperautomation. Hyperautomation uses RPA and Artificial Intelligence technologies like Machine Learning and Natural Language Processing to automate tasks that involve decision making or processing structured or unstructured data. Advance analytic technology is used to mine data, process structured or unstructured data, analyze text, predict and prescribe analytics technology.
Some typical candidate processes ideal for RPA include:
As you can see, RPA is quickly becoming a game changer. Organizations leveraging this emerging technology are realizing significant efficiencies and productivity gains.
By leveraging RPA, you can help to recession-proof your organization by scaling operational efficiencies and streamlining cash flows.
Regina Rider is a senior manager with more than 20 years of experience leading operational and technical teams to deliver transformative solutions for clients in the communications, manufacturing, and financial industries.
Gabe Villa is a cloud and data solutions architect. He recently completed a project to analyze, architect and implement real-time reporting and RPA which enabled a communications company to optimize productivity and reduce overtime.