The Journey to Intelligent Automation with RPA & DataRobot
Background on Robotic Process Automation
The term “robotic process automation” (RPA) emerged as a marketing term around 2010. RPA focuses on the user interface (UI) levels of applications to automate processes and is highly dependent on both screen scraping and workflow automation. Rather than being dependent on code, as is required for screen scraping, RPA software allows users to establish automation and manage workflows using drag-and-drop features in a visual way that eliminates the requirement of coding knowledge. RPA’s value comes from the elimination of manual and repetitive tasks using attended or unattended robots to automate a process that was once a manual one.
“As organizations look for ways to improve operational efficiency and integrate legacy systems with new enterprise applications and digital business, robotic process automation continues to grow its footprint.” (2019 Gartner Magic Quadrant for Robotic Process Automation Software)
Journey to Intelligent Automation
As organizations grow their RPA programs, they will look beyond core capabilities and seek higher value opportunities. By leveraging machine learning (ML), intelligent automation (IA) programs can develop solutions for opportunities that were thought to be too complex to automate and in need of human intervention to make the predictions. With DataRobot, we can train machine learning models to make those decisions and continue the automation without human interaction.
RPA can be a very valuable tool for everyone. But the key to making it into true intelligent automation is to connect the hands (RPA) with the head (ML+AI). This is where machine learning with DataRobot can jump-start your RPA program to create solutions that were never thought to be fully automated.
Maturing the intelligent automation program takes time. The goal is to operationalize capabilities within your organization to improve delivery and beat competitors. As the program evolves, expanding your Center of Excellence (CoE) is critical, creating new roles that can be shared by existing members of the CoE to provide insights on the new machine learning capabilities.
We have partnered with Automation Anywhere, Blue Prism, and UiPath to develop DataRobot packages that integrate easily into RPA processes. Our prediction API can also easily be called upon using REST web services existing in almost all RPA solutions, such as Blue Prism. We are continuing to build out packages to make it easy for clients to connect the RPA processes with the machine learning tools from DataRobot.
Bringing together RPA with machine learning models that are built in DataRobot forms an intelligent automation solution. DataRobot can connect to all RPA platforms and has built-in integrations with the leading RPA tools.
Below are demos of RPA tools working together with DataRobot machine learning for intelligent automation solutions.
DataRobot and UiPath video demo:
DataRobot and Automation Anywhere video demo:
DataRobot and Blue Prism video demo:
About the Author:
Andrew Pellegrino works in Business Development at DataRobot specializing in Robotic Process Automation with Machine Learning. Previously, Andrew lead the Intelligent Automation team at Kellogg Company. Andrew was also part of the Intelligent Automation practice at KPMG for over 4 years assisting clients from initial strategy to implementation of Intelligent Automation solutions. Andrew has a M.S. in Finance and a B.S. in Economics from Michigan State University.
Andrew works in Business Development at DataRobot specializing in Robotic Process Automation with Machine Learning. Previously, Andrew led the Intelligent Automation team at Kellogg Company. Andrew was also part of the Intelligent Automation practice at KPMG for over 4 years assisting clients from initial strategy to implementation of Intelligent Automation solutions. Andrew has a M.S. in Finance and a B.S. in Economics from Michigan State University.
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