Robotic process automation (RPA) is software that aims to automate back-office work, eliminating the need for humans to perform mundane tasks like gathering and sorting data and freeing up their time to do more strategic work. Artificial intelligence (AI) is a computer system that is able to perform tasks that ordinarily require human intelligence. When brought together, these two powerful tools take digital transformations to the next level.
By mapping out how people, processes, and technology interact to deliver value to customers today, an operating model serves as an invaluable tool for executives planning to invest in new ways of delivering value tomorrow. Operations can be mapped for the whole company but also for individual divisions and departments. This leveling is critical for companies intent on enterprise-wide digital transformation. Executives can utilize their own budgets and teams in their quest to root out inefficiencies within the departments they oversee.
Business process and information system misalignment is wasteful
A common source of inefficiency in operating models is misalignment between process and technology. When this occurs, the inevitable result for the people involved is more work. This knowledge work demands experience and expertise of the business, but as a well-structured series of routine tasks, it tends to be boring. In many middle and back offices, professionals spend time working across multiple computer systems while moving data between them. Work caused by poor design is wasteful. It squanders scarce resources, increases the cost of doing business, is demotivating and error-prone, and slows processes to compromise customer service.
Robotic process automation realigns information systems
Companies need a fast, cost-effective means to realign information systems with the business processes they support. Robotic process automation (RPA) is proven in this role. Typical RPA projects are completed in under six weeks and generate positive return on investment in months. Business processes can be automated by substituting humans with computers and deferring repetitive and routine tasks to software robots. Using software robots for routine tasks frees employees to focus on high-value tasks such as attending to customers’ service requests. Just as a switch within an electronic system moves current between circuits, RPA can control the flow of digital information, moving it across applications. RPA provides a fast, effective, and affordable means of realigning multiple systems to the real information needs of a business process.
Abstract tasks are beyond RPA’s reach
RPA is a powerful tool of digital transformation capable of converting entire sequences of routine tasks into new straight-through processes. However, many processes are more complicated because they combine routine tasks with a second, higher form of knowledge work. Abstract tasks require weighing conflicting demands, applying common sense, making judgments, and deciding courses for action. Abstract tasks are beyond the reach of RPA’s procedural “do this, then do that” capabilities. Applying RPA to processes involving both routine and abstract work leaves humans in the loop, as the flow of digital information must stall to wait for human involvement. While this may be necessary for some processes, particularly in regulated sectors, there are many processes where transformation to new digital straight-through work makes good business sense.
Automated machine learning complements RPA
Many abstract tasks can be automated with machine learning models. As an example, DataRobot worked with a large American insurance company to create a machine learning model capable of routing emails to the relevant customer service team, freeing employees from the otherwise burdensome task of deciding which colleagues were best placed to respond to customers. Embedding this model into a new workflow created by our partner UiPath proved straightforward and simple.
With DataRobot, the same teams responsible for RPA create the AI needed to automate beyond human in the loop and achieve new digital straight through processes. Used together, RPA and DataRobot accelerate your company’s pace of digital transformation.
About the Author:
Scott Armstrong works in Business Development at DataRobot. Previously, Scott ran Business Development at Domino Data Lab and worked in Business Development at Cloudera. He enjoys the intersection of Automation, Data Science and AI, and spends time with his wife and kids biking and hiking in the woods of South Carolina and North Georgia. Scott has an MBA from the University of Chicago Booth School of Business.