Process Automation as a Driver of Quality, Efficiency, and Lower Operational Cost

Intelligent Automation is the intersection of process automation, and artificial intelligence (AI) technologies. AI is all over the news and in many marketing communications. Often you see it also called, machine learning, cognitive technologies, or deep learning (a type of AI solution).  Regardless of the nomenclature, its primary value is in automation and making decisions. At its core, it’s software learning from your data that does what people do. However, an AI model gains its value when embedded in your technology. Thus, the area of Robotic Process Automation (RPA).

Robotic process automation (RPA), or just process automation, is software that interacts with applications, or web sites, in the same way as humans. It does this by having a “script” that automates repetitive, rules-based processes usually performed by people sitting in front of computers. By interacting with applications just as humans would, software robots can open email attachments, send emails, complete e-forms, record and re-key data, extracts data from systems or documents, and perform other tasks that mimic human action. The tasks are performed by software robots, or “bots”, that execute the steps on behalf of people.  These can also be scheduled to run at scheduled times.

Many large organizations across industries are automating at least some of their processes. RPA is gaining broader recognition.  However, executives still have a limited understanding of its full value. In a Deloitte survey last year of 1,500 “cognitive-aware” executives in the U.S., roughly 17 percent were familiar with both the concepts and the application within their companies. [1]

Globally, 59% have either scaled automation across parts of the business, fully automated at least one process, or have piloted at least 1 process. However, of these only 19% have scaled across the business.1 Approximately 50% of the processes eligible for automation have not been realized. The more processes that leverage automation, the greater the return on investment.

RPA is a solution to drive benefits through automation, with or without AI technology by:

• Creating Greater Efficiency
  The “bots” can perform more tasks, with greater speed, and can operate 24/7. This gets tasks done faster, with fewer data entry errors, and handles more volume. This impacts cost through cost avoidance – handling more volume without the need to hire more people.
• Improving quality
  Since the bots can access email, systems, spreadsheets, etc. data is collected and moved between application with human data entry. This removes human error in the equation. In addition, since it performs faster than humans, it can perform additional validation check, that would require more time/effort than a person. This lowers cost by avoiding rework due to data entry errors.
• Lower Operational Cost
  The cost savings come from the ability for the bots that can perform repetitive, rules-based tasks, faster, and more efficiently. This means you need fewer people to perform these tasks, freeing them to focus on exceptions or other higher value activities.

While many larger companies are smaller companies can achieve the same return on investment. According to Deloitte, smaller companies are less likely than larger companies to automate processes, but their success rate is higher. The findings from these organizations show that several differentiators for success hold true regardless of company size. 1

In talking with executives, we often get the question, “process automation has been around a long time, how it this different?” This is not your father’s business process management (BPM) system. The current state of the technology is fast to implement. A single, simple set of automation tasks can be achieved in weeks, without any programming data interfaces to other systems. In addition, using an agile approach, processes can be implemented quickly. In addition, today’s process automation is augmented by the ability to a) send/receive emails, extract data from documents using Optical Character Recognition (OCR), and/or AI.

Increasingly, RPA is being combined with other AI technologies such as speech recognition, natural language processing, and machine learning to automate perceptual and judgment-based tasks once reserved for humans, which is extending automation to new areas and help companies become more efficient and agile. We’ll leave this for a later article.

[1] McKinsey, “The Automation Imperative”, Sep 2018