Cognitive Process Automation™ and Tomorrow’s Workplace

“Eighty percent of IT’s effort is focused on mundane grunt work — ditch-digging to keep the lights on with barely 20% spent on innovation,” says Frank Casale, founder of the Institute for Robotic Process Automation (IRPA). He told Cindy Waxer (@Cwaxer), “Taking on the bulk of routine, dismal work … makes IT workers feel like human robots.”[1] The same can be said about most workers’ feelings whose primary tasks involve routine, tedious work. Through the ages, innovators have developed technologies to relieve humans from having to perform such tedious tasks. Robotic process automation (RPA) is simply the latest technology developed with that same purpose in mind. Waxer writes, “For today’s overworked, time-strapped IT employees, bots are more than simply apps that perform automated tasks, like delivering weather reports or taking pizza orders. Rather, they’re a respite from endless help-desk calls, constant software updates and tedious server maintenance jobs.” Analysts at Nanalyze agree. They observe that nobody has ever said, “I can’t wait to push some paper today!”[2] They continue, “The mind-numbing work to keep the wheels of commerce rolling — filling out invoices, deciphering hand-written memos, processing insurance claims — can be a real grind. It’s been that way since the time when Ebenezer Scrooge refused to provide another lump of coal to help warm overworked clerk Bob Cratchit. Lacking frailty of mind and body, artificial intelligence for business process automation appears to be a no-brainer.”

What is Robotic Process Automation?

Most people are familiar with process automation. It’s been around since Henry Ford invented the assembly line. So what is RPA? Analysts from sourcingfocus.com write, “The most important thing to say about RPA is that it is not a robot! At least it is not a physical robot. RPA is a type of software that is able to interface with computer systems in the same way as a person does. RPA software is able to ‘type’ and is able to ‘click’ and is able to move a cursor. This enables it to open and close programs and to use programs. This is why the term ‘robotic’ was coined — there’s no physical robot but the software behaves in a robotic way. What is key though is that the RPA software is able to carry out tasks with a much greater level of efficiency than a human operator — and it never gets tired. RPA has been shown to be a highly effective option for carrying out certain types of tasks. It has delivered huge cost savings for organisations and eye wateringly massive returns on investment of 100s of per cent in some instances. It is certainly worth every organisation taking a serious look at how they might take advantage of what it is able to do.”[3] Bob Violino (@BobViolino) adds, “Robotic process automation [is] technology that lets software robots replicate the actions of human workers for routine tasks such as data entry [and it] is altering the way organizations handle many of their key business and IT processes.”

What is Cognitive Process Automation?

RPA has been around for some time. In discussions with clients, however, I’ve discovered they want to move beyond RPA and make their processes smarter not just automated. They want Cognitive Process Automation™. Violino notes, “When RPA is used in conjunction with cognitive technologies, its capabilities can be significantly expanded.” David Schatsky (@dschatsky), managing director at Deloitte, told Violino, “The integration of cognitive technologies with RPA makes it possible to extend automation to processes that require perception or judgment. With the addition of natural language processing, chatbot technology, speech recognition, and computer vision technology, for instance, bots can extract and structure information from speech audio, text, or images and pass that structured information to the next step of the process.” McKinsey analysts call this next step “intelligent process automation.” They assert, “We believe [intelligent process automation] will be a core part of companies’ next-generation operating models.”[5] Whatever you want to call it, cognitive technologies are going to make process automation activities smarter.

Not all process automation tasks require cognitive capabilities. Anastassia Fedyk, a Ph.D. Candidate in business economics at Harvard Business School, explains, “Start by distinguishing between automation problems and learning problems. Machine learning can help automate your processes, but not all automation problems require learning. Automation without learning is appropriate when the problem is relatively straightforward. These are the kinds of tasks where you have a clear, predefined sequence of steps that is currently being executed by a human, but that could conceivably be transitioned to a machine. This sort of automation has been happening in businesses for decades.”[6] As noted above, Casale believes tedious work makes workers “feel like human robots.” McKinsey analysts believe intelligent process automation “takes the robot out of the human.” They suggest that cognitive process automation requires five key technologies. They are:

  • Robotic process automation: “A software automation tool that automates routine tasks such as data extraction and cleaning through existing user interfaces. The robot has a user ID just like a person and can perform rules-based tasks such as accessing email and systems, performing calculations, creating documents and reports, and checking files.”
  • Smart workflow: “A process-management software tool that integrates tasks performed by groups of humans and machines (for instance, by sitting on top of RPA to help manage the process). This allows users to initiate and track the status of an end-to-end process in real time; the software will manage handoffs between different groups, including between robots and human users, and provide statistical data on bottlenecks.”
  • Machine learning/advanced analytics: “Algorithms that identify patterns in structured data, such as daily performance data, through ‘supervised’ and ‘unsupervised’ learning. Supervised algorithms learn from structured data sets of inputs and outputs before beginning to make predictions based on new inputs on their own. Unsupervised algorithms observe structured data and begin to provide insights on recognized patterns.”
  • Natural-language generation (NLG): “Software engines that create seamless interactions between humans and technology by following rules to translate observations from data into prose. … Structured performance data can be piped into a natural-language engine to write internal and external management reports automatically.”
  • Cognitive agents: “Technologies that combine machine learning and natural-language generation to build a completely virtual workforce (or ‘agent’) that is capable of executing tasks, communicating, learning from data sets, and even making decisions based on ’emotion detection.’ Cognitive agents can be used to support employees and customers over the phone or via chat, such as in employee service centers.”

Because cognitive (or intelligent) process automation remains in its infancy, it’s likely to mature in a number of different ways depending on the industries it supports and the processes it automates. Violino adds, “The integration of cognitive technologies and RPA is extending automation to new areas and can help companies become more efficient and agile as they move down the path of becoming fully digital businesses.”

Summary

McKinsey analysts conclude, “Companies are using IPA to invest in and develop new platforms, engage with customers, and win over advisors, all at a dramatically lower cost. But companies are only scratching the surface of what is possible. Tomorrow’s winners are those that embrace these capabilities as part of a next-generation operating model and move quickly to capture the value from them, pulling away from the laggards who choose to dip in only one toe at a time.” Sourcingfocus.com analysts agree. “RPA and AI are not the future,” they write, “they are the present. A great return on your investment that efficiently and effectively gets the job done. Whether or not you and your organisation ultimately invest in RPA and AI solutions importance of investing in finding out more about it the case for investing some time and energy in finding out more about it and how it might add value to your business is extremely compelling. Those that don’t run the risk of missing out on a very good thing.”

Footnotes
[1] Cindy Waxer, “Get Ready for the Bot Revolution,” Computerworld, October 2016.
[2] Staff, “Artificial Intelligence in Business Process Automation,” Nanalyze, 11 February 2017.
[3] Staff, “RPA and AI are not the future – they are the Now!” sourcingfocus.com, February 2017.
[4] Bob Violino, “How to supercharge robotic process automation,” ZDNet, 8 March 2017.
[5] Federico Berruti, Graeme Nixon, Giambattista Taglioni, and Rob Whiteman, “Intelligent process automation: The engine at the core of the next-generation operating model,” McKinsey & Company, March 2017.
[6] Anastassia Fedyk, “How to Tell If Machine Learning Can Solve Your Business Problem,” Harvard Business Review, 25 November 2016.

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