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The evolution of process automation

Intelligent automation can change how work gets done, but organizations need to balance operational efficiencies with evolutionary workforce changes.

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We hear a lot about automation and its impact. But in reality, the evolution of task automation spans history—from Mayans automating water transportation via aqueducts to Henry Ford’s automation of the mechanical assembly line.¹

Automation has always represented an opportunity to create value from the balance of the classic paradigm of people, process, and technology. Consider automating water transport: technology (the aqueducts) enabled the process (water transport) supported by people (who built the aqueducts). This same balance ushered in the industrial age.

This paradigm shifted in the information age. Data-related tasks require people (on a keyboard) to enable processes (transactions) supported by technology (telephones, spreadsheets). Automation of data-driven tasks started in the 1960s with enterprise resource planning systems and evolved to include robotic process automation.

But automation of tasks beyond simple “screen scraping” and data sorting has been stymied by the ability to ingest only structured formats and enterprise operating processes that were non-digital or contained unreliable data. Task automation under these conditions still required human intervention—until recently.

Intelligent automation is a new capability that enables processes to perform in ways that optimize the amount of human support needed.

This shift—moving the burden of processes from humans to technology—has the potential to redesign the way work gets done. As increasingly more complicated tasks are performed by process automation, humans are free to engage in higher-value tasks.

In a recent IBV survey of more than 3,000 organizations, almost every enterprise reports engagement in some level of intelligent business process automation. Almost four out of ten are employing AI-based capabilities.

Pioneers in technology-driven intelligent automation are taking strategic steps to balance operational efficiencies with evolutionary workforce changes. In this report, we examine the steps taken by these early adopters and provide guidance for those seeking to explore intelligent automation.

¹ Lev, Katy Rank. “Ancient Mayans masters of water pressure.” Mother Nature Network. December 23, 2009. https://www.mnn.com/green-tech/research-innovations/stories/ancient-mayans-masters-of-water-pressure; Eschner, Kat. “One hundred and three years ago today, Henry Ford introduced assembly line: His workers hated it.” Smithsonian Magazine. December 1, 2016. http://www.smithsonianmag.com/smart-news/one-hundred-and-three-years-ago-today-henry-ford-introduced-assembly-line-his-workers-hated-it-180961267/; One of many to define the division of labor: “Division of Labour.” Wikipedia, accessed September 25, 2017. https://en.wikipedia.org/wiki/Division_of_labour#Adam_Smith

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Meet the authors:

Gene Chao, Global Vice President and General Manager for IBM Automation; Elli Hurst, IBM Global Business Services, Vice President for Global Automation; Rebecca Shockley, Executive Consultant CBDS Data Platform & AI, Global Business Services

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