An Agile, Incremental Approach to Business Process Automation

I’ve long believed that customer self-service was key to the success of e-business, - the IBM Internet strategy I was closely involved with in the mid-late 1990s.  It was quite revolutionary how easy it was to now do for yourself so many ordinary activities that previously required a phone call during office hours or a trip to a store or office.

Moreover, such e-business applications were relatively easy to develop.  By integrating their existing transaction and data based applications with a web front-end, - a strategy we succinctly described as Web + IT, - any business could now be in touch with its customers, employees, suppliers and partners at any time of the day or night, no matter where they were.  Companies were able to engage in their core activities in a more productive way by web-enabling their back-end systems, that is, linking their web front-ends to the presentation services of their back-end applications.

I was reminded of IBM’s e-business strategy when recently reading about Robotic Process Automation (RPA), a technology for automating business processes based on emulating the manual actions of a human at a keyboard.  RPA aims to improve the operational efficiency of office and service workers by automating tedious, repetitive, tasks, such as those associated with widely used horizontal processes in HR, Finance & Accounting and IT services.

RPA enables process automation at a fraction of the cost and time of classic software development.  Rather than automating a process by redesigning the overall back-end application, RPA interfaces with the back-end system by performing the same actions that a human does via the application’s user interface.  RPAs thus creates kind of software robots, or bots for short, that work alongside the humans.

I got interested in RPA because earlier this year I joined the advisory board of AiRo Digital Labs, a Chicago-based startup focused on so-called Digital 2.0 consulting services based on RPA, data sciences, AI and other emerging technologies.  In May, the company participated in the Genius Bot Challenge, a competition sponsored by Automation Anywhere, a leading developer of RPA software.  AiRo Digital Labs submitted a bot that automated the process of onboarding new employees, and was chosen, - from among the more than 1000 bots submitted, - as one of the top three finalists, along two much larger companies, General Motors and Entergy.

As this press release explained, the bot “can be configured to onboard contractors, temporary staff, offshore staff, and seamlessly automates a majority of the tasks…  [it] reduced manual labor for HR and IT personnel, increased process accuracy & adherence and led to an overall reduction of about 50% in labor costs and 75% in average time to handle new hire onboarding globally.”  AiRo Digital Lab’s success in the competition, - despite being a small, recently founded startup, - spurred me to learn more about RPAs.

While the term RPA is relatively recent, it’s roots go back to screen scraping technologies.  In the 1980s, screen scraping was widely used to replace text-based, dumb terminal interfaces to back-end applications with graphical user interfaces on PCs.  As discussed above, screen scraping methods  were used in the 1990s to web-enable back-end applications so they can be accessed with a browser over the Internet.  In the past several years, RPA has evolved beyond its screen scraping origins and is now seen by many as a potential game-changing technology, - an agile, incremental approach to business process automation.

Most jobs involve a number of different tasks or processes.  Some of these tasks are more amenable to automation than others, because they are highly-structured in nature, rather than requiring higher-order human skills.  But just because tasks have been automated, does not imply that the whole job has disappeared.  To the contrary, automating those parts of a job will often increase the productivity and quality of workers by complementing their skills with computers, as well as by enabling them to focus on those aspects of the job that most need their attention.  RPA makes it easier to automate those highly-structured, repetitive, and often tedious tasks. 

In a 2015 Harvard Business Review article, professors Mary Lacity and Leslie Willcocks nicely explained the growing importance of RPAs.  “When people first hear the term Robotic Process Automation, they might imagine shiny robots gliding around office buildings.  In reality, this is just software that can be made to perform the kinds of administrative tasks that otherwise require stop-gap human handling - for  example, transferring data from multiple input sources like email and spreadsheets to systems of record like ERP and CRM systems.  Calling it robotic, however, emphasizes the utility of a machine that can stand in for a worker and handle disparate, discrete chores.”

RPA differs from classic business process automation in two key ways: people with business process and industry expertise but no programming experience can start automating processes with RPA tools with only a few weeks of training; and RPA requires few changes to the underlying back-end systems.  Such a lightweight approach to automation lowers the threshold of processes worth automating.  “In general, early adopters of RPA find that automation radically transforms operations, delivering much lower costs while improving service quality, increasing compliance (because everything the software does is logged), and decreasing delivery times.”

Lacity and Willcocks cite Telefonica O2’s use of RPA technologies as a concrete case study.  Using only four people, the UK mobile communications provider deployed over 160 software bots to process between 400,000 and 500,000 transactions each month, yielding a three-year return on investment of over 650%.

Based on their study of Telefonica O2’s RPA journey, the authors concluded that RPA is most suitable for high volume, highly standardized, mature processes that can be well described by a set of rules, and is particularly worth considering in situations where increasing the speed and accuracy of a process will lead outsized benefits.  Since RPA only requires access to the presentation layer of the back-end applications, it can readily run on any in-house platform or cloud-based system.  Compliance risks are minimal because every action executed by an RPA bot is logged and thus auditable. 

A recent study of over 150 companies involved in AI-based projects found that over 70% of the projects were adding AI capabilities to their existing processes.  RPA developers also view AI as the next stage in the evolution of RPAs.  According to a 2017 Forrester report, the RPA market is expected to grow from $250 million in 2016 to around $3 billion in 2021.  

“For us, there is a big takeaway from the case research we have done,” wrote Lacity and Willcocks in the conclusion of their HBR article.  It indicates that, as cost barriers fall, workplaces will naturally gravitate toward teams of humans and robots working together to accomplish goals, each assigned the tasks for which they are ideally suited.  RPA is one automation tool, but not the only one, that will help to bring about this future of operations.

As cognitive intelligence tools like IBM’s Watson are adopted, those will be game changers, too.  Combining these technologies, human knowledge workers might soon, in the midst of creative tasks, call on multi-tasking robotic coworkers to perform supporting work as needed -  boosting their output even in novel processes with robots-on-request.   In this way, contrary to today’s worst fears, robotics could facilitate the rise, not the demise, of the knowledge worker.  Let’s hope the imaginations of their managers expand as rapidly as their automation toolkits.”

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