Robotic Process Automation (RPA) Set to Transform Industries & the Global Workforce
RPA (robotic process automation) is one of the hottest topics being discussed in executive suites and online tech forums today. PricewaterhouseCoopers estimates a $2 trillion economic impact from RPA powered digital transformation. The firm projects that 45% of work activities may be automated.
Today, the software / hi-tech and banking / financial services industries are leading this white collar robotics revolution. Healthcare and retail are lagging the most but are seeking to close the gap. Sandwiched in between are manufacturing, transportation and energy industries according to several research firms, to include a joint KPMG, HFS Research study titled, the “State of Operations and Outsourcing 2017.” But what exactly is RPA? Are there any early successes and lessons learned? And finally, how might robotic process automation and AI shape the nature of work and our future workforce?
What is Robotics Process Automation (RPA)?
The Institute for Robotics Process Automation and Artificial Intelligence defines, RPA as, “…the application of technology that allows employees in a company to configure computer software or a “robot” to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems.”
Many of us are familiar with robots seen in Hollywood movies and on the factory floor of manufacturing plants. Similar to these robots that do the heavy lifting of blue collar workers, RPA does the repetitive and mundane, low value-added work of white collar workers. Additionally, RPA can put robots in the hands of real people on the front line — and not just in the hands of industrial engineers, outside consultants or other techies working behind the scenes. This allows thoughtful organizations to create a mixed human-robot workforce that combines the creativity, innovation and flexibility of people with the speed, accuracy and discipline of software robots. This marriage of humans and machines will define the future of work. Simply put, real people are now working alongside their new digital colleagues. While RPA is still in its infancy, there are some early successes and lessons learned in the software technology and banking / financial services industries.
Early RPA Successes
The earliest and most successful applications of RPA have been with very structured, repetitive tasks like those found in telecom, HR, finance and accounting, insurance claims, mortgage processing,customer service and help desk support
- ANZ Bank uses RPA to automate more than 40 processes, freeing up their people to do more higher-value add and rewarding work
- AT&T Technology and Operations introduces “Bots [that] can complete tasks, which once took days or weeks over the course of a year, in a matter of hours.”
- According to Transparency Market Research, “the global IT robotic automation market will reach a value of US$16. billion by 2024, expanding at a CAGR of 47.1% during the period from 2016 to 2024.”
- IBM combined RPA with Watson help a leading financial company create 50% more growth without adding more headcount
- Sourcing and management advisory firm, Mindfields, estimates cost savings of “more than 30 per cent across key RPA-centric functions such as finance and accounting, human resources and supply chain, within the next one to two years.”
- RPA vendor, Blue Prism, stock price soars to 865 on 1 Aug 2017, up from 280 in Nov of 2016. Customer and sales continues to rise in first half of 2017.
RPA Lessons Learned
- Assign a single partner to be in charge of the entire project when using outside vendors
- Provide vendors with incentive to transfer knowledge to your employee team members
- Adapt an Agile implementation methodology, not waterfall
- Define the rationale for the RPA initiative, help people adapt to the change and communicate, communicate, communicate
- Identify early adopters and log quick wins to build momentum
- Select RPA team members that are comfortable with ambiguity and failure as there will be lots of trial-and-error learning taking place at a rapid rate
- Identify processes that have simple if-then business rules vs. those that are very complex or require human judgment
- Tasks with high volume transactions, minimal manual exception-handling and high risk of mistakes are often good candidates for automation.
- Look for processes that require accessing multiple systems to extract data.
The robotic processing automation market is projected to grow at a double-digit rate (47%) over the next seven years and it will transform industries, processes and the very nature of work. Workers of the future will have to not only do their own work but create bots to work alongside of them to get work done better and faster. Those that get out front will be able to shape the future of robotics in a manner that can be both humanistic and rewarding. However, those who tarry too long may find themselves lacking the marketable skills and experience required of the future workforce.