Those of us of a certain vintage can recall the uproar stirred by the ideas put forth in Michael Hammer and James Champy’s Reengineering the Corporation. Originally published in 1993, the authors argued that operational improvement should not be limited to incremental gains of 10 percent or 20 percent, but rather should aim for a “quantum leap in performance the 100 percent or even tenfold improvements that can follow from entirely new work processes and structures.”
Indeed, the idea of transformational change which is today at the core of CXO agendas, has a long history. But while businesses have worked at fundamentally reengineering their business processes for more than 20 years, most have failed to achieve the benefits anticipated. A key factor has been that the technology needed to support the radical process redesign that Hammer and Champy envisioned was not up to the task.
The rapid growth of Robotic Process Automation (RPA) capabilities changes the equation. So what does a RPA robot look like? Put aside the image of R2D2 and bb8, think digital bots that can execute any task that can be defined and governed by business rules. Think of finance and accounting, procure to pay, payroll processing, clinical data management and any host of business processes that follow a standardized protocol. Digital robots log on to systems, extract data, analyze for results and send e-mails and reports just like a humans.
If you think of reengineering as comprising three pillars: processes, technology and people, Craig Nelson a case can be made that the process principles developed by Hammer, Champy and other reengineering pioneers are well established. The emergence of RPA, mean while, takes technology capabilities to unprecedented levels.
Which leaves us with the people component, and several burning questions: first off, what skills will people need to effectively leverage process discipline and technology and enable true business transformation? The people managing RPA-fueled business process reengineering face some tough challenges, such as determining which processes and functions should be automated and which shouldn’t be. This is critical, as experience is showing that automation for its own sake is a losing proposition.
Another thorny task is defining the white spaces between automated processes and human intervention and connecting the dots. While these problems are being approached in a new way through RPA, the problems them selves are in many respects straight out of classic organizational science text books, suggesting there’s still a place for old school talent in the new age.
RPA is also redefining the skills requirements of employees impacted by process change. Enterprises are discovering that RPA isn’t about eliminating 40 percent of the workers in a department, but rather about eliminating 40 percent of the workload of each worker in the department. So the task becomes automating the right parts of the existing job and then reskilling to fill the freed up bandwidth to optimal benefit. This is a complex and by no means painless proposition and the people affected being people will in many cases be resistant, frightened and resentful. It’s naïve to believe otherwise, just as it’s unrealistic to argue that RPA will simply eliminate the boring parts of our jobs and allow us all to be more creative.
But difficult as these conversations might be, they are taking place, and initiatives are underway to tackle these complex challenges and address the granular realities of what smart machines can achieve.