Key Takeaways
- Automation doesn’t affect jobs. Achieving the optimal combination of humans and machines is only possible when work is deconstructed into tasks.
- The Reinventing Jobs framework enables the deconstruction of jobs and workflows into tasks, analyzing the return on improved performance of each task and clearly illustrating where various types of automation will substitute, augment or create human work.
- Achieving the optimal combination of humans and machines required a radical rethink of organization design, culture, and leadership.
- In the face of continued advances in work automation, society will face significant disruption as the traditional mindset of “learn, do, retire” gives way to one of “learn, do, learn, do, rest, …..”
- In order to facilitate this transition, we will need to reinvent education and social security mechanisms, including considering variants of Universal Basic Income.
The book Reinventing Jobs by Ravin Jesuthasan and John W. Boudreau provides a framework to understand and optimize the increasingly rapid evolution of work and automation. The framework explores four steps: deconstruct, optimize, automate, and reconfigure; it can be used to bundle work into jobs and create optimal human-machine combinations.
InfoQ readers can download a sample of Reinventing Jobs.
InfoQ interviewed Jesuthasan and Boudreau about criteria to decide if a task can be automated and different ways to automate tasks, reinventing the leadership role and skills recommended for leaders to develop, how deconstructing jobs into tasks impacts salary and other rewarding mechanisms, the role that Universal Basic Income can play for the future of work, and using their four-step framework as a personal career tool.
InfoQ: Why did you write this book?
Ravin Jesuthasan: Over the last few years, John and I have been keen observers of the debate about humans versus machines, and how much of the debate was framed in terms of jobs being substituted. Our research and experience with many organizations over the last few years clearly illustrated that automation affects tasks, not entire jobs. So we saw an opportunity to provide business leaders with a toolset to achieve the optimal combinations of humans and machines.
John W. Boudreau: We realized that several themes were emerging from our previous work that applied to the work-automation question. For example, “Lead the Work” was about engaging human workers in ways beyond regular full-time employment, and principles such as deconstructing jobs, accounting for the return-on-improved-performance, and a more fluid and permeable work organization boundary were all relevant to work automation as well. Combining “Lead the Work” and “Reinventing Jobs” offers a framework for optimizing human and automated work, within an ecosystem of evolving arrangements.
InfoQ: For whom is this book intended?
Boudreau: This book will be useful for workers, leaders, boards, investors, regulators and policy-makers, because optimizing work automation requires that all of these constituents develop their solutions and ideas with a common framework and goals.
Jesuthasan: This book is intended for everyone who is interested in understanding precisely how automation will affect work and the potential consequences for organizations, leaders and individuals.
InfoQ: In the book, you describe a four-step framework for optimizing work automation. How does that look?
Jesuthasan: The first step involves deconstruction jobs or workflows into component tasks and categorizing them as listed below. The second step involves understanding what we are solving for. The four segments of the curve illustrated below describe the four potential outcomes of an improvement in performance of a particular task; reducing errors, reducing variance, achieving an incremental improvement in performance or achieving an exponential improvement in performance. Step 3 illustrates the three different types of automation to consider and step 4 captures how these different types of automation, combined with the previous two steps to identify where human work should be substituted, augmented or transformed as a result.
InfoQ: What criteria are used to decide if a task can be automated?
Boudreau: There are three criteria we suggest. Each of them is a continuum, rather than a binary yes-no answer. Tasks that fall closer to the “automatable” end of the three criteria are more automatable and vice versa.
#1: Repetitive-Variable: Tasks that are closer to the “repetitive” (the same activity in most situations) end of the scale are more automatable, while those closer to the “variable” (the activity differs by the situation) end are less so.
#2: Independent-Interactive: Tasks that are closer to the “independent” (performed without interacting or consulting with others) end of the scale are more automatable, while those closer to the “interactive” (performed in collaboration with others) are less so.
#3: Physical-Mental: Tasks that are closer to the “physical” (performed with physical motion, strength, etc.) end of the scale are more automatable, while those closer to the “mental” (performance with thought, intellect, creativity, etc.) end are less so.
InfoQ: What are the different ways to automate tasks, and how can we know which one to apply?
Boudreau: We identified three categories of ways to automate tasks: Robotic Process Automation (RPA), Cognitive Automation (including Artificial Intelligence), and Social Robotics.
Robotic Process Automation (RPA): RPA is the simplest and most mature category. RPA automates high-volume, low-complexity, and routine tasks. For example, it has long been used to automate “swivel-chair” tasks that used to require a person to swivel from one data source to another to transfer or connect data from disparate systems. A common application involves transferring data between software systems or using simple rules to find information in emails or spreadsheets and entering it into business systems like enterprise resource planning (ERP) or customer relationship management (CRM).
Cognitive Automation: Cognitive automation uses tools like pattern recognition and language understanding. Cognitive automation in the form of machine learning, using scalable cloud computing resources, has produced systems that can recognize patterns and understand meaning in big data in a human-like way.
Social Robotics: The word “social” refers to robots that move around and interact with people, using sensors, AI, and mechanical machinery. A subset of social robotics is “collaborative” robotics (cobots). Cobots are machines that actually sense the human worker and actively adjust to physically work with the human.
InfoQ: How can robotic process automation, cognitive automation, and social robotics, be combined in post-surgery treatment?
Boudreau: A great deal of postsurgical care requires tasks using the sort of empathy and emotion that no machine can do, but cognitive automation still plays a significant role. Cognitive automation, supported by RPA-created data, gathers and analyzes patient data. Caregivers can use these insights to know how different treatments work on patients with certain genetic makeups. The caregiving staff and physicians can now deliver personalized care that increases rates of patient recovery and reduces complications. Automating the routine tasks of an oncologist’s job reinvents it to focus on the empathetic and emotional tasks that humans do best, and are vitally important in patient recovery. Humans assisted by the AI insights also are more precise in prescribing drug treatments. While social robotics is less common, there are examples of robots that move around the patient space providing words of comfort and leading exercises, such as Zora, a robot deployed in dementia treatment in France, as reported in The New York Times on November 23, 2018.
InfoQ: You stated in the book that the leadership role should also be reinvented. Can you elaborate?
Boudreau: Leadership must evolve along many dimensions. We suggested five transformational changes:
- Mindset. From“learn, do, retire” to“learn, do, learn, do, rest, learn . . . repeat”
- Ability. Fromemployment qualifications towork readiness
- Reward. Fromsalaries for permanent jobs toflexible total rewards for deconstructed tasks and work arrangements
- Deployment. Fromjob architecture and movement between jobs towork architecture continuously matching capabilities to tasks
- Development. Fromcareer ladders based on fixed jobs toreskilling pathways based on tasks and reinvented jobs
InfoQ: What kind of skills do you recommend leaders to develop if they want to be ready for the future?
Jesuthasan: Some of the most critical skills for leaders in the future will include their ability to orchestrate a diverse ecosystem of work options that includes full time employees, gig workers, robotic process automation, AI, alliances, outsourcers, etc. Underpinning the emerging skill of orchestration will be the equally critical skill of curating the optimal work experience for every human who contributes to the work of the organization, regardless of the nature of that work relationship, so they all feel connected to the mission and purpose of the enterprise.
InfoQ: When we deconstruct jobs into tasks, how does that impact salary and other rewarding mechanisms?
Jesuthasan: There is going to be significant disruption in how we value work as the traditional approach of benchmarking whole jobs to determine compensation will become increasingly ineffective as organization deploy tasks to various alternative work options. It will be increasingly critical that companies value skills and tasks so they can appropriately value their own unique combinations of humans and machines.
InfoQ: What's your view on the role that Universal Basic Income (UBI) can play for the future of work?
Jesuthasan: We have been involved in a number of debates and discussions in Davos about the role of UBI in a world where the relationships between skills, work and income is increasingly uncertain. While we believe that society will continue to create work for humans even as automation accelerates, humanity will go through periods of significant transition that may require mechanisms like UBI.
Boudreau: The idea is that in some areas where work automation accelerates, it will become difficult or impossible for organizations and leaders to anticipate work changes in time to reskill the human workers to adjust to the new automation. In those cases, it may be socially and economically optimal to offer workers a period of guaranteed income, while they take the necessary time and actions to transition to new work roles. One version of this idea is to provide all employment-age members of the population a “universal basic income” (UBI), that provides enough income to meet basic needs. In some of the most expansive versions of UBI, it is provided to everyone, with no required actions or means-testing.
InfoQ: How can the four-step framework be used as a personal career tool?
Boudreau: Just as leaders and employers typically think of work, capability, careers, learning and development in terms of jobs and job requirements, workers themselves also often think about a career as a progression of jobs. Our book shows that this fixation on jobs obscures important aspects of work evolution, and hinders the fluid matching of work and workers. Work is constantly evolving at an ever-faster pace. That evolution happens at the level of tasks, not jobs. So, the framework we describe not only helps organizations identify, anticipate and optimize how they design work, it also helps workers think clearly about how the work they are doing, and the work they hope to do in the future, is evolving. By thinking of a career as a constantly-evolving progression of roles that may include jobs, projects, and tasks, and that may engage with organizations in many different ways, workers will be better prepared to anticipate how automation might substitute, augment or enhance their work. They will be better equipped to anticipate work changes and prepare for them proactively.
About the Book Authors
Ravin Jesuthasan is a recognized global thought leader and author on the future of work and human capital. He is a regular participant and presenter at the World Economic Forum’s annual meetings in Davos and Dalian/Tianjin, and is a member of the forum’s Steering Committee on Work and Employment. He has been recognized as one of the top 25 most influential consultants in the world by Consulting Magazine and is also the author of Transformative HR and Lead The Work: Navigating a World Beyond Employment and Reinventing Jobs: A 4-Step Approach to Applying Automation to Work. @ravinjesuthasan
John W. Boudreau, Ph.D. is professor and research director at the University of Southern California’s Marshall School of Business and Center for Effective Organizations. He is recognized worldwide for breakthrough research on the bridge between superior human capital, talent and sustainable competitive advantage. He has authored over 200 publications and received several scholarly and professional lifetime achievement awards and fellowships. His website.