Four Fundamentals of Workplace Automation

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As the automation of the physical and the digital world advances, many jobs will be redefined rather than eliminated - at least in the short and medium term much like bank teller's job was redefined with the advent of ATMs.

The potential of artificial intelligence to perform tasks once reserved for humans is no longer reserved for spectacular demonstrations by driverless cars, machines beating humans at chess, go or PacMan. Just head to an airport: automated check-in kiosks now dominate many airlines' ticketing areas. Pilots actively steer aircraft for just three to seven minutes of many flights, with autopilot guiding the rest of the journey. Passport-control processes at some airports can place more emphasis on scanning document barcodes than on observing incoming passengers.

What will be the impact of automation efforts like these, multiplied many times across different sectors of the economy? Can we look forward to vast improvements in productivity, freedom from boring work, and improved quality of life? Should we fear threats to jobs, disruptions to organizations, and strains on the social fabric?

A recent Mckinsey research suggests, first and foremost, that a focus on occupations is misleading. Very few occupations will be automated in their entirety in the near or medium term. Rather, certain activities are more likely to be automated, requiring entire business processes to be transformed, and jobs performed by people to be redefined.

More specifically, our research suggests that as many as 45 percent of the activities individuals are paid to perform can be automated by adapting currently demonstrated technologies. In the United States, these activities represent about $2 trillion in annual wages. Although we often think of automation primarily affecting low-skill, low-wage roles, we discovered that even the highest-paid occupations in the economy, such as financial managers, physicians, and senior executives, including CEOs, have a significant amount of activity that can be automated.

The organizational and leadership implications are enormous: leaders from the C-suite to the front line will need to redefine jobs and processes so that their organizations can take advantage of the automation potential that is distributed across them. And the opportunities extend far beyond labor savings. When we modeled the potential of automation to transform business processes across several industries, we found that the benefits (ranging from increased output to higher quality and improved reliability, as well as the potential to perform some tasks at superhuman levels) typically are between three and ten times the cost. The magnitude of those benefits suggests that the ability to staff, manage, and lead increasingly automated organizations will become an important competitive differentiator.

According to our four interim findings elaborating on the core insight that the road ahead is less about automating individual jobs wholesale, than it is about automating the activities within occupations and redefining roles and processes.

  • The Automation of Activities: Our extensive research during design and development of AI-BPR and Max Impact Framework suggests across verticals that the mechanics of activities will change, not the activities themselves. If you have a certain set of capabilities that are required for a job, then the relevance of these activities remains. The mechanics of who performs these activities changes. For example, if your customer support agents used 65% of their time giving Level 1 support, and that can be automated, then the support agents will simply move up the value chain and focus on end to end customer experience rather than answering redundant "automatable" queries. Upskilling is the key to job retention. As part of our research we outlined a set of roles, established the capabilities required to execute those roles, and then finally looked at the "Automatibility"of those capabilities using current and cutting edge technologies, adjusting the levels of capabilities based on constraints and external factors that induce unreliability in the process (forcing human intervention).
  • Redefinition of Jobs and Business Processes: According to our analysis, fewer than 5 percent of occupations can be entirely automated using current technology. However, about 60 percent of occupations could have 30 percent or more of their constituent activities automated. In other words, automation is likely to change the vast majority of occupations—at least to some degree—which will necessitate significant job redefinition and a transformation of business processes. As roles and processes get redefined, the economic benefits of automation will extend far beyond labor savings. Particularly in the highest-paid occupations, machines can augment human capabilities to a high degree, and amplify the value of expertise by increasing an individual's work capacity and freeing the employee to focus on work of higher value.
  • Impact on High Wage Occupations: Conventional wisdom suggests that low-skill, low-wage activities on the front line are the ones most susceptible to automation. We're now able to scrutinize this view using the comprehensive database of occupations we created as part of this research effort. It encompasses not only occupations, work activities, capabilities, and their automatability, but also the wages paid for each occupation. Our work to date suggests that a significant percentage of the activities performed by even those in the highest-paid occupations (for example, financial planners, physicians, and senior executives) can be automated by adapting current technology.
  • Future of creativity, inference and meaning: Capabilities such as creativity and sensing emotions are core to the human experience and also difficult to automate. The amount of time that workers spend on activities requiring these capabilities, though, appears to be surprisingly low. Just 4 percent of the work activities across the US economy require creativity at a median human level of performance. Similarly, only 29 percent of work activities require a median human level of performance in sensing emotion.

Automation, if implemented incorrectly, opens up a new concern. High levels of automation means more data, more data means increased concerns about data security and privacy. The quality and safety risks arising from automated processes and offerings also are largely undefined, while the legal and regulatory implications could be enormous. To take one case: who is responsible if an autonomous taxi has an accident?

We feel, customer centric business processes are ripe for automation using technologies like AI, Machine Learning, and even Blockchain. The era of smart systems has begun and process design and process reengineering powered by design thinking is the key to getting it right.

We are ready with our tools, methodologies and expertise. It's time to engage.

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Mritunjay Kumar
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