The Entry-Level Dilemma | KPMG | GLOBAL

The Entry-Level Dilemma

The Entry-Level Dilemma

In a future where foundational work is automated, how will we build careers?

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Global Head of Shared Services & Outsourcing Advisory

KPMG in the U.S.

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Cognitive automation is coming!

As explained by thought leaders—including KPMG’s Robert Bolton—we are currently on the cusp of a fourth great change in the world’s workplace. Whereas once we were able to automate only repetitive mechanical tasks, we are now able to produce software that automates more complicated intellectual tasks such as data analysis and even customer interaction, freeing up the humans behind those jobs to – ideally - focus on innovation. Automation of these basic works tasks is not new – think ATM machines, airport kiosks and various forms online banking and shopping – but the pace of automation has accelterated greatly over the past few years due to advances in computing power and the proliferation of online data to leverage.

For many industries, however, there remains a curious dilemma. Those repetitive tasks that will soon become part and parcel of a robotic worker’s duties actually have traditionally had tremendous value for the people who have to do them at the beginning of their careers.

Bot Auditors

Take, for example, the audit profession. Entry-level auditors are often given repetitive work like reviewing transactions. Though many would see this as passing rote and repetitive tasks down the chain to the junior members of the team, these jobs actually serve a valuable purpose. Through reviewing those transactions, a keen auditor can learn best practices for organizations and their reporting methods. They can learn real-world applications of things they’ve thus far only read in books. Most importantly, however, they can gain valuable experience that can make them more attractive in the future of their career.

In a future where that learning is no longer a direct part of the job, where will it come from? More importantly, where will the “entry level” be for young workers and how will they gain the skills and experience to advance into more senior positions and into management?

These challenges are not as new as they may seem. There has long been an argument against outsourcing, especially offshore, of service jobs from the perspective that if most entry level work in, for example the IT or finance groups, is done offshore, how will those onshore employees learn the skills to move into management? This has proved challenging from a variety of perspectives but most organizations have been able to overcome them by using a variety of techniques such as better collaboration between on and offshore staff, putting limits on what goes offshore, and trusting (and verifying) that the offshore work is being done correctly and leaving onshore resources to focus on more strategic activities.

Interestingly, answering those questions when it comes to automation requires a bit of speculation about what kind of jobs will be created in this new world of automation. “Bots,” as we call them colloquially, will be able to do many of the things that we consider time consuming and repetitive, but the one thing they will not be able to do, at least well, is supervise other bots. Organizations—whether in auditing or any other specialty—will need to create jobs centered around ensuring that bots are working effectively. That oversight will require two different skillsets: the first is managing the bots, but the second is actually knowing what they’re doing to verify that they’re doing it correctly. There are also opportunities to build software bots but this will quickly become a highly commoditized activity in most cases and mirgrate to low cost markets.

Becoming a “Bot Boss”

Unlike supervising people, supervising a bot is more about managing outcomes than managing the process. It won’t, for example, require knowing the intricacies of programming the bots, but it will require learning the technology required to direct them. Luckily, this software already exists, and with drag-and-drop functionality, it’s already intuitive even for first-time users.

There are several outcomes that will need to be monitored. The first, and most obvious, is the work itself. At a low level, if you’re auditing transactions and the results being presented by your bots don’t make sense, there is clearly something going wrong in the workflow. But checking each output could be almost as consuming as just having a human worker do the actual work. That’s why bots are equipped with secondary processes that check for errors. In the event of something not adding up, a Bot Boss will be required to look into it.

Off-the-job Training

But this new entry-level position still requires an in-depth knowledge of those best-practices. There will need to be better and more structured on-the-job training. But where else will our new employees learn them? As with many other social phenomena, the answer is more simple than we think: they’ll learn them in schools, universities and through specialized traning programs.

University programs are never static. Curricula change every year—every semester even—based on new insights into various fields of study. There will be much more reliance in the future to provide students with valuable training in practical tasks that replace the on-the-job training they would otherwise have had in the first formative years of their careers. There are many challenges to this route that will need to be overcome, however, such as the high-cost of post secondary education in markets such as the United States, weak primary and secondary educational systems that do not prepare students for more advanced learning, and in some markets, little or no access to quality educational services.

These changes will not be easy or quick, nor should they be. This is the fourth major industrial revolution, and with each of history’s other leaps forward in mechanization, we are poised to have a lot to learn.

But we shouldn’t be afraid, either.

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