How Automatable are Procurement and Supply Chain Jobs?

robot Nataliya Hora/Adobe Stock

Last Tuesday, President Donald Trump signed an executive order to review the H-1B visa program, which brings 85,000 highly skilled foreign workers to the U.S. every year. The executive order was long coming. Critics of the current program argue that since workers under the H-1B visa cannot leave for another employer without starting the visa process over again, employers can give them lower wages than what American workers would receive.

But what about the robots?

Those worried about job competition may have more to lose to a machine. According to a report released this year by the McKinsey Global Institute, the speed and extent of automation will be most affected by these five factors: technical feasibility; cost of developing and deploying solutions; labor market dynamics; economic benefits of automation; and social and regulatory acceptance.

Who Will be Affected?

Hardly any sector, from manufacturing and food service to law and medicine, is immune to automation. (Speaking of medicine, McKinsey’s report mentioned an anecdote about a case of rare leukemia, which eluded doctors for months, that was diagnosed by IBM’s Watson within 10 minutes.)

Figures vary on what percentage of jobs can be fully or partially automated. According to McKinsey’s own recent study of 80% of the global labor force across 46 countries, less than 5% of occupations can be entirely automated. However, 60% of occupations have “at least 30% of automatable activities,” and almost half of work activities have the potential to be automated with current technology. Some 1.2 billion workers and $14.6 trillion in wages are involved in “technically automatable activities.”

Other studies suggest that a larger share of jobs have potential for automation (or are at risk of, depending on where you stand). A 2013 analysis of the U.S. labor market found that 47% of U.S. occupations are at high risk of automation over the next two decades.

McKinsey’s research shows that there is a slight correlation between hourly wage and automation potential. Work activities of people in the lowest wage group, defined as earning less than $15 an hour, have the highest rate of automation potential (51%). That rate falls to 46% for those whose hourly wages are between $15 and $30.

What About the Procurement Profession?

Instead of guessing how well a robot can do the job of, say, an insurance underwriter, McKinsey focused on analyzing work activities. They found that predictable physical labor (unsurprisingly) had the highest potential for automation, but so did data collection and processing. Managing other people and applying expertise in the form of decision-making or planning were among the tasks least susceptible to automation.

Now if we look at the procurement and supply chain profession, different positions can differ considerably in what percentage of their tasks are automatable. The job description for an entry-level supply chain analyst position may include gathering data on the organization’s supply chain operations and conducting analysis; suggesting improvements; and negotiating supplier contracts. Data collection as a job duty would be highly susceptible to automation. Negotiating contracts? Less so. Then consider the typical job responsibilities of a supply chain director, which would likely include the less automatable tasks of managing a team and making big decisions.

There are numerous other relevant factors, of course, such as job location (countries with larger workforce and more advanced economies have more automation potential) and social acceptance (nurses, for example, are unlikely to be replaced by robots). There is also the possibility that more jobs will open up in a given sector, as a result of growing demand, even as the sector becomes more automated.

Technological savviness and the ability to work with machines are likely to count among the most in-demand skills in a more automated world. But also in high demand will be so-called “human” skills, such as social and emotional intelligence, as those are much more difficult for a machine to replicate. As the McKinsey report put it, “tighter integration with technology will free up time for human workers including managers to focus more fully on activities to which they bring skills that machines have yet to master.”

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