Research shows 60% of jobs can be 30% automated. How about yours?
It is hard to imagine the number of jobs that have are able to be automated and digitized.
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It is hard to imagine the number of jobs that have are able to be automated and digitized. It may seem like an elusive concept with no clear starting point or even what is technically possible. But this is exactly where Grexx can make a difference something about!
The American consulting giant McKinsey, led by James Manyika, conducted years of research studying automating and digitalizing tasks titled, A Future That Works: automation, employment and productivity (2017). Their findings include compelling data on digital transformation still relevant today, even though it was published some years ago. And if you have even a handful of knowledge about what has been added in terms of technological developments in recent years, it’s still safe to say that the impact outlined in 2017 will only grow more in 2023. McKinsey revisited this topic in June 2023, but more on that later!
At Grexx, of course, we love these kinds of studies. They may be rather bulky and lengthy publications, which is why we are pleased to highlight some of them for you in this article. You can also find these findings in McKinsey's publications Four fundamentals of workplace automation (2015) and Where machines could replace humans - and where they can’t (yet) (2016). of which are worthwhile reads.
The labor market in focus.
The researchers analyzed the US labor market and selected roughly 800 dead-end jobs and about 2,000 tasks that are found throughout these occupations. They represent these findings in the chart below:
• In the left column, the list of occupations: including salespeople, hospitality workers, teachers, and health care workers
• In the middle column, the tasks performed by these professionals: for example, salespeople welcome customers, answer questions about products and services, keep the workplace tidy, give product demos and process sales and transaction.
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The researchers analysed those 2,000 tasks and identified the necessary capabilities, or skills, needed as a human (or machine!) to perform the task well.
- In the right-hand column, you will find 18 different capabilities, divided into three categories: social, cognitive, and physical skills.
This analysis focuses on the American job market, outlining tasks and competencies required for many jobs. With that information, it can then be concluded which part of the job can be replaced by technology.
Technology is constantly evolving.
In the span of six years between 2017 and 2023, the number of capabilities in which technology can play a role has increased significantly. One obvious example is developments in AI and language modeling. In 2015, when we started, ChatGPT did not exist and neither could we imagine such a system.
Recently, McKinsey returned to this 2017 report in a new study on generative AI, The economic potential of generative AI: The next productivity frontier (2023). It became clear that much more is now possible than was thought at the time of the earlier study in 2017. The proportion of skills that can be automated is rising substantially, and faster than expected. The report also indicates that the adoption of these new techniques is still considerably slow. In other words, there is a wealth of potential, but we are still doing relatively little with it.
💡 Want to read more about the impact of generative AI? You can download the report here and on page 34, you can read more about what has been discussed above.
It’s important to note that since the 2017 study, there have been a) numerous new developments in all sorts of areas and b) there are also developments that you are not yet aware exist. As the technology continues to evolve, the number of capabilities that can be filled by technology will only continue to increase.
Automating capabilities.
The next step in the research is to determine to what extent capabilities and thus jobs or sectors can be automated. This is not a simple task, as it often depends on several factors. For example, in principle, it is quite feasible to develop a machine that can stack objects. But should that stacking be done in an unpredictable environment, such as a busy construction site? Then that machine needs very different skills than in a controlled environment.
McKinsey obviously took that into account. In Where machines could replace humans - and where they can’t (yet) they displayed their findings below:
• Displayed vertically are the series of sectors (construction, retail, finance, healthcare, etc.)
• Horizontally, there is a mix of different work (management, expertise, unpredictable physical work, etc.)
• The colored spheres indicate the degree to which the work can be automated: from cool blue (barely automatable) to warm red (very automatable). The size of the sphere indicates how much manpower is currently engaged in that task.
• The gray bars on the right summarize things, with a percentage of automation potential.
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It shows that most sectors are easily at a potential of 40+ percent automation. Of particular interest then are the big spheres (lots of hours of labor) and the blue spheres (lots of automation possible). Does your organization have large red spheres? Then automation is the jackpot. If you mainly have small blue spheres, then automation is logically a lot less interesting.
45% of the work is to digitalize tasks.
We are happy to share a few more interesting statistics from the survey:
• Roughly 45% of all work can be automated. As technology that can process natural language (think language models like ChatGPT) approaches human-level proficiency (we're a long way off!), this percentage increases to 58%.
• Interestingly, there are very few jobs where 100% automation is preferred. Only 5% of jobs can be fully automated.
• 60% of jobs are more than 30% automated.
• And logically, the use of experts combined with software gives the optimal mix.
💡 Want to play with this dataset yourself?Check Where machines could replace humans - and where they can’t (yet)
This blog post has focused on a number of McKinsey publications, but it is worth noting that these predictions are widely shared among a legion of reputable sources, for example, Goldman Sachs writes in their article Generative AI could raise global GDP by 7 percent (2023) that two-thirds of jobs could be at least partially automated by AI.
What’s next?
Digitalization deserves a place at the top of the management agenda. Of course, it is up to your team to flesh out the details. This survey gives you a clear starting picture of what is possible.
Perhaps you already have a strong digital transformation strategy in place for your organization that addresses these issues. If not, it’s time to prioritize it, because your competitors are most likely doing so.
And just imagine getting ahead of the competition. Can you imagine what that could mean for your productivity, effectiveness, competitive position, innovation, and budgets?
At Grexx, we have plenty of ideas about how to make digitalization a top priority for your organization. Contact one of our experts for information or schedule a no-obligation discovery call. We'd love to show you what's possible and give you honest advice on digital transformation.
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