Where machines could replace humans—and where they can’t (yet)
PART
II
Activities and sectors in the middle range for automation
Across all occupations
in the US economy, one-third of the time spent in the workplace involves
collecting and processing data. Both activities have a technical potential for
automation exceeding 60 percent. Long ago, many companies automated activities such
as administering procurement, processing payrolls, calculating
material-resource needs, generating invoices, and using bar codes to track
flows of materials. But as technology progresses, computers are helping to
increase the scale and quality of these activities. For example, a number of
companies now offer solutions that automate entering paper and PDF invoices
into computer systems or even processing loan applications. And it’s not just
entry-level workers or low-wage clerks who collect and process data; people
whose annual incomes exceed $200,000 spend some 31 percent of their time doing
those things, as well.
Financial services and
insurance provide one example of this phenomenon. The world of finance relies
on professional expertise: stock traders and investment bankers live off their
wits. Yet about 50 percent of the overall time of the workforce in finance and
insurance is devoted to collecting and processing data, where the technical
potential for automation is high. Insurance sales agents gather customer or
product information and underwriters verify the accuracy of records. Securities
and financial sales agents prepare sales or other contracts. Bank tellers
verify the accuracy of financial data.
As a result, the
financial sector has the technical potential to automate activities taking up
43 percent of its workers’ time. Once again, the potential is far higher for
some occupations than for others. For example, we estimate that mortgage
brokers spend as much as 90 percent of their time processing applications.
Putting in place more sophisticated verification processes for documents and
credit applications could reduce that proportion to just more than 60 percent.
This would free up mortgage advisers to focus more of their time on advising
clients rather than routine processing. Both the customer and the mortgage
institution get greater value.
Other activities in the
middle range of the technical potential for automation involve large amounts of
physical activity or the operation of machinery in unpredictable environments.
These types of activities make up a high proportion of the work in sectors such
as farming, forestry, and construction and can be found in many other sectors
as well.
Examples include
operating a crane on a construction site, providing medical care as a first
responder, collecting trash in public areas, setting up classroom materials and
equipment, and making beds in hotel rooms. The latter two activities are
unpredictable largely because the environment keeps changing. Schoolchildren
leave bags, books, and coats in a seemingly random manner. Likewise, in a hotel
room, different guests throw pillows in different places, may or may not leave
clothing on their beds, and clutter up the floor space in different ways.
These activities, requiring
greater flexibility than those in a predictable environment, are for now more
difficult to automate with currently demonstrated technologies: their
automation potential is 25 percent. Should technology advance to handle
unpredictable environments with the same ease as predictable ones, the
potential for automation would jump to 67 percent. Already, some activities in
less predictable settings in farming and construction (such as evaluating the
quality of crops, measuring materials, or translating blueprints into work
requirements) are more susceptible to automation.
Activities with low technical potential for automation
The hardest activities
to automate with currently available technologies are those that involve
managing and developing people (9 percent automation potential) or that apply
expertise to decision making, planning, or creative work (18 percent). These
activities, often characterized as knowledge work, can be as varied as coding
software, creating menus, or writing promotional materials. For now, computers
do an excellent job with very well-defined activities, such as optimizing
trucking routes, but humans still need to determine the proper goals, interpret
results, or provide commonsense checks for solutions. The importance of human
interaction is evident in two sectors that, so far, have a relatively low
technical potential for automation: healthcare and education.
Overall, healthcare has
a technical potential for automation of about 36 percent, but the potential is
lower for health professionals whose daily activities require expertise and
direct contact with patients. For example, we estimate that less than 30 percent
of a registered nurse’s activities could be automated, based on technical
considerations alone. For dental hygienists, that proportion drops to 13
percent.
Nonetheless, some
healthcare activities, including preparing food in hospitals and administering
non-intravenous medications, could be automated if currently demonstrated
technologies were adapted. Data collection, which also accounts for a
significant amount of working time in the sector, could become more automated
as well. Nursing assistants, for example, spend about two-thirds of their time
collecting health information. Even some of the more complex activities that
doctors perform, such as administering anesthesia during simple procedures or
reading radiological scans, have the technical potential for automation.
Of all the sectors we
have examined, the technical feasibility of automation is lowest in education,
at least for now. To be sure, digital technology is transforming the field, as
can be seen from the myriad classes and learning vehicles available online. Yet
the essence of teaching is deep expertise and complex interactions with other
people. Together, those two categories—the least automatable of the seven
identified in the first exhibit—account for about one-half of the activities in
the education sector.
Even so, 27 percent of
the activities in education—primarily those that happen outside the classroom
or on the sidelines—have the potential to be automated with demonstrated
technologies. Janitors and cleaners, for example, clean and monitor building
premises. Cooks prepare and serve school food. Administrative assistants
maintain inventory records and personnel information. The automation of these
data-collection and processing activities may help to reduce the growth of the
administrative expenses of education and to lower its cost without affecting
its quality.
Looking ahead
As technology develops,
robotics and machine learning will make greater inroads into activities that
today have only a low technical potential for automation. New techniques, for
example, are enabling safer and more enhanced physical collaboration between
robots and humans in what are now considered unpredictable environments. These
developments could enable the automation of more activities in sectors such as
construction. Artificial intelligence can be used to design components in
engineer-heavy sectors.
One of the biggest
technological breakthroughs would come if machines were to develop an
understanding of natural language on par with median human performance—that is,
if computers gained the ability to recognize the concepts in everyday
communication between people. In retailing, such natural-language advances
would increase the technical potential for automation from 53 percent of all
labor time to 60 percent. In finance and insurance, the leap would be even
greater, to 66 percent, from 43 percent. In healthcare, too, while we don’t
believe currently demonstrated technologies could accomplish all of the
activities needed to diagnose and treat patients, technology will become more
capable over time. Robots may not be cleaning your teeth or teaching your
children quite yet, but that doesn’t mean they won’t in the future.
As stated at the
outset, though, simply considering the technical potential for automation is
not enough to assess how much of it will occur in particular activities. The
actual level will reflect the interplay of the technical potential, the
benefits and costs (or the business case), the supply-and-demand dynamics of
labor, and various regulatory and social factors related to acceptability.
Leading more automated enterprises
Automation could
transform the workplace for everyone, including senior management. The rapid
evolution of technology can make harnessing its potential and avoiding its
pitfalls especially complex. In some industries, such as retailing, automation
is already changing the nature of competition. E-commerce players, for example,
compete with traditional retailers by using both physical automation (such as
robots in warehouses) and the automation of knowledge work (including
algorithms that alert shoppers to items they may want to buy). In mining,
autonomous haulage systems that transport ore inside mines more safely and
efficiently than human operators do could also deliver a step change in
productivity.
Top executives will
first and foremost need to identify where automation could transform their own
organizations and then put a plan in place to migrate to new business processes
enabled by automation. A heat map of potential automation activities within
companies can help to guide, identify, and prioritize the potential processes
and activities that could be transformed. As we have noted, the key question
will be where and how to unlock value, given the cost of replacing human labor
with machines. The majority of the benefits may come not from reducing labor
costs but from raising productivity through fewer errors, higher output, and
improved quality, safety, and speed.
It is never too early
to prepare for the future. To get ready for automation’s advances tomorrow,
executives must challenge themselves to understand the data and automation
technologies on the horizon today. But more than data and technological savvy
are required to capture value from automation. The greater challenges are the
workforce and organizational changes that leaders will have to put in place as
automation upends entire business processes, as well as the culture of
organizations, which must learn to view automation as a reliable productivity
lever. Senior leaders, for their part, will need to “let go” in ways that run
counter to a century of organizational development.5
Understanding the
activities that are most susceptible to automation from a technical perspective
could provide a unique opportunity to rethink how workers engage with their
jobs and how digital labor platforms can better connect individuals, teams, and
projects.6 It could also inspire top
managers to think about how many of their own activities could be better and
more efficiently executed by machines, freeing up executive time to focus on
the core competencies that no robot or algorithm can replace—as yet.
By Michael
Chui, James Manyika, and
Mehdi Miremadi
https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet
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