Reassessing the Internet of Things
AUG 6, 2015
SAN FRANCISCO – Nearly 30 years ago, the economists Robert Solow and Stephen Roach
caused a stir when they pointed out that, for all the billions of
dollars being invested in information technology, there was no evidence
of a payoff in productivity. Businesses were buying tens of millions of
computers every year, and Microsoft had just gone public, netting Bill
Gates his first billion. And yet, in what came to be known as the
productivity paradox, national statistics showed that not only was
productivity growth not accelerating; it was actually slowing down. “You
can see the computer age everywhere,” quipped Solow, “but in the productivity statistics.”
Today, we seem to be
at a similar historical moment with a new innovation: the much-hyped
Internet of Things – the linking of machines and objects to digital
networks. Sensors, tags, and other connected gadgets mean that the
physical world can now be digitized, monitored, measured, and optimized.
As with computers before, the possibilities seem endless, the
predictions have been extravagant – and the data have yet to show a
surge in productivity.
A year ago, research firm Gartner put the Internet of Things at the peak of its Hype Cycle of emerging technologies.
As more doubts about
the Internet of Things productivity revolution are voiced, it is useful
to recall what happened when Solow and Roach identified the original
computer productivity paradox. For starters, it is important to note
that business leaders largely ignored the productivity paradox,
insisting that they were seeing improvements in the quality and speed of
operations and decision-making. Investment in information and
communications technology continued to grow, even in the absence of
macroeconomic proof of its returns.
That turned out to be the right response. By the late 1990s, the economists Erik Brynjolfsson
and Lorin Hitt had disproved the productivity paradox, uncovering
problems in the way service-sector productivity was measured and, more
important, noting that there was generally a long lag between technology
investments and productivity gains.
Our own research at
the time found a large jump in productivity in the late 1990s, driven
largely by efficiencies made possible by earlier investments in
information technology. These gains were visible in several sectors,
including retail, wholesale trade, financial services, and the computer
industry itself. The greatest productivity improvements were not the
result of information technology on its own, but by its combination with
process changes and organizational and managerial innovations.
Our latest research, The Internet of Things: Mapping the Value Beyond the Hype, indicates
that a similar cycle could repeat itself. We predict that as the
Internet of Things transforms factories, homes, and cities, it will
yield greater economic value than even the hype suggests. By 2025,
according to our estimates, the economic impact will reach $3.9-$11.1
trillion per year, equivalent to roughly 11% of world GDP. In the
meantime, however, we are likely to see another productivity paradox;
the gains from changes in the way businesses operate will take time to
be detected at the macroeconomic level.
One major factor
likely to delay the productivity payoff will be the need to achieve
interoperability. Sensors on cars can deliver immediate gains by
monitoring the engine, cutting maintenance costs, and extending the life
of the vehicle. But even greater gains can be made by connecting the
sensors to traffic monitoring systems, thereby cutting travel time for
thousands of motorists, saving energy, and reducing pollution. However,
this will first require auto manufacturers, transit operators, and
engineers to collaborate on traffic-management technologies and
protocols.
Indeed, we estimate
that 40% of the potential economic value of the Internet of Things will
depend on interoperability. Yet some of the basic building blocks for
interoperability are still missing. Two-thirds of the things that could
be connected do not use standard Internet Protocol networks.
Other barriers
standing in the way of capturing the full potential of the Internet of
Things include the need for privacy and security protections and long
investment cycles in areas such as infrastructure, where it could take
many years to retrofit legacy assets. The cybersecurity challenges are
particularly vexing, as the Internet of Things increases the
opportunities for attack and amplifies the consequences of any breach.
But, as in the 1980s,
the biggest hurdles for achieving the full potential of the new
technology will be organizational. Some of the productivity gains from
the Internet of Things will result from the use of data to guide changes
in processes and develop new business models. Today, little of the data
being collected by the Internet of Things is being used, and it is
being applied only in basic ways – detecting anomalies in the
performance of machines, for example.
It could be a while
before such data are routinely used to optimize processes, make
predictions, or inform decision-making the uses that lead to
efficiencies and innovations. But it will happen. And, just as with the
adoption of information technology, the first companies to master the
Internet of Things are likely to lock in significant advantages, putting
them far ahead of competitors by the time the significance of the
change is obvious to everyone.
Martin Neil Baily is Chair in Economic
Policy Development and Senior Fellow and Director of the Business and
Public Policy Initiative at the Brookings Institution.
James Manyika is a director of the
McKinsey Global Institute (MGI), McKinsey & Company’s business and
economics research arm, and a non-resident fellow at the Brookings
Institution.
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