How Rapidly Will New Technology Spread Across an Industry?
One of the
underlying ideas here is that the industry we call ‘construction’ is a
‘technological system’, a densely connected network of firms and organizations
that produces and maintains the built environment. This system can be divided
into three different levels (local, national and global) and three distinct
sub-sectors (residential and non-residential building and engineering
construction), each with their own characteristics and therefore each with
their own development trajectory. The driver of these differing development
trajectories will be how rapidly firms adopt the range of new twenty-first
century technologies now emerging.
These technologies
will greatly enhance our abilities to reorder the physical world, the ultimate
purpose of a technological system. These abilities are increasing through
continued improvement in hardware, both mechanical and silicon, and software,
with new applications and programs and the development of machine intelligence.
How firms
use technology, in the way it is adopted, adapted and applied, varies widely
within the construction technological system, and this is a significant driver
of change. After 100 years the construction technological system is well
developed, and as a mature system it is also conservative. Mature technological
systems accumulate capital and skills, and this investment in the existing
system gives it great inertia until some disruptive change emerges. How and why
a new technology spreads through the economy and society are determined by many
factors, but studies of historical cases like steam power, tractors,
electricity, phones and the internet have given us good examples of technology
diffusion and its dynamics.
The rate of adoption of
technologies within the firms that make up an industry, which is affected by a
range of factors, has also been studied. The technology adoption literature
discusses rank effects, which are the different individual characteristics of firms
such as their size, and how they affect the rate and extent of adoption of new
technologies, also the effects of competitive dynamics, which is how the
adoption of new technology by one company in an industry influences the
adoption of technology by other companies in that industry.
From economic history, we know major new
technologies take time to diffuse through the economy because they require
parallel changes in forms of organization, methods of production and patterns
of consumption. These are not decisions firms and households make quickly or
easily, due to the investment in upgrading machinery and equipment usually needed.
New technologies are ‘embodied’ in this new physical capital, in the way a 20
year old car incorporates the technology of two decades ago when it was made. In
the literature there are many studies of the introduction of new technologies,
and the consensus is that it typically takes 15 to 30 years for a new
technology to reach 90 percent of its potential market. A well-known
example is Paul David’s research on electrification in the US, which took 30
years from 1900 because of the fundamental
changes industry and households needed to make to take advantage of electrical
power.
Another good example is tractors. The figure below shows the tractor slowly displacing horses and mules in US agriculture from 1910 to 1960. Horses and mules declined from about 26 million in 1920 to about 3 million by 1960, while the number of tractors rose from zero in 1910 to 4.5 million by 1960. One reason for the slow spread of tractors was the incremental innovation needed to increase their capabilities, which made them more attractive over time. A second was an increase in farm wages after 1940, which made tractors more economic.
The spread
of new technologies through society and the economy often takes longer than
expected, based on the benefits the new tech typically brings. Paul David observed
many people "lose a proper sense of the complexity and historical
contingency of the processes involved in technological change and the
entanglement of the latter with economic, social, political, and legal
transformations. There is no automaticity in the implementation of a new
technological paradigm, such as that which we presently discern is emerging
from the confluence of advances in computer and communications
technologies." The same could be said today about the advances in machine
learning and artificial intelligence.
Generally, discussion of construction industry development over the next decade
shares a view that the impacts of new technology, including BIM, will
be gradual, changing industry practice over time without significantly
affecting industry structure or dynamics. Given the entanglement of economic,
social, political, and legal factors in the construction technological system
this might be the case, however there are good reasons to think this may
be wrong because these studies either predate the current surge in machine
learning or do not consider the potential of AI. Machine learning, AI,
automation and robotics are an interconnected set of technologies that are
evolving quickly, enabled by expanding connectivity and the massively scaleable
hardware available today.
Technologies have to be adapted
into solutions for specific tasks, with their role in the workplace evolving
over time as machines reach the levels of performance required. Only when their
cost is low
enough will they be adopted, but developing and engineering new technologies takes time
and money. Once established, the single most important factor in
technology uptake is the price/performance relationship, or the gain in
productivity or other measure (time, quality, safety) the new technology
delivers for a given level of investment. To successfully displace an older
technology a new technology often has to provide an overwhelming economic
advantage to overcome the inbuilt conservatism of an existing industry, due to
the investment by incumbents in the current system. This is a significant
barrier because, at present, the price/performance trade-off is not there for
the many small firms in building and construction because the investment required to upgrade capability is too
large for the size of these firms. However, for larger firms the issue is not
whether to invest, in BIM for example, but how much, if they intend to compete in the
upgraded and modified category of firms in the industry.
A period of technology-driven restructuring of the building and construction industry may be about to start, similar to the second half of the 1800s when the new materials of glass, steel and reinforced concrete arrived, which led to new methods of production, organization and management. There are many implications of such a restructuring. Some firms are rethinking their processes in response to developments in AI, robotics and automation as capabilities improve quickly and the range of new products using these technologies expands. Many firms, however, are not. Meanwhile, frontier firms are exploring new tech and pushing the boundaries of what is possible, and are inventing new processes.
There is understandable skepticism across the industry about the extent of impact of new technology, the ‘business as usual’ approach has worked well for many firms. With the characteristic changeability of construction sites particularly challenging for automated and robotic systems, it might take decades of investment for machines to learn how to do site work. On the other hand, once a robotic system has learned how to do something, that skill can be copied and replicated at minimal cost, and that applies as much to engineers, architects, quantity surveyors, urban planners and project managers as it does to crane drivers, bricklayers and electricians.
A period of technology-driven restructuring of the building and construction industry may be about to start, similar to the second half of the 1800s when the new materials of glass, steel and reinforced concrete arrived, which led to new methods of production, organization and management. There are many implications of such a restructuring. Some firms are rethinking their processes in response to developments in AI, robotics and automation as capabilities improve quickly and the range of new products using these technologies expands. Many firms, however, are not. Meanwhile, frontier firms are exploring new tech and pushing the boundaries of what is possible, and are inventing new processes.
There is understandable skepticism across the industry about the extent of impact of new technology, the ‘business as usual’ approach has worked well for many firms. With the characteristic changeability of construction sites particularly challenging for automated and robotic systems, it might take decades of investment for machines to learn how to do site work. On the other hand, once a robotic system has learned how to do something, that skill can be copied and replicated at minimal cost, and that applies as much to engineers, architects, quantity surveyors, urban planners and project managers as it does to crane drivers, bricklayers and electricians.
Rodolfo E. Manuelli and Ananth Seshadri 2014. Frictionless
Technology Diffusion: The Case of Tractors, American Economic Review.
Paul David 1991. Computer and Dynamo: The Modern Productivity Paradox in a Not-too-Distant Mirror, in Technology and Productivity: The Challenge for Economic Policy. OECD.
Paul David 1991. Computer and Dynamo: The Modern Productivity Paradox in a Not-too-Distant Mirror, in Technology and Productivity: The Challenge for Economic Policy. OECD.
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