Construction Scenarios: AI and Technological Opportunity
In one of those interesting
accidents of timing, reports from the two leading management consultancies on
the future of construction were released within days of each other. These are briefly
summarised below. Also, some quotes from interviews with people on new technology
and their projects, with some comments and observations to close.
From management consultants
McKinsey comes the latest in their series of reports on technology and construction,
this one titled Artificial Intelligence: Construction Technology’s Next Frontier,
the first major publication specifically on the industry-wide implications of
AI that I know of. This is one of a series of recent papers on AI, automation and infrastructure.
The World Economic Forum and the
Boston Consulting Group released their Shaping
the Future of Construction report
in 2016, with some interesting examples of frontier firms. They have published
a scenario analysis as the second, final step in their Future of Construction
project, which has involved people from industry and researchers from a wide
range of organizations. The three Future Scenarios they describe make
technological context central to the future form of the industry.
As an adjunct to these two
reports, the views and comments by the managers in their interviews in
Infrastructure Intelligence’s Toward Digital Transformation provide
a nice counterpoint to the somewhat stilted language found in management
consultese. All three were published simulaneously and contain a lot of boilerplate about change management,
agility, recruitment and talent management but, despite the importance of organizational
structure and the development of skills if you want to compete for the future, this is not discussed here.
*
McKinsey identifies five AI-powered applications, and use cases that have
already arrived in other industries, that can be applied to construction. This
is a practical approach that seems to target major contractors, and is a
different approach to previous reports that could have been primarily intended
for public sector clients. McKinsey has been seriously developing their
infrastructure practice for some years now, positioning themselves for the
global infrastructure boom they forecast over the next few decades. The five
industry applications are:
Transportation route optimization algorithms for project
planning optimization;
Pharmaceutical outcomes prediction for constructability
issues;
Retail supply chain optimization for materials and
inventory management;
Robotics for modular or prefabrication construction and
3-D printing;
Healthcare image recognition for risk and safety
management.
Each
of these has a short discussion with some nice examples of crossover potential.
They are all plausible extensions of current technology, and in robotics, 3-D
printing and drones leading construction firms are already well advanced. Using
AI for optimization is obvious, but it is just as likely construction
contractors will be using logistics firms to manage transport and inventory as
they are to invest in the hardware and software development needed. The
question is whether this makes a convincing case for using AI in construction, or
whether these are the pathways into construction for AI, or the only ones.
McKinsey
also looks at some machine learning algorithms that are more relevant to
contractors, and briefly assesses their potential
engineering and construction applications. Despite their extensive reporting on
BIM elsewhere there is no discussion of the potential use of AI in design and
engineering, or in restructuring processes. They do have a good, generic
framework for types of machine learning, and they suggest algorithms will be useful for:
Refining
quality control and claims management
Increasing
talent retention and development
Boosting
project monitoring and risk management
Constant
design optimization
And then there’s this:
industry
insiders need to look beyond sector borders to understand where incumbents are
becoming more vulnerable and to identify white space for growth. Both owners
and E&C firms can explore nontraditional partnerships with organizations
outside the industry to pool advanced R&D efforts that have multiple
applications across industries.
Not coincidentally, McKinsey might be able
to arrange introductions and facilitate ‘exploration’ and, like many McKinsey
papers, this one reads a bit like a catalogue. However, where the previous reports
in this series have emphasised industry problems, using consolidated industry
data from their client base, this one is full of solutions. While some of these
may be solutions looking for problems there are, nonetheless, many acute
observations in this paper on the range of possibilities AI will offer in the
near future. They have put out a stream of reports on AI over the last few
years.
This is a short paper and light on detail. If
McKinsey has a more interesting story to tell on pathways for AI into
construction it might look something like the scenarios depicted in the WEF/BCG
paper. They use the term Infrastructure and Urban Development Industry (IU) to
describe what I call the Built Environment Sector:
The scenarios
depict three extreme yet plausible versions of the future. In Building in a
virtual world, virtual reality touches all aspects of life, and
intelligent systems and robots run the construction industry. In Factories run the
world, a corporate-dominated society uses prefabrication and
modularization to create cost-efficient structures. In A green reboot,
a world addressing scarce natural resources and climate change rebuilds using
eco-friendly construction methods and sustainable materials. It is important to
keep in mind that the scenarios are not predictions of the future. Rather, they
demonstrate a broad spectrum of possible futures. In the real future, the IU
industry will most probably include elements of all three.
Each scenario is used to extrapolate implications
for the industry, identifying potential winners from technological
transformation, and the range of examples and ideas shows the value of such a widespread
collaboration between industry, government and academia. The WEF does not say
how far into the future they are looking, although it seems a fair bet that it
is a lot further than McKinsey.
Building in a virtual world
Interconnected
intelligent systems and robots run IU
Software players will
gain power
New businesses will
emerge around data and services
Factories run the world
The entire IU value
chain adopts prefabrication, lean processes and mass customization
Suppliers benefit the
most from the transition
New business opportunities through integrated
system offerings and logistics requirements
A green reboot
Innovative technologies, new materials and
sensor-based surveillance ensure low environmental impacts
Players with deep knowledge of materials and
local brownfield portfolios thrive
New business opportunities around environmental-focused
services and material recycling
*
What to make of all this?
Scenarios can be useful thought experiments, but by their nature are limited
because the futures they depict are typically extensions of the present.
Tomorrow will be like today, only more so. And saying AI will be important in
the near future is not particularly insightful, although for some construction
managers may be necessary. Some, however, are already working with digital-twin
projects and restructuring around technological opportunity, as the quotes from
Infrastructure Intelligence’s Digital Transformation
interviews below indicate:
London’s Crossrail and Malaysia’s
Mass Rapid Transit Corporation are two examples that show how “visionary
transportation owners and supply chains are embracing digital technology”, ”moving
beyond 3D modelling and 2D deliverables to enable handover of digital as-built
information to operations.” Steve Cockerell – Bentley Systems
“BIM Wednesdays, where each
Wednesday we got together in a location or had people Skype call in and view
models on smartboards. This meant that when we got to the point of submission
we had collectively resolved all the issues”. Mert Yesugey – Mott MacDonald
“Not knowing where to start is
something we hear often. Just being so overwhelmed with all the technology
that’s available and all the workflow processes. The lessons that we’ve learned
are you must start small with tangible pilots and attack one part of the
workflow at a time, implement technology, create a feedback loop and be able to
measure what’s working and what’s not.” Sasha Reed – Blackbeam
David Waboso
of Network Rail on procurement
based on whole of asset life and outcome based contracts, focusing on in-service
performance and outputs. An example is Resonate’s “Luminate” digital train
management system, “a novel form of contracting that needs only a small upfront
investment and is based a shared benefits agreement whereby the supplier will
be rewarded if the new system delivers performance improvements and a
corresponding reduction in delay compensation payments.”
*
So where is the industry at in
regard to technology take-up, now that there is widespread recognition of the
reality of a digital future? Will construction industry development over the
next decades absorb the impacts of new technology and 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. 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.
If we think of the structure of
the industry as a pyramid, there is a broad base of tradesmen and small firms
at the bottom, followed by a deep layer of medium sized firms, and a small top
section with a few large firms. Those large firms and some of their clients are
clearly on the technological frontier, and their investment in capability and
capacity should deliver significant increases in efficiency and productivity,
and probably scale. Some medium-size firms are also making these investments,
and also have access to technologies like algorithmic optimisation,
platform-based project management, robotic, VR and AR applications and so on.
The WEF/BCG Shaping the Future of
Construction report, which is now nearly two years old, included many
snapshots of what a range of firms at the frontier were doing, and some are in the table
below. These sort of examples are missing from McKinsey’s high level analysis,
and reflect the diversity of the industry beyond McKinsey’s potential client
base.
Shaping the Future: Technology,
materials and tools in 2016
Company
|
Example
|
Fluor (US)
|
has built up an
internal team of experts on concrete to advise the client at an early
planning stage, to develop a foundation of data based on experience and to
create a convincing business case for greater use of innovations (such as
50%-faster-curing concrete) in the market.
|
BASF and Arup (Europe)
|
have jointly
developed an app for architects, engineers and project owners to calculate
the energy savings achievable from the latent-heat storage system Micronal.
|
Skanska (Swedish)
|
has developed a new
construction concept known as “Flying Factories”, which are temporary
factories set up close to construction sites; they apply “lean” manufacturing
techniques and employ local semi-skilled labour. The advantages include a
reduction in construction time of up to 65%, a halving of labour costs and a
44% improvement in productivity.
|
Broad Group (China) with ArcelorMittal (India)
|
is using a system of
modular building components that enables very speedy construction: a
57-storey building was built in 19 days by moving 90% of the construction
work to the factory.
|
Komatsu (Japan)
|
is developing
automated bulldozers incorporating various digital systems. Drones, 3D
scanners and stereo cameras gather terrain data, which is then transmitted to
the bulldozers; these are equipped with intelligent machine-control systems
that enable them to carry out their work autonomously and thereby speed up
the pre-foundation work on construction sites, while human operators monitor
the process. On mining sites, autonomous haul trucks are already in common
use.
|
Win Sun (China)
|
has been building 10
houses a day by using 3D-printed building components, and has concluded a
deal with the Egyptian government for 20,000 single-storey dwellings
leveraging this technology.
|
Skanska
|
and its partners are
pioneering the wireless monitoring of buildings, using sensors to record data
(such as temperature and vibration), and wireless equipment to store and
transmit this data. Data analytics are applied to determine the implications
of any changes in the sensor readings. These smart-equipment technologies
have the potential to reduce unexpected failure by 50%, improve building-management
productivity by 20-30% thanks to less need for inspections, and improve the
building’s energy performance by 10% over its lifetime.
|
Atkins
|
has implemented advanced parametric design
techniques for detailed design “optioneering” in the water infrastructure
industry. That has made it possible to provide 22 design options in one day,
a 95% time improvement on traditional design methods for similar results.
|
Arup
|
combines various
data-collection methods, including mobile surveys, security-camera footage
and traffic-flow reports, for improved decision-making in the design of
residential projects.
|
Skanska
|
is developing a Tag & Tack system, pioneering
the use of radio frequency identification (RFID) tags and barcodes on
products and components in construction projects for real-time monitoring of
delivery, storage and installation, the new system is achieving reductions of
up to 10% in construction costs.
|
Source; WEF
Based on these examples, the
level of technology use in construction, compared to advanced manufacturing
techniques in 2016, is well behind. Companies in the aerospace or automotive
industries have developed their automated factories, integration capabilities
and use of new materials like carbon fibre. Adidas makes 300 million shoes a
year and in 2017 opened a fully automated factory in Germany. There are many
examples. The lag is primarily due to the dynamic of a project-based industry,
where it is hard for contractors and consultants to spread costs incurred with
innovation across projects. Consequently, the manufacturers and suppliers of
building and construction products, machinery and equipment do most of the
research and innovation because they, like car companies, can spread the
development costs over many clients. The role of contractors is to seek
efficiencies in delivery, as the examples show. What these examples also show
is that the gap between the industry’s larger, leading edge firms and SMEs is
growing, and can be expected to increase because the great majority of smaller
firms cannot innovate as fast or as effectively as larger firms.
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.
Other relevant posts:
Construction’s three pathways to
the future here
WEF Shaping the future of
construction here
BIM is essential but not
transformational here
Technological diffusion takes
time here
Disruptive change in
construction here
Frontier firms in construction here
