Construction Industry Economics and Policy: July 2018

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.

Construction Industry Economics and Policy

Sunday, 8 July 2018

Two Reports on the Future of Construction