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7.4. Accelerating technology use

Te whakatere ake i te whakamahinga o te hangarau

We need to accelerate the adoption and diffusion of technological and digital change.

A thriving world of innovators are developing technology that can revolutionise the way we plan, design, procure, construct, operate and decommission infrastructure. Digital twins can help our cities work more efficiently. New tunnelling technologies are lowering the cost of construction.423 Crowd sourcing can help speed up maintenance by making it easy for people to report faults like potholes. However, much of the technology we need to transform our infrastructure already exists. There’s limited need for high-risk investments at the cutting edge of technology. New Zealand could see huge benefits through the fast adoption of existing technologies.

Adopting these technologies requires the infrastructure sector to be organised and coordinated so it can seize opportunities as they arise. There’s much to gain. Existing technologies alone have the potential to lift infrastructure service levels for the vulnerable, reduce costs and overruns, improve operations and maintenance and decarbonise with greater speed.

7.4.1. Context


Technology uptake has been slow.

While other industries have embraced new technologies, infrastructure and construction lag. The characteristics of infrastructure can make it more difficult to adopt new technology. The long life of infrastructure can lock in older technologies. The need for a consistent approach across large infrastructure networks like roads and water networks can make it difficult to make incremental change. Fragmented and decentralised ownership or operation can make coordination across much of our infrastructure system expensive and unwieldy. Even so, there are many opportunities for technological change to improve our infrastructure.

Technology can improve productivity and lift service levels.

Technology can enable responsive and intelligent data-driven infrastructure systems. Technological innovation and prosperity are closely linked424 to the adoption of information and communications technologies (ICT), a key determinant of productivity in infrastructure.425 Technology presents New Zealand with an opportunity to address chronic productivity issues in the infrastructure sector. Currently, our construction sector uses ICT less than any other industry.426 While some infrastructure sectors, such as telecommunications and some regions have made considerable progress in technology adoption, others have failed to keep up.

New Zealand is well placed to leverage many of the advances in digital technology that have occurred in the past decade. We’ve built a high-quality broadband network and have coverage that, while not universal, is widespread. Strong market competition in sectors such as energy and telecommunications has proven important in incentivising pockets of technological excellence. New Zealand is also small and agile with a rich history of adopting new digital technologies with speed, dating back as far as 1985, when New Zealand was one of the first countries to adopt a national system of electronic fund transfers (known as EFTPOS).427

7.4.2. What we’ve heard


We’ve heard that industry hasn’t invested significantly in technological advancements for several reasons: its major customers (in many cases, the government) haven’t really demanded it and there has been a lack of certainty about a long-term pipeline of work, as well as serious labour and skills challenges. There is, though, a clear understanding and support for moves toward open data and recognition that common infrastructure metadata standards will be needed if we’re to adopt digital twins and other digital technologies.

Submitters told us that a national digital strategy was needed to galvanise action and drive behaviour change. There was also a need for strong and clear mandated requirements at the procurement stage of a project. These could include requirements for digital modelling, efficiency dividends and decarbonisation that will speed up the adoption of technology across the infrastructure sector. A clearer pipeline of work for several decades to come would help reduce uncertainty and give industry the confidence to increase investment in capabilities and skills.

7.4.3. Strategic direction


Clear strategic direction and leadership

Central leadership and an all-of-government approach are critical to speeding up the use and spread of new technology.

Based on best practice from across the OECD,428 several common themes are key to stronger government leadership in the adoption of new technologies.

A national digital strategy: A clear strategic approach is a powerful lever for shaping a more intelligent and technology-enabled infrastructure system. National digital strategies must provide guidance on the growth and direction of infrastructure technology. The government is currently developing a Digital Strategy for Aotearoa.

Procurement: The government’s procurement and contracting approach can drive the adoption of digital technology and the shared benefits this would offer to major infrastructure programmes. The government is the largest procurer of infrastructure in many sectors. The procurement requirements it sets can ripple through the wider infrastructure system. This means procurement can be used to increase the uptake and maturity of technology across the infrastructure system by:

  • Encouraging vendors with strong technology experience.
  • Setting minimum efficiency dividends for major works.
  • Including carbon emission targets.
  • Requiring regular data on the performance of infrastructure using common standards.

Climate change targets: Clear targets for reducing carbon emissions from infrastructure encourages the use of technology to help address the climate change impacts of infrastructure.

Spatial planning strategies: These can be used to reinforce the greater digitalisation of infrastructure by ensuring that the regulatory framework enables telecommunications and associated providers to invest in the network more easily and efficiently. Regional spatial plans should aspire to give industry more certainty in investing in technology and developing capabilities, particularly when combined with a clear long-term direction on the pipeline of infrastructure work.

Regulation: The legal and regulatory environment for setting and updating technical standards, such as minimum energy performance standards, needs to be responsive to technological change. Regulators must have the power and responsiveness to set standards that reflect this, as well as obligations to review them regularly.

Skills: A key constraint to progressing technology capabilities in the infrastructure space is labour market constraints.429 This is an important part of developing our workforce capacity and capabilities as detailed in Section 7.5.

Data for the public good

Prioritising data across infrastructure industries.

There’s much to be gained from a data-rich infrastructure system. Project selection can be improved through more sophisticated modelling and better assessments of community needs. Entire networks can be better managed through digital twins and real-time pricing. Case Study 15 shows how maintenance can be streamlined through digitised asset management. Digital solutions can also help infrastructure operators and regulators to manage our critical national systems more effectively. Sharing data, with the appropriate security and privacy arrangements in place, can spark innovation and improve outcomes for users. But we’ll only see the real expression of data when it’s readily available.

Case studies

The solutions to the issues we face have often been shown to work here and overseas. These case studies are an example to learn from.

Collaboration and data sharing across the infrastructure industry.

An open-data environment is one where all infrastructure data is available, secure, free of information that could identify an individual and standardised so it can inform decisions. It’s used by operators and can inform machine learning, a process where data is analysed to improve the accuracy of digital technologies. As the value of data grows with rapid digital change, it’s likely that network operators and utilities will benefit from greater sharing of data about infrastructure.431 This is demonstrated in platforms like Port Community Systems, which are neutral and open digital platforms that facilitate automated port processes through intelligent and secure information exchange between all stakeholders.432 While some examples are emerging, this collaboration isn’t yet happening across infrastructure sectors in a coordinated way. Commercial confidentiality often hampers the willingness to share ideas and data. Not all data is or can be open. Some data, such as that which is sensitive or critical, may not be able to be shared widely and may require security mechanisms. At other times, data needs to be anonymised to protect privacy. Despite this, greater progress toward more open data should be made, since optimising our infrastructure investments requires good information about design, construction and operation.

The key elements required to move towards a more open data environment for infrastructure include:

  • The development of common national infrastructure metadata standards, building on existing government initiatives.
  • A clear identification of the ownership of the data, independence for those institutions that have kaitiakitanga over it and capabilities to generate value from its management.
  • Robust cyber security management systems, protocols and safeguards.
  • A balance between leveraging data and protecting the security and privacy of New Zealanders.
  • Trusted stewards and institutions for data.
  • A shift to minimum levels of commercial confidentiality.

“The purpose… is to send a clear message to the Government and private sector. [We] need to open up infrastructure data and make full use of data science and machine learning to get more out of existing infrastructure and to make the right decisions about future infrastructure.” – United Kingdom National Infrastructure Commission433

A move towards open data needs to respect Māori data sovereignty and Te Tiriti o Waitangi.

A shift is currently occurring in the way that mātauranga Māori is accessed, grown and shared intergenerationally. The traditional ways of handing this knowledge forward through whakapapa are being rapidly challenged by digital forms of knowledge.

Infrastructure creates large amounts of data through its operation, maintenance and use. This will continue to increase over the next 30 years. The processing power of artificial intelligence means data and knowledge will be intertwined. This has significance for Māori. Knowledge is taonga and as we look to increase the use of open data in infrastructure, we’ll need to identify the value, ownership and management of data and consider Māori data sovereignty and the principles of Te Tiriti o Waitangi.

Adopting existing technologies

The adoption and spread of existing technologies is a priority.

The key to unlocking the vast productivity, performance and wellbeing benefits of technology isn’t always invention, but speedy adoption, increased certainty and putting in place incentives for technology uptake. A greater use of technology across the infrastructure system can raise productivity and performance, create higher-skilled jobs, build transparency and improve resilience.434

There are well established technologies that could be implemented now in New Zealand’s water, waste, energy, transport, telecommunications, education and health sectors. Key benefits include:

  • Better monitoring and managing of the vast existing infrastructure asset base.
  • Better transport and energy systems to help achieve a net-zero carbon economy by 2050.
  • Reduced demand on the health system and a corresponding demand for health infrastructure by enabling technology-at-distance services like telehealth systems.
  • Faster consenting and development by digitising these processes.

A programme to improve the incentives for adopting new technologies would be a useful first step. The key elements of this are shown in Table 6 and would bring together requirements to build skills, ensure a public sector and industry commitment to growing the infrastructure data available and ultimately, move towards a system of open data where possible. It would also identify opportunities to standardise the way technologies are used to reduce cost barriers by taking advantage of economies of scale. Regulatory and legal frameworks are required to keep pace with new technologies and applications, while also managing security risks.

Building Information Modelling (BIM)

Integrated BIM uses digital 3D models to streamline design processes and manage an integrated design process through centralised data storage. It is envisaged that in the future, integrated BIM will also include cost, time and resource management.

Table 6: Steps to improve the adoption and diffusion of technology

Skills and capabilities

Barrier


Skills and capabilities for design, delivery and operation

Explanation


Developing people’s skills and capabilities for technology development and widespread use in infrastructure, while avoiding market shortages and rising labour costs.

Data

Barrier


How information is generated

Explanation


An open system of infrastructure data can grow the development of technology and the resulting benefits, efficiencies, insights and innovations.

Standardisation

Barrier


Greater diffusion through data standards or common interfaces

Explanation


The standardisation of technologies that can have benefits through widespread adoption, such as digital twins and digital consenting. A common data framework and standard interface can make it easier for individuals and companies to work together.

Commissioning / Procurement

Barrier


Mandatory requirements, selection criteria, conditions and models of contracting

Explanation


Moving from lowest cost to highest value. Setting requirements for digital incentive structures or preferential selection criteria as part of the procurement process. Utilising a mission-based approach (or targets) to motivate greater technology uptake (for instance, net-zero carbon emission by 2050).

Regulatory / Legal

Barrier


Enabling legislation

Explanation


Resolving the regulatory and legal issues that arise from new technologies, such as privacy issues (for instance, the collection of and access to personal information such as biometrics).

Security

Barrier


Managing the risks of new technology

Explanation


Managing and resolving the security issues that arise from new technologies, such as the risk of cyber-attacks.

Investing in digital innovation can have better returns than investing in physical infrastructure.

Digital innovation is flourishing, producing new technologies that are changing the way we deliver and operate infrastructure (see Table 7 and Case Study 16). Artificial intelligence techniques, such as machine learning, can deliver more insights into infrastructure and systems, enabling greater efficiency. Building Information Modelling (BIM), the digital representation of a structure, can vastly improve design, while 3D printing could change the nature of construction. These powerful tools can help planners and developers to tailor the delivery of infrastructure systems to meet the needs of communities and leverage technology to enable better infrastructure and better outcomes.

To realise the benefits of digital technology, the infrastructure industry needs to adapt to the new world of big data and data analytics and work together. For example, the disciplined and consistent use of BIM technology has been estimated to have saved the government of the United Kingdom the equivalent of NZD $4 billion over a six-year period.436 Many information-technology solutions projects have been shown to cost less and deliver better returns on investment than built options, while delivering the same service outcome (see Figure 34).

Table 7: Digital technologies that can transform infrastructure industries

Artificial intelligence – machine learning

Artificial intelligence enables digital devices to respond and learn from their environment. It is anticipated to streamline tasks, especially those that are repeatable and continue to learn and develop through completing tasks and receiving feedback.

Digital twins

Digital twins can be used to analyse historical performance and then predict how infrastructure will perform in the future by mimicking real-world behaviour (see Case Study 17).

Digital consenting

Digital consenting is an application of BIM and digital twins that streamlines the consenting and approval process. Traditionally, the consenting and approval of changes to the built environment rely on people checking compliance. Digital consenting removes the human element by integrating the consenting and compliance checks into BIM and digital twin applications.

Immersive media (augmented reality / virtual reality)

Augmented and virtual reality are technologies that help visualise digital information. Augmented reality merges digital information with the real world through headsets or mobile devices so that the digital elements appear as additions to the real environment. Virtual reality involves full immersion into a digital space removed from the real environment. Both technologies can make use of sensors and devices to allow human interaction with digital elements.

The Internet of Things

The Internet of Things is a network of physical objects capable of collecting, sharing and acting on data without human intervention. At its core, the Internet of Things relies on physical devices, sensors and telecommunication networks to improve processes based on a larger set of data from the whole network of devices. The Internet of Things will affect the way infrastructure is managed through greater real-time communication between the different parts of a network.

Case studies

The solutions to the issues we face have often been shown to work here and overseas. These case studies are an example to learn from.

Possible cost-benefit ratios of Information Technology Systems projects compared to building new road capacity

Figure 34: Information technology investments can provide value for money

Source: Adapted from McKinsey (2013) [437]

Source: Adapted from McKinsey (2013) [437]

Digital twins in spatial planning

There’s an opportunity to develop digital twins for our infrastructure as part of the emerging spatial planning process.

Regional and urban digital twins, aided by big data and machine-learning approaches, can bring together all the data held about individual infrastructure, capture data on the connections between infrastructure systems (such as between water, transportation and energy) and support the development of a data-driven economy.

The aspiration is to develop a National Digital Twin that brings together the digital information of spatial plans. The approach could begin with a digital twin that’s an adequate representation of the real world (see Case Study 17) and moves towards one that can analyse and predict the future performance of an asset, network or system. This modelling could improve maintenance, support planning decisions and enable better performance. Initially the digital twin could be used to help integrate land use and transportation planning at a regional level, plan for future corridors of growth and identify areas where growth is likely or appropriate for new projects (for instance, following international examples in using digital earth technologies to identify renewable energy projects).438 As capability grows, it could become an important decision-making tool for national infrastructure networks.

This technology could also help grow our understanding of the way the infrastructure system works. In the future, it may be possible to ask questions of the digital twin, such as: “If the population of Auckland were to increase by 50% by 2050, how might we change the way we use existing transport networks?”

Case studies

The solutions to the issues we face have often been shown to work here and overseas. These case studies are an example to learn from.

7.3.4. Recommendations

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