A richer understanding of how our infrastructure assets perform has been sorely missed across the sector for too long
Why would any business invest its hard-earned cash on a promise of reduced operating costs and better service for customers but then omit to check if it actually delivers? Well bizarrely, it is pretty much standard operating procedure across the built environment when managing assets.
Yet to professionals working in the complex aerospace, automotive or manufacturing sectors, the concept of outcome-based contracting is nothing new.
Whether it is via the sophistication of aircraft engine manufacturers providing power by the hour or simply through car parts suppliers providing consistent quality and just-in-time delivered components, these industries not only understand what they need from their contractors but have invested in the capability of checking.
Fortunately for the built environment sector, life is about to get easier in this department as data and modelling starts to radically impact our world. The digital twin really does hold the key to securing a future of outcome-based delivery.
The National Infrastructure Commission’s latest report “Data for the Public Good” puts it very succinctly: “A national digital twin would enable the UK to develop a richer understanding of the way our infrastructure works and optimise it, so government and industry can make more informed decisions about the future.”
The use of data science, machine learning and predictive analytics, it adds, will contribute to each model of an infrastructure asset, network or system to power predictive asset maintenance, support planning decisions and enable performance optimisation. In short, we will be able to check – in real time – whether or not our assets are delivering to plan and, crucially, take steps to improve the outcomes.
It is this richer understanding of how our infrastructure assets perform which has been sorely missed across the sector for too long. Failure to grasp the concept of outcomes across the infrastructure lifecycle has led to the chronic underperformance that we routine now see across the UK infrastructure - underperformance that continues to act as a catastrophic brake on the economy.
Traffic congestion, train delays, flooding disruption, increased illness from poor quality housing or energy inefficient housing and offices are all the result of our failure to focus on outcomes when we contract to construct, operate or maintain infrastructure. Understanding the costs and impacts of this inaction is critical to prompting change and the use of digital twins is set to revolutionise our ability to make better decisions.
Tools such as GeoConnect+, which was developed recently by PCSG with Ordnance Survey and BC Group, help bring data sets together and underpin concept of digital twins. The cloud-based platform is designed to help large asset owners and operators manage large, disparate estates by providing a better context for digital models.
Rather than creating a single centralised model, GeoConnect+ gathers and links data to allow quick and accurate interrogation of the data by connecting asset information with other geospatial datasets such as mapping, land and property data, flood, river, and road network data.
As the NIC explains, being able to effectively access this data gives us the ability to ask questions and run simulations to test and optimise outcomes from investment decisions on transport use, energy consumption or urban planning. It enables us to integrate the maintenance of assets with the need to minimise disruption to consumers.
Ultimately the digital twin enables us to manage our infrastructure with vital outcomes not only firmly in mind but tested, evaluated and measurable during operation. It provides a platform to move swiftly and inevitably towards outcome-based contracting and provides a long-awaited opportunity to raise the industry’s bar in terms of delivering value for public and private investment.
Mark Bew is strategic advisor the UK’s Centre for Digital Built Britain and is chairman of engineering consultancy PCSG.