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The findings reveal something the industry does not openly acknowledge: the real bottleneck is not capability in technology, processes or people, but the organisational ability to adapt and orchestrate these to support decision-making. Here are some of the findings of our research.
The industry is becoming more digital. Dashboards are more common, models are evolving in sophistication, and sensor data is increasingly part of project delivery. Yet the research revealed that risks are still discovered late and the same issues repeat across projects.
What has changed is not decision-making, but how convincingly problems can be visualised. In many cases, digital twins have become high-resolution mirrors of existing inefficiencies.
The Project-Enterprise disconnect
Construction’s biggest blind spot lies in how it uses data beyond individual projects. Digital twins are almost always deployed at the project level. They inform delivery within individual projects, but construction firms do not operate as isolated projects. They operate as portfolios of risk, performance and commercial exposure. As a result, while firms are getting better at understanding individual projects, they still struggle to use data to improve performance across the business.
This tension is partly structural. Construction is organised around temporary projects but governed through permanent enterprises. Data is created in one, while value is expected to be realised in the other. When these layers are not connected, data and information become stranded within projects, and enterprise decisions do not benefit from data and digitalisation happening in individual projects.
Performance reported, not accumulated
The problem sits between projects and the enterprise. Each project generates its own data, often using different tools, standards and processes. This fragmentation is not accidental: it reflects how construction is organised.
Intelligence remains linked to individual projects. A delay identified on one project does not systematically inform another. A supply chain issue remains local rather than becoming organisational knowledge. The result is a system that learns slowly, despite having more data than ever before.
The data accumulation issue
As data moves upward across organisational levels, it becomes increasingly aggregated and standardised, often at the expense of context. Meaning gets diluted, creating a tension between comparability and interpretability when using data for decision-making.
From alignment to orchestration
This is where the industry’s current thinking falls short. Most digital strategies still assume that the goal is to align tools with established processes. But the evidence points to something more demanding.
What leading firms are developing is not alignment, but orchestration. They have orchestration capacities, reflecting their ability to continually adapt technologies, data infrastructures, organisational roles, routines and governance mechanisms across projects and the enterprise. In such firms, digital transformation is not a one-off temporary implementation, but a continuous process of coordination and reconfiguration.
In firms with such competence, data is no longer passive: it is actively produced, standardised, circulated and interpreted through orchestrated socio-technical arrangements. In these firms, data increasingly drives decisions and begins to support or even replace narratives, shaping conversations and priorities.
In some cases, executives explicitly challenge interpretations that contradict what the data shows. Data starts to be conceived as an organisational actor at all levels, dictating discussion items in the boardroom, triggering actions and redistributing accountability across organisational roles.
From orchestration to value
Value does not come from more sophisticated models, but from the ability to orchestrate data, people and systems so that information flows across projects and informs decisions at multiple levels of the business. When firms orchestrate data across projects, they stop managing individual jobs and start managing performance as a system. Decisions that were once reactive and local become anticipatory and portfolio-wide, with patterns in delay, risk or productivity detected early across multiple projects.
But the most advanced firms go further. As their capabilities mature, data is no longer used only to optimise delivery, but it becomes a strategic asset. Firms begin to leverage it beyond project execution, offering new services, ways to communicate with clients, and even shaping new revenue streams around performance, carbon and asset intelligence. At this point, value is no longer realised through better projects alone, but through entirely new ways of competing. Digital transformation, in this sense, moves from operational improvement to new ways of value realisation and business model innovation.
Until firms move beyond project-level optimisation and develop the capacities to orchestrate data, people and systems across multiple levels of the business, digital twins will continue to underdeliver.
Newcastle University’s DICE Lab focuses on advancing how data, digital technologies, and organisational systems support decision-making in construction and engineering. The lab is open for collaboration with industry partners. Prof. Mohamad Kassem can be contacted at: [email protected]
