Inside Digital Twin: How to Enhance the Value of Yesterday’s and Today’s Data

In recent years, the concept of the Digital Twin has become firmly established in the vocabulary of construction digitalisation, emerging as one of the most frequently cited keywords in innovation contexts related to the lifecycle of buildings and infrastructure. However, its practical application in the Italian market often remains confined to pilot projects or isolated cases, partly due to a fundamental misunderstanding: the belief that a Digital Twin can only be achieved through complete, perfectly structured BIM models.

While this view may be theoretically correct in an ideal sense, it risks deterring many organisations from pursuing a progressive and genuinely sustainable digitalisation path, both economically and operationally. In reality, an effective Digital Twin can – and should – be developed starting from existing resources: CAD archives, PDF drawings, laser scanner and photographic surveys, asset and maintenance databases, sensors, and operational information in general. The aim is to transform this information base, even if fragmented and heterogeneous, into a coherent and interoperable system capable of evolving over time towards full information modelling.

Beyond the Myth of the “BIM-Only” Digital Twin

A common misconception is to view the Digital Twin as merely a three-dimensional replica of a physical asset. In reality, the 3D model is just one of many information layers that constitute a digital twin.

What truly defines a digital twin is the dynamic connection between digital data and real assets – a system capable of integrating heterogeneous sources and updating over time. The value of a Digital Twin lies not in having a perfectly virtualised model, but in having reliable, connected, and usable data presented within an immediately understandable spatial context to support operational and strategic decisions.

In the Italian context – where real estate and infrastructure assets are often extensive, complex, and layered over time – the creation of a digital twin must take reality into account: up-to-date BIM models or consistent databases are rarely available. The real challenge is to create informational continuity from disorder, establishing reference standards that enable the progressive integration of various sources.

Enhancing the Value of Existing Assets

Most organisations already possess a significant amount of information – often underused: DWG or PDF drawings, maintenance documents, floor plans, surveys, photos, asset registers, and data from sensors or management systems.
The most effective approach is not to pursue a fully BIM-oriented perspective, nor to adopt increasingly advanced yet still fragmented solutions (separate systems, diverse software or platforms, ad hoc tools limited to specific contexts). Instead, it is to systematise existing data, ensuring maximum consistency, traceability, and interoperability, following a more Data Lake-oriented logic.

Today, digital platforms enable the integration and georeferencing of files of various types, federating them into a single environment where every element – whether a floor plan, photographic layer, or point cloud – becomes part of an informational ecosystem.
This approach enables the extraction of immediate value: spatial management of environments, tracking of maintenance tickets, association of technical or documentary data with assets, and contextual visualisation of information.

Digitalisation can therefore begin pragmatically, without waiting for the creation of a complete BIM model, while simultaneously laying the foundations to achieve that goal – pursuing the same aims of centralisation, standardisation, and usability. The Digital Twin should be regarded as the orchestrator of both past and present data, finally providing them with a shared space to converge. It transforms archived and forgotten information into functional and contextualised data, extracting real value for today and predictive value for tomorrow.

Standardisation and Interoperability: The True Core of the Digital Twin

Every effective Digital Twin is built on a fundamental principle: data standardisation.
Without a common language and shared classification criteria, any integration effort risks becoming another information silo. Defining Information Requirements (OIR, PIR, AIR) is therefore an essential step not only in BIM processes but in any gradual digital transformation journey.

Establishing rules for structure, naming, coding, and formats from the outset makes information interoperable, regardless of its nature, level of maturity, or originating software or platform. In this sense, creating an information specification and technical guidelines that also apply to traditional data collection phases (surveys, archives, technical documentation) is a strategic investment, ensuring consistency and integrability throughout the entire asset lifecycle.

From Heterogeneous Data to an Integrated Model

The progressive integration of data is a process that must consider a frequently underestimated factor: time. At the outset, the available information set will inevitably be heterogeneous. Some parts may already be modelled in BIM, while others exist only in 2D formats or even on paper.

The task of the digitalisation process is to federate these information layers within a unified platform, enabling their interpretation, correlation, and enrichment over time.

This information-layering approach enables the gradual development of a system:

• starting with simple representations (drawings or asset sheets);
• adding more advanced layers (laser-scanner surveys, meshes, partial models);
• progressively integrating management data and IoT sensors;
• eventually achieving complete and interoperable AIM (Asset Information Model) structures.

What is important is that each step remains consistent with the previous one, maintaining a single data management logic to support the use of a unified platform for centralising and managing the many operational aspects associated with this information.

The Value of the Digital Twin as a Living Ecosystem

A Digital Twin is never “finished”; it is a living system that grows and updates alongside the evolution of the physical asset. The integration of field data – from IoT sensors, monitoring systems, or maintenance activities – enables the digital twin to develop from a simple archive into an operational and even predictive tool.

The collection and historisation of information opens the door to new possibilities:

• predictive analytics to optimise maintenance and reduce failures;
• comparative assessments of expected versus actual performance;
• continuous monitoring of asset conditions;
• improved support for investment decisions through a more accurate understanding of the asset lifecycle.

The ability to contextualise data within a spatial and geometric reference – typical of the Digital Twin – makes it possible to overcome traditional barriers between management systems, creating a single, accessible, and shared representation.

A Gradual and Sustainable Journey

The digitalisation of the built environment should not be approached as a sudden technological leap, but as a progressive journey towards digital maturity, developed ad hoc through a deep understanding of the surrounding conditions and objectives. The goal is not to produce perfect models, but to build a system capable of continuous growth – within and together with the context it is intended to serve.

From this perspective, even a “simplified” model or an organised database represents a significant step towards a mature Digital Twin. Each implementation phase must also be accompanied by validation and control processes to ensure data reliability and maintain consistency with defined standards. Only then can the system evolve in a controlled manner, without information loss or overlap.

From Managing Single Assets to an Integrated Vision

Another key aspect of the Digital Twin is the federation of data across multiple assets.
In complex contexts – such as infrastructure networks or extensive real estate portfolios – the ability to aggregate information from different locations or asset types enables centralised and comparative management, which is essential for optimising resources, priorities, and maintenance strategies.

Geographic contextualisation through GIS environments, integrated with technical and documentary data, also enables a territorial view of the asset portfolio – extending the concept of the Digital Twin to a broader urban or infrastructural scale.

Conclusions: Building Long-Term Value Starting Today

In the Italian market, the adoption of Digital Twins is still in a consolidation phase. However, the potential of this technology is enormous, especially when approached realistically and progressively.

There is no need to wait for the “ideal condition” to begin. Instead, what is required is a strategy of integration and standardisation – one that delivers return on investment by enhancing the value of existing information and creating a shared aggregation process across different types of input.

As we have long emphasised for Building Information Modelling, the Digital Twin is not simply the implementation of a software solution, but a methodology – an even more complex one – that spans multiple domains and requires a broad strategy and deep knowledge for successful deployment. It is the ability to transform disordered data into structured knowledge, and structured knowledge into operational value.

By creating coherent, open, and interoperable digital ecosystems, it becomes possible to ensure more informed, efficient, controlled, and therefore sustainable asset management over time. This objective does not necessarily require complex BIM models, but a clear vision: gradually bringing together, under a single platform, all the data that describe reality.

Only then can the Digital Twin become not a futuristic concept, but a concrete opportunity for the present.

Alvise Verì
Architect | BIM Manager & Chief Consultant Bimfactory