How the digital twin will revolutionize the real estate industry.
The Digital Twin is a term increasingly used in the real estate sector, yet it is rarely fully understood or comprehensively applied. In many cases, the digital twin in the real estate industry is merely equated with IoT or BIM. However, the concept of a Digital Twin, and especially the potential behind it, is far more powerful and can create significant value—particularly in the real estate sector.
In this industry, real estate assets have significantly longer lifespans compared to other industries. Additionally, operational costs throughout a building’s lifecycle far exceed initial construction costs. This makes it highly valuable to capture, maintain, and leverage data associated with an asset—from the initial idea and construction to usage and eventual repurposing or recycling.
Why does a real estate company need to evolve? What are the driving forces?
The Digital Twin is a term increasingly used in the real estate sector, yet it is rarely fully understood or comprehensively applied. In many cases, the digital twin in the real estate industry is merely equated with IoT or BIM.
Digitalization is fundamentally reshaping the landscape and the possibilities for service offerings. However, digital transformation is not the only driver of change. Other key influencing factors include the growing sustainability requirements for buildings, the globalization of the real estate market, and general competitive pressure. The sustainability of real estate and a customer-centric approach are becoming the central focus. Topics such as energy reduction, circular economy, response times, transparency, and information demands are increasingly shaping the priorities of our clients and stakeholders.
Through a potential analysis of technological drivers in the real estate industry, conducted via interviews with leading service providers and investors, we identified data and platforms as the two most promising mid-term drivers. These two factors are also at the core of the Digital Twin concept. Data from various sources is collected and made available in a central location. Of course, intelligence and additional technologies are also required to complete and refine this concept.
Digital Twin – what else? What is a Digital Twin?
The word “Digital Twin” was first used by NASA in a report in 2010 on the Apollo 13 mission. It is interesting to note that the Apollo 13 mission took place 50 years ago. Even then, NASA accurately replicated the systems on the ground for problem solving and fed them with “real-time data” from the flying original.
We define the digital twin as follows:
- A Digital Twin is a true-to-life digital representation of a physical object.
- The Digital Twin enables parameters, information and realtime data as well as target and purpose of an object.
- The Digital Twin can be used to map, predict and optimize the performance, behavior and use of an object.
There are now countless applications of Digital Twins:
- Data-driven twins of entire cities are being created with diverse information from zoning maps, building information, green spaces, building lines and much more.
- The industry is creating digital twins of products or even production lines to better adapt products to customer needs via various feedback loops and thus take fewer risks. Companies are constantly optimizing and monitoring their entire production (reducing production downtime, optimizing lead times, etc.). Digital Twins open up great potential in all areas, whether for simple consumer goods or complex products such as cars, airplanes or even wind turbines.
- This also applies to people: They create images of themselves in social media (LindekIn, Facebook, Instagram, etc.) and feed them with information, sometimes on a daily basis. But digital avatars are also being created in medicine for faster examinations, more accurate remote diagnoses, or even for analyzing the effect and side effect of drugs in advance.
But what about real estate?
What is a Digital Twin and what role does it play in the real estate industry?
Real estate is not comparable to normal goods. There are three main differences:
- Lifetime
- Cost allocation over the lifetime (20/80)
- Individuality of each product
Digital Twin for real estate explained through the property lifecycle: Even before construction begins, the Digital Twin (DT) is created and enriched with as much information as possible to generate a virtual representation of the future property. This early-stage visualization allows for the development of different design variations, enabling the sale of the property even before actual construction starts.
Buyers know exactly what they are purchasing, reducing the risk of unexpected issues later. This significantly shortens time-to-market, and potential costly adjustments during or after construction can be avoided.
Virtual construction site with BIM and supply chain
As preparation for implementation, the construction site can already be virtually set up, tested, and optimized. Most of the data comes from the Building Information Model (BIM) but can be supplemented with additional data from the entire construction ecosystem. This allows the entire supply chain for the construction site to be modeled. Additionally, the required space for the construction site can be minimized, which is particularly beneficial in dense urban areas. Cost allocation up to project completion can be predicted, ensuring early financial security.
Even during construction, the Digital Twin enables optimization opportunities. Just-in-time deliveries are planned and continuously adjusted to match the actual construction progress. Delays can be immediately coordinated with subsequent steps. Tasks involving expensive construction machinery are scheduled more efficiently to reduce waiting times.
Using Augmented Reality (AR) and Virtual Reality (VR), virtual planning is compared with on-site construction, allowing errors to be detected and corrected immediately. This is especially useful for hidden structural elements that are no longer visible after project completion and could otherwise lead to significant follow-up costs.
The greatest potential of the Digital Twin unfolds during the usage phase
Today, due to the large number of existing buildings, the Digital Twin is usually created during the usage phase. At this stage, the most comprehensive information about the property is available, allowing the Digital Twin to realize its full potential. Usage, operational, and real-time data from the property feed into the Digital Twin. These are combined with additional data sources, effectively bringing the twin to life. This enables the representation of performance, behavior, and usage of the property, unlocking various applications:
- Interfaces within real estate companies across different departments are simplified or unified.
- Reports are enriched with real-time data and additional information and can be generated at any time.
- Transparency is created, optimizing usage, operations, and occupant well-being within the building.
Which information sources feed the Digital Twin?
The goal is not to connect as many data sources as possible at once or create new ones, but rather to break down existing silos, consolidate data, and make it available within a unified data model—across the entire lifecycle.
A list of potential data sources with examples highlights the vast potential:
- Object Data: Certifications and labels, micro/macro location, tenant structure
- Asset Management Data: Property strategy, reduction pathways, valuation & financing
- BIM with all 7 Ds: 3D planning, implementation planning, cost analysis, sustainability and efficiency, operations, and facility management
- External Sources: Environmental and weather data, financial market data
- Facility Management: FM data from overall operations, often stored in a Computer-Aided Facility Management (CAFM) system
- Specialized Applications: ERP, CRM, construction management tools
- Real-Time and Usage Data from smart building systems, Internet of Things (IoT), control technology, and building automation
How do real estate companies add value with a digital twin?
However, just collecting data is not enough. The main goal of the digital twin is to create added value. But how? Basically, there are three ways:
- Internal optimization, such as increasing efficiency and reducing costs.
- Improving the customer experience, or creating new customer experiences.
- Or the combination of these two points in the context of identifying new services or even new business models.
The digital twin and, above all, the linking of the various data sources to form an overall view form the basis for this. The digital twin is an enabler to really create added value from data. The approach can be two-sided. On the one hand, with the identification of use cases and the derivation of the required data sources, on the other hand, with the analysis of the combined data sources with data analytics and the insights thus gained for the creation of use cases.
Environmental, Social, and Governance Reporting (ESG Reporting)
A current use case is ESG Reporting (Environmental, Social, Governance). To generate the report, object data is combined with external relevant sources within the Digital Twin. The property strategy, including the defined energy reduction pathway and specific measures, serves as the foundation. Additionally, usage, consumption, and real-time data from the control systems or IoT sensors of the building are integrated. These are further enriched with certification or eco-label data and combined with external sources such as environmental data and regulatory requirements.
This data foundation is then analyzed in detail, with risks identified and quantified. Based on EU taxonomy guidelines, the CO₂ footprint of the building is calculated. The reporting generated from this data serves two key purposes: ensuring transparency for investors and verifying compliance with regulations. Additionally, ESG reporting supports asset management in actively controlling and continuously improving real estate portfolios, ultimately enhancing sustainability.
How is a Digital Twin implemented technically?
This simplified representation gives you a rough overview of the most important elements in the chain from the data source to the desired output.
- Different data sources require different interfaces (ERP system, building management system, BIM, IoT) à protocols, batches, events, etc.
- The raw data is stored in the digital twin. However, they cannot yet be used directly due to the different way they are used and first need processing. With the transformation, the data is processed so that it can be provided in a data model.
- Access from the services, the target systems or APIs is made to the DataLake, the Data Warehouse or DataMarts. This implementation of the provisioning layer is strongly dependent on the corresponding target service and its requirements.
It is essential to consider key elements in data security, including cybersecurity & privacy, data governance, and data access. These aspects are crucial for the sustainable use of the system but are often addressed too late.
Eraneos has some project experience from the strategic considerations to and with the implementation. We would like to share four tips with you.
- Architecture → Think big: The architecture should be flexible and designed for future expansions. Cost- and requirement-driving cases, including edge cases, must be considered.
- Use Cases → Start small: Identify a use case that can generate initial value and implement it as a proof of concept for the architecture—ideally using Minimum Viable Products (MVPs).
- Data → Data to value: In the first step, integrate only the data sources truly relevant to the use case. Identify the right data model(s) for your application. In real estate, a semantic model can be particularly useful for allocating data within a building structure.
- Security → Security first: You are handling business-critical and personal data. Consider security from the outset and involve experts early in the process.
