Sustainability and ESG are omnipresent topics within the real estate industry. Affected by the public discussions on climate protection, the ecological aspect of buildings is moving more and more into the focus. What needs to change and how can portfolios be managed in a climate-neutral way? 


ESG as a game-changer


There are plenty of applications and a lot of discussions on how to define and measure KPIs for ESG. Yet, when trying to take a practical approach and to understand what it really means, it is not so evident. So where to start? With the perspective of different data sets that surround buildings, we can approach ESG terms to benchmark the performance of real estate.


Which data do you need?


We have location-based data, demographics, city data, comparables and market indicators to choose from. But at the core, we have the customer – a person, who walks into a building with a certain purpose in mind, with a certain expectation.


“Valuations of buildings are mainly based on financial data and KPIs like location and market value. But not enough on the content or the materials in the building themself” states Daniel C. Tabacaru, Founder of AGAIN X, a Norwegian company aggregating sustainability KPI’s for existing buildings using aggregated data and machine learning.


With the help of algorithms AGAIN X can show clients where lies the biggest potential and where is the biggest risk in managing their buildings. “Based on our extensive interviews and workshops with our customers, we have identified six main areas that create uncertainty in assets management, among them maintenance prediction, material quality, toxic materials, and energy usage”, Tabacaru concludes. Benchmarking is an important part of it. We need to benchmark it against the best and similar buildings. To evaluate what, we need to look at the scale of the data. From there you can define three scenarios: keep the building, demolish and build a new one, or refurbish it.


The value of sharing data


We need to move towards the understanding that sharing data is adding value to your data. And we have to take a look at how dependent we are on third-party data and how limited our data is to locations and counties. An approach could be the replication of a human brain: in the learning phase, you accumulate a lot of data. And from gathering and storing data, you can understand new situations. After the algorithm recognizes the buildings typologies, the elements of the building and the criteria to identify and build a risk assessment model, then it will be much easier to generate benchmarks for ESG. But keep in mind, every country has its specifics regarding data, data storage, and labelling. 


When we talk about data exchange, the first problem that needs solving is the granularity of data or the single individual item for which the data relates to. When we are talking about real estate assets, we normally mean a building or a group of buildings or even sometimes built-in premises, so we have to be very specific on how to attribute the data that we collect or exchange. 


But we are not just dealing with pure data around our buildings, we also have the human aspect. What do we know about the person visiting, for example, our shopping centre?


Customer data in focus


You need to know your customers to be relevant. Data can help you generate a great customer experience – collecting data, getting the insights, and acting on the information.


Data Talks is a Swedish company which helps companies to create a world-class customer experience, based on their data. With their Customer Data Platform (CDP) you can build personalized customer engagement by collecting, analyzing and acting on your data.  

Philip Nordfeldt, Co-founder, on using a CDP said “We are using many different channels and each channel is generating a lot of data. So how can you then generate valuable customer experiences? By putting the customer in the middle and connecting all this data from various sources.”


It makes sense taking a closer look at what a CDP is and what it can do. We are in this shifting mindset stage where property owners and real estate managers have to measure not just how many people are walking in and out of a building, as an example, but also the attention the people give. Attention becomes the actual currency that real estate owners and the tenant exchange. This can be one way to approach ESG benchmarking. The Social part in ESG, by defining customer profiles. Because in the end, everybody is more or less a customer. 


A practical example


The Shopping centre owner and the Asset Manager are not just simply selling or renting out square meters to its tenants. The Asset Manager is actually offering the relevant audience of the shopping centre visitors to its tenants. The way you measure the feedback, the loyalty and engagement of the customers is the way to get relevant KPS and estimate and benchmark something that can be called a social impact of your business model, of your approach and your values.


Having a more holistic view on data, collecting data and putting the customer into the focus will certainly generate a better customer experience.


When we talk about the social impact on a larger scale we need to turn towards social demographics and macroeconomic figures that used to be something we analyze only on retrospect, based on some statistics. But now we have a way to gather this data, to analyze this information and make predictive models and aggregated datasets.


Role of demographic and macroeconomic data


What kind of demographic or macroeconomic data can we aggregate and how valuable and applicable it can be to measure the ESG score for real estate? 


Algoli, based in Germany, is an algorithm builder, allowing you to build powerful data-driven apps and control large & complex external data sets. “Algoli unifies different data sources and different data progress into one single data stream. You can select individual data attributes you are interested in. Then we have a technology in place that you only have to use one data API to get all the data you need. The most difficult aspect is the accessibility of the data especially if you go across geographies” states Dirk Wilfling, CEO at Algoli.


For example, with Algoli you can select the number of population, the income level, the NET wealth worth or even the educational level in a certain ZIP code – across borders. Those can then be compared to each other which will help you to understand the social impact of a specific region regarding different criteria.


Defining KPIs for ESG


How all these data aspects can be shaped into a versatile KPIs to benchmark the ESG performance of real estate? How does it come together into a model that can be attributed to a real estate asset and how can we even identify a real estate asset?


“Having the choice of working together with many different companies, you find yourself struggling in choosing the right ones” says Achim Jedelski, Digital Advisory & Blockchain at Drees & Sommer and Co-founder at FIBREE. “The next challenge is to integrate. Integrations are crucial when dealing with sharing data. The best approach is to create a good solution for your customers not building a product around your own idea.”


We can see that a data integration layer is missing. FIBREE and the Unic Object Identifier (UOI) system serves as the key for accessing interoperable databases with dynamic information on new and existing buildings or their built environment. The UOI enables you to view specific information relating to a building, floor, room, or window frame, based on your role and access rights.


Common data standard and exchange level where we can build our solutions on


“As a corporate, you fear young startups. You are not sure how long they will exist. And you don’t want to start searching and changing for a new solution after a while. That is why corporates end up with some of the larger forces in space. Because you know they can provide the needed support for the next 20 years. But that can not be the solution. We need to create some kind of “basic layer” that is enabling everybody of us to either build a solution or to provide and control data to manage the core business. For many people, Data is not yet core business. The real estate is not data-driven at the moment, it just got started” Jedelsky concludes.


Smart rules over powerful ones


The essential part is a common data approach. Within the industry, we have many different standards – take ISO 19650 or CREDA (Comercial Real Estate Data Alliance) as an example. There needs to be a practical way to find datasets and to aggregate them.


FIBREE and ECREDA (European Comercial Real Estate Data Alliance) are working on a project, taking this approach further. To come up with a common solution, we need industry players and larger corporates to be active. We need to understand their pain points and agree on what are the needs. Then you can build a future business model on top of that.


Data as part of your DNA


Now, taking a solution into use that can calculate certain benchmarks. Then another one which is enriching the dataset with some demographics and adding some customer data from a DCP on top of that. Is it possible to streamline those data and display it for a certain portfolio?


“Technically that is possible. Like many other solutions, also Assetti is offering an API. But it is not just about gathering the data. You need to be able to capture the data, present it and make then the right conclusions out of that. Investors need to exchange data. Each of them has his data model, which handles kind of the same data but on the other hand not. The devil is in the detail” tells Hannu Rantanen, CEO of Assetti.


Flexibility is needed or some kind of configurability and a technical enableing, which is essentially an API. The evolution of data layers means data streaming. We can also see the analogy from FinTech. Most of them are relying on the API of the incumbents e.g banks opening up their basic transaction data. Crucial for the real estate investors and owners is to open up their data. But in a way that there remains room for innovation and smaller companies also to participate. 


Getting best practices converged into standards 


The practical side of ESG benchmarking should be born out of the practical usage of these data sets and exactly from the visualization of datasets using asset management platforms, Business intelligence and interpretation layers. 


Recently the general discussion in the industry has shifted, especially since the beginning of COVID. The ownership of data and real estate incumbents being protective of their data has turned into a discussion on how we can utilize data and what is the right format to do so. Data sharing and data ownership should not be the excuse or the obstacle anymore when talking about the use of information. 


Potential next steps


ESG is still the goal. First, we need to find a good way to aggregate and exchange data and we need a platform to collect all those together. Where do we see the industry going and what would be further practical approaches? 



“The technology is there. We are often asked, which kind of data you can connect? Well, whatever data you have basically. The focus should be more on the WHY. What is the sense, why you want to connect the data and what is the value? “



«We should not forget that we are talking about the building industry. In buildings, you have huge delays and also the consequences of what you measure as an output comes from 20 years back. That fact can not just be solved with IoT but is something you need to look more holistically into it. You have the market valuation which is generated by shared data. All building owners are sharing some of their information and like this, you have an approach that the markets generate a valuation. That is something we are trying to convince our clients. Giving us some of their data means we can give them back trifold of the value of that data. 

One of the biggest challenge when using data is cleaning the data. We tend to simplify data, to label it in a simplified approach. All patterns that are generating fluctuation in the model are coming from the details outside the main labelling. We are talking about ESG to aim towards a more sustainable world. We need to convince our clients to prioritize quality to price now. Because quality means price saved on the longterm. The approach to data is going to change dramatically within the next years.”



“High price does not always mean high quality in the real estate market. Accessibility of the data has to be priced well. We will have an on-demand way to access data. Getting for example information regarding one street instead of buying data regarding an entire country.”



“Real estate is a very physical industry. The industry has to understand that there is a business model behind data. We need help Real estate to understand. That understanding and also a new way of approach will occur when tech people are going to be part of management.”



«I wish for a common data model within the real estate industry, including ESG. However, it feels a bit like shooting on a moving target because the business cases regarding physical assets called real estate are changing. But once we go to that direction, processes will improve, applications will improve, data exchange will improve.»


The meaning of ESG is how to build a sustainable future, which is a big goal. Technology is the answer, we just need to ask the right questions. The next big thing will be a lot of small things.