Many other industries have already recognized the importance of data. How are real estate companies approaching this topic?

Business leaders recognize the importance of data in principle, but many of them are not willing or do not know how to take all the necessary steps to have good data.

The real estate sector is a little bit behind the curve as it is perhaps more conservative as an industry and also because the data required to describe the financial performance of real estate assets is very complex.

When I became involved with real estate almost 20 years ago, one observation I had was that the data environments were much more complex than in other industries, with more data points and interactions harder to model with an IT system. That is why it is not surprising that companies struggle when implementing IT systems.

Andreas Kozma

Founder & CEO
iREMS International AG

Andreas has extensive industry experience in the areas of internet and enterprise computing as well as business consulting. Andreas was born and raised in Zürich, Switzerland. He earned an MBA and a Master's degree in Computer Science at the University of Zürich.  Andreas has always been involved in end-to-end enterprise projects, from the business side to the planning side to the actual design, development, and deployment of projects in Chicago, USA and in several countries in Western Europe, such as Switzerland, France, Holland and Belgium. Andreas then relocated to Central Europe, where he worked for Deloitte & Touche Central Europe on large-scale IT system implementations (mainly SAP and banking solutions) throughout the region. During the dot-com boom, Andreas also advised iEurope Capital, a venture capital fund focusing on high-tech investments in Central Europe. As a founder and CEO of iREMS International group, Andreas concentrated on developing a comprehensive data platform for real estate management, combining best of breed IT engineering and architectural solutions with a deep understanding of the real estate business domain. Today iREMS is one of the leading real estate management platforms in the Central European region. More »

What do companies usually struggle with the most?

A common situation is when the task of building a reporting software is simply delegated to IT without specifying the underlying business and reporting requirements. Consequently, they will focus on other metrics like how popular the software is instead of understanding whether that chosen solution meets the organization's requirements. Given that in real estate, data requirements are very diverse and come from different sources, they need to be integrated in non-trivial ways.

Integrating systems is quite challenging in general but in the real estate industry’s data-heavy environment, it becomes even more difficult to integrate data sources from different systems. The more separate software packages a company tries to integrate, the more problems it will face with creating and maintaining those data interfaces.

Who is usually the person within real estate companies that is responsible for data management? Is the selection of this person usually a strategic decision?

It should be a strategic decision, but it seems like sometimes it is not taken seriously enough by top management. The obvious choices are asset managers and CFOs. Asset management needs good data to make the right decisions and the CFO needs to have good reports for controlling and reporting, so both are valid choices.

An ideal situation is having data-aware asset management who can formulate information requirements alongside a CFO who is also able to communicate with the asset management team. Both sides need to be able to understand each other and it does not really matter which one takes the lead as long as they coordinate with each other.

Another potential challenge that comes to mind is harmonizing data across borders. Multi-national portfolio managers must have different ways of collecting and using data in each country. How can this challenge be managed?

When a portfolio becomes international, the level of complexity increases yet again. More data needs to be connected, synchronized and coordinated. The complexity of handling different legal requirements in terms of invoicing, reporting, and accounting, and the handling of financial data in different currencies add another layer of complexity, which means that the design and the structure of the software needs to be even better thought through to handle all these different requirements. The challenge is to build a data architecture that allows to harvest each type of data at its source where it is generated. The data then needs to be processed and transported for storage to a central location, where it is readily accessible for transformation and assembly by many different types of reporting requests. To make it more complicated, when collecting the data you need to take into consideration both the geographical origin and the functional modules such as operational expenses (OpEx), cost of financing or capital expenditure (CapEx).

You can compare this exercise to urban planning where physical production sites need to be connected by transport links to areas of consumption. In the real world, we call it supply chain management, in software engineering you could call it data logistics.

In your opinion, what attributes should successful real estate management software possess?

Obviously, a software provider needs to know how to write software which can provide the desired functionality and include the many distinct features that need to seamlessly cooperate with each other. We need to know how to work with large transactions and data volumes, how to ensure that reports are running fast and systems are resilient and self-healing. That is already quite a challenge that many IT companies are struggling with and it is just one part in which tech, IT and software engineering know-how are particularly important.

The other area where our craft needs to be good is understanding the business logic and the language of our clients. In other words, we not only need to be able to listen to them tell us what they think they need. Often, we also need to understand the underlying business requirements so that we can help them to understand what they really need. The perceived and the final, best practice requirements are not always in line. To arrive from one to the other is a process containing change management, business process analysis and data analysis activities. This is on the business side of the big divide, which often separates IT experts from the business world.

I earned a major degree in business and a minor degree in software engineering at the University of Zürich as it was important to me that I can understand the language of business professionals while being able to communicate with IT specialists. Understanding both sides is in my view the main ingredient to providing a successful IT platform in real estate.

In terms of the size of a portfolio and the phase of the business cycle, when is a good time to invest in new software?

I have to add one more important principle that real estate companies should follow, which often we do not see. That is seeing data as a financial, digital twin of a building. If the digital image of the building is scattered in several systems of service providers, Excel files and so forth, then it is much harder to obtain a unified image of the financial situation of that building. It makes it that much harder to create reports and eventually take the right decisions. Funds should see the important value of a unified repository of financial information that they control but that also needs to be built up and needs to be invested in. Many funds do not recognize that.

The question to be asked should be when is it a good time for an investor to start its own financial data model and collect its own unified data. A good moment is in the current period, for example, when it is hard to undertake transactions due to the difficult economic environment. Teams have more time to clean up and streamline internal processes so it is a very good moment to work on those requirements and definitions, to figure out what financial data is needed. That will then give the set of business requirements, based on which the relevant system specifications can be created. Those specifications in turn allow to choose and successfully implement the right system(s).

In the end, investing in data management can also help with cutting costs, which is an absolute high priority for many companies right now.

Yes, indeed. Cost control both within data processing and within operating the income-producing assets is a major priority, as it constitutes one-half of the yield calculations. However, it cannot be an end by itself. The reduced costs and fewer errors actually come as a bonus from a well-designed and well-executed target operating model combined with a well-designed IT platform. If the specification is designed in a simple, straight-up way, then the efficiency gains and cost savings will follow automatically.

Before you can have the right software, you need to have the right data. How can companies collect high-quality and complete data on their assets?

Once again, real estate is more complicated than other industries, in that we have a higher number of players compared to other businesses. We have valuators, property managers, accountants, asset managers, facility managers, etc. This means that even for a smaller-sized portfolio we can easily have 10 different external companies which all need to obtain and provide certain sets of information and they all have their own data standards and IT systems.

As an investor, you can ask all of these companies to provide certain Excel spreadsheets and if those are well-standardized, you can integrate them into your own data landscape. However, even though this approach is easier to set up initially, it is very hard to scale up - It is difficult to formalize properly, it is quite labour-intensive and prone to errors.

Another possibility is to interconnect multiple systems. There are several international real estate service providers who specialize in interfacing their own systems with their clients' systems. Nonetheless, every data bridge or interface between systems is difficult to build and maintain, so this route can also be very challenging.

A new way that is emerging and we have had good experience with is actually for the landlord to extend the scope of their system by asking service providers to conduct their transactions on the system of the property owner. That is the safest way once the system is set up because it is then guaranteed that the people who work on the system do not need to do any reporting - data is automatically produced in the landlord’s system based on explicit data entry standards and validation rules. Another big advantage of this approach is that all financial data is available to the landlord from the onset, without any additional effort.

One thing that is still usually difficult is to measure the success of an ESG strategy. How can IT systems help companies overcome this challenge?

What is most real estate specific is the E (Environmental), because of the heavy carbon footprint of buildings, both during construction and operational phases, so I’d focus on that and divide the question into two parts.

The first part is the technical information that can come from building information management (BIM) systems with sensors measuring the consumption of the building. With this, we can identify where we might lose energy and then fix those problems.

The second part is the financial information. Energy consumption must be re-invoiced to the tenants, providing a direct and straightforward way to inform them of how much energy they are consuming. Simply by using the energy re-invoicing process in an integrated fashion, we can extract a lot of ESG knowledge like the tenant's consumption footprint and the energy consumption of the entire building for each type of energy. If the information is properly collected during the invoicing process, then it can also be rolled up to the country or portfolio levels. If we then start collecting this information in periodic intervals, we can obtain entire time series of energy consumption data, which is the basis of any sophisticated ESG reporting activity.