Data driven business models will change the real estate industry has been saved
Data driven business models will change the real estate industry
Real Estate Predictions 2019
Written by Hendrik Aholt, Jörg von Ditfurth and Volker Wörmann (DE)
As technology keeps developing and becomes more affordable—for both new and existing structures—and collaboration platforms, sensors, and smart devices continue to advance, the amount of data produced by buildings is increasing exponentially. This data can give real estate market participants (investors, asset managers, property managers, and tenants) a competitive advantage and help them avoid disruption if they use it effectively to develop data-driven services and new business models focused on the specific needs of users, owners, or the property itself. But only a joint effort among all real estate stakeholders (constructors, investors, owners, tenants, and service providers) can optimize data to create insights that improve performance and profitability.
In the day-to-day business of asset and property management, the increasing amount of data available offers a range of opportunities. For example, big data can help automate due diligence as the technical records and current conditions of building components can now be generated real-time and reliably (with such technologies as building information modeling (BIM) and blockchain playing a role).
Predictive analytics is also becoming the standard sooner than many might have expected. This includes activities such as using information from the past to predict when technical components might need maintenance or repairs. Service providers that tackle these opportunities faster will become more efficient and provide better services. Business models based on success fees will be more common for those digital servicers, which will increase their margins. This development can change the landscape of service providers and consequently lead to market elimination and/or consolidation in that sector.
Predictive analytics for the tenancy-side of the building will probably take more time to develop but offers additional potential and will be even more relevant in the light of co-working spaces. If investors and asset managers can assess the optimal usage of a rental space for tenants based on data collected (e.g., utilization and services used), a perfect win-winwin situation can emerge for all three parties.
Looking ahead, the emergence of artificial intelligence and machine learning can also have an impact. For example, these technologies can address some of today’s questions in regards to cybersecurity and enable additional analytics and benefits which will be used in many aspects.
To generate these digital benefits, real estate stakeholders will need to find different ways to collaborate. Instead of discussing who has to pay for technical enablement and what data belongs to whom, real estate players should recognize that digitization means integration and networking. Success in big data will come with breaking up existing data silos.
Decisionmaking based on combined data from inside and outside the building (technical, tenancy, service, and market level) provided by different stakeholders will create the competitive edge. In particular, a “digital twin” of the real estate asset that encompasses all the benefits outlined above (and more) has to use a collaborative platform to ensure acceptance of the data, transparency, and mutual involvement. In short, tenants, investors, and servicers have to be strategic partners in the future.
Given the huge business potential, new market entries from the technology sector will most likely try to take their share of this real estate data market. Drawing on their own business models for the profitable use of data, those financially and well-equipped technology leaders can offer standardized global service strategies that could disrupt real estate investment managers and service providers. To avoid this competition, real estate stakeholders will need to move quickly and make themselves familiar with the potential of big data and how to convert it into smart data—no matter if investor, asset manager, or property manager.
Similarly, for a tenant, big data can help define future target real estate locations, required space, and needed technology. This not only enables tenants to compete in the war for talent but also generate the benefits from cost efficient future real estate assets. And just as with other real estate stakeholders, tenants must embrace collaboration with landlords and servicers.
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