I posted already about the need of Decarbonizing real estate assets. This becomes a major problem when real estate portfolios are made of dispersed units instead of buildings. In southern Europe but in particular in Spain, the majority of flats are owned by individuals so making individual flats more energy efficient becomes a major problem to solve. According to Eurostat in Spain, 75% of houses are owned by individual owners, and in Italy, the figure goes down to 72%.
The start-ups in the space can broadly be split into these categories
- Energy Monitoring and Analytics, provide real-time monitoring, energy dashboards, and advanced analytics to uncover energy-saving opportunities. Bidgely is a start-up in this space that has bagged more than 80M in funding. It disaggregates energy data to identify usage patterns, appliance-level consumption, and potential energy-saving opportunities.
- Predictive maintenance uses data analytics and machine learning algorithms to predict equipment failures and maintenance needs in real estate properties
- Smart Building Automation, develop solutions that use sensors, IoT devices, and data analytics to automate and optimize building systems, including HVAC, lighting, and occupancy management. ?Nest, a Google subsidiary will be a good example in this category.
- Cost reduction driven by energy savings can lead to higher asset yields and overall net portfolio asset value increases.
- There is an overall improvement of the rental/home experience not only because maintaining optimal temperature, lighting, and ventilation levels improves daily life but also the phycology associated with being environmentally responsible.
- ?Improving portfolio’s ESG compliance levels.
- Data models can drive new revenue streams and give higher strategic optionality and long-term value to the company?
Some challenges of the model
- Accessing data will normally be hard and time-consuming. ?Installing sensors could be costly and when dealing with individual units on rental agreements times to install sensors may be limited to new leases only.
- Data Quality and Accuracy, there will be a lot of data engineering needed to clean and standardize data before building a meaningful data model.?
- ?Privacy and Security concerns among tenants and owners will arise as some of the data collected could potentially be sensible.
- ?Scaling operations in individual units will be challenging.
We are exploring this space in a corporate venture-building effort together with a real estate fund. We plan to leverage their assets and our go-to-market strategy is focusing on acquiring first mid-size portfolios and then transitioning to individual owners over time.