By Ben Perrett,

Co-Founder & Director at Etainabl 

In the fast-evolving landscape of real estate, the integration of technology into daily operations is not just a trend but a strategic imperative. Having access to automated and reliable data is essential for enhancing operational efficiency, reducing costs, and improving sustainability.  However, achieving this goal can sometimes be difficult due to the way in which buildings are structured, the age or location of the current metering systems and a general lack of clarity about the availability and current usage of data. Here’s a structured approach to automate data within your existing building:

Assess The Assets Data Sources

While it might seem straightforward, fully understanding the data you need to collect from your property is perhaps the most critical step. This typically involves gathering information from both primary and sub-metering systems across various utilities, including electricity, gas, and water. Additionally, it’s important to consider other often-overlooked data sources, such as onsite waste metrics, solar PV output or fluorinated-gas as these ultimately will  be contributing to your carbon footprint.

Assess The Data Is Going

Next, map out how data flows within your operations and who needs it. This involves identifying various stakeholders like external consultants, on-site personnel, and property owners, and understanding how they interact with the data. For instance, consultants might need access to data for verifying invoices, while on-site personnel may use sub-meter data to allocate costs to tenants. Recognising these interactions helps in understanding the complexities of data management and potential bottlenecks.

Assess Current Data Collection Methods & Interoperability

Examine the existing methods of data collection. Whether through invoices, manual readings, submetering systems, or smart meters—and how the data is transmitted (FTP, email, API, etc.). Assessing these processes allows you to identify how automated the current system is and where there might be gaps in data collection or opportunities for integration and automation.

Implement Data Integration and Automation Solutions

Based on the gaps and needs identified in the earlier steps, begin implementing more automated data collection and integration solutions. This could involve upgrading to smart meters that automatically send data via APIs, integrating data collection software that compiles data from various sources into a central dashboard, or employing machine learning algorithms to analyse usage patterns and predict future trends.

Regular Review and Stakeholder Engagement

Finally, establish a routine for regularly reviewing the data collection and management processes. Engage with stakeholders frequently to ensure that the system meets their needs and to adjust to any new requirements or technologies. Continuous improvement will help keep the data management system efficient and relevant.

Common Challenges

There are a number of common challenges to be aware of when trying to manage and implement a new data management strategy for your real estate assets these include:

• Technological Barriers: Older buildings might require significant retrofitting to install modern metering systems.
• Data Silos: Different departments or stakeholders might have conflicting needs or incompatible systems.
• Cost of implementation:Upgrading systems to support automation can be expensive. The initial costs for new hardware (like smart meters and sensors), software for data integration, and the training required for staff to effectively use these new tools can be substantial.
• Knowledge gaps: The lack of in-house technical expertise to manage and interpret automated data systems can be a significant barrier. Real estate companies may need to contract with external services or provide extensive training to existing employees
• Maintenance of systems: Automated systems require ongoing maintenance to ensure they function correctly and efficiently. The need for regular updates, troubleshooting, and repairs can introduce downtime and additional costs.
• Scalability: When implementing any data strategy you need to take into account scalability. As properties or portfolios grow, the data management system must scale accordingly. Scalability challenges include managing larger volumes of data, integrating data from new assets, and maintaining performance.

By assessing and upgrading your data collection and management practices, you can significantly enhance the operational efficiency of real estate assets, leading to better performance and sustainability outcomes.