Although data and information have always been critical aspects of real estate asset management, never has it become more pervasive, accessible or powerful than it is today. We often hear of the terms “big data” or “data analytics” being championed in corporate boardrooms globally, but many firms do not understand their full business impact (or benefit). A common challenge with today’s data systems, accordingly, is that they are still being developed to meet the needs of individual departments or for specific business processes, instead of considering larger organizational needs.
Understanding the Silos
Real estate is a complex asset class. Management of it is even tougher.
Multiple teams analyze different aspects of property on a daily basis. You have property management responsible for daily operations. You have accounting in charge of financial reporting. Your portfolio management teams are in charge of monitoring investment performance. Third party firms and consultants are working on transactions and asset lifecycles. However, do you know what critical information each team needs? What about overlaps in data or communications shared across all groups? What about frequency of data, or even the types of systems employed? These are common issues that confound most organizations that own, operate or manage real estate portfolios and infrastructure—plenty of data, but no clear direction as to its use, accuracy or efficiency.
The “Asset- Centric” Approach
An asset-centric data strategy is about taking a bottom-up approach to information and analysis: starting at the individual building level and working upwards. By aligning your data around individual properties instead of departmental needs and business processes, efficiencies are gained as data becomes standardized, compiled and sourced singularly. Envision a private, mid-sized real estate portfolio management firm decided to change their financial and capital needs reporting schedules from quarterly to monthly, but their existing system is a mix of self-managed spreadsheets and legacy programs across different departments. Integrating historical information would be challenging given limitations in tracking dates dynamically, as well as integrating static files for analysis.
An asset-centric data strategy would help mitigate these issues by providing the following:
Flexibility and efficiency: Open data points linked at the property level ensure usability for multiple groups, limiting redundancies in the data gathering process. Data queries are also easier and do not require technical or departmental expertise for reporting and analysis.
Future and past proofing: An asset-centric data strategy allows an organization to respond to changing analytical requirements. You should not have to “start fresh” every time a new report is needed. The information should be continuous and adaptable over time.
Maintaining data standards: Compiling data at a single source also means you ensure data quality. Terminology, numbers, inputs—they are all consistent. Conversely, a top-down strategy means each department uses its own data formats and standards, which often leads to operation redundancy.
By taking an asset-centric approach to real estate portfolio and infrastructure data, your analytics become more responsive to changing operational requirements by letting the data do the work. This creates a highly collaborative environment and company silos, accordingly, become a thing of the past.
Photo: XXLPhoto/Shutterstock
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