Competition for institutional investment dollars is heating up, following the exponential growth in the number and size of commercial real estate funds. Investors are demanding more financial and operational information about their portfolios. Additionally, investors are looking at automated solutions for collecting this data. With some institutional investors being involved in more than a hundred separate advisory relationships, it has become impractical for them to receive and validate information manually. To remain competitive, management firms will need to implement comprehensive business intelligence solutions that will not only enable effective aggregation of data for internal portfolio management but also will provide a platform for the automated distribution of information to investors. Selecting a business intelligence platform that meets the needs of a commercial real estate organization is an involved task that should be undertaken with the same sense of importance as the purchase of a property management and accounting system.
Commercial real estate investors must be able to accurately assess trends and analytics in their portfolios and ensure they make effective decisions that maximize investment returns. The key to portfolio optimization is data transparency. Data transparency is achieved through a business intelligence strategy. The objective of business intelligence is to make sense of an immense amount of information that exists in a myriad of formats across the commercial real estate enterprise, and present it in a way that allows for intelligent decisions aimed at improving bottom-line results.
In a real estate context, this can have many applications: analyzing leasing patterns to manage occupancy, identifying variances in actual versus budget or pro forma, mining property management data to isolate data-quality issues, monitoring loan-to-value and debt-service coverage ratios to ensure compliance, benchmarking rental rates against market information, calculating and comparing fund performance and property performance with the NCREIF Fund Index, tracking lease deals and calculating net effective rents.
Additionally it is imperative that commercial real estate owners can quickly identify their exposure to a particular type of tenant. A landlord may want to determine their exposure to sub-prime lenders across their portfolio. Having a business intelligence tool provides the ability to proactively manage portfolio risk. Without it, hours are spent trying to compile information from a myriad of disconnected sources, a costly and inefficient process that will ultimately affect the bottom line.
Many real estate owners look to their property management and accounting systems to serve as their business intelligence platform. These systems are optimized for adding, editing and deleting single records and are not built for portfolio-level reporting. Reports and analytics that take seconds to run when a data warehouse is leveraged can take minutes or even hours to run directly from the property management and accounting system. Additionally, implementing a business intelligence strategy limits the impact on users when underlying systems are changed or when new systems are added.
Total Package
The data warehouse is just one part of a robust analytics platform. Many other functions also should be incorporated into a total business intelligence plan. Besides analytics and the data warehouse, the integration platform is of key importance to the strategy. It is essential that an automated extract, transformation and load (ETL) process be implemented. This process should connect data within the enterprise and from external sources. Institutional investors should look to their investment advisory firms to feed valuation models, investment-level financials, operational statistics and property attributes into their organization without the manual re-keying of data into Web forms or Excel spreadsheets or reliance on hard copies. Investment advisory firms should expect the same from their property managers.
Many advisory firms have adopted a model that forces property managers to use a single property management and accounting system for the collection of data. However, with the move away from core investments, advisors must now consider alternatives. Many “opportunity” fund-managers seeking high yields have been provided Excel spreadsheets and hard-copy reports from their joint venture operating partners. This process is error-prone, time-consuming and inefficient. Instead, advisory firms, or any real estate organization involved in an operating partnership, should look to an automated data feed based on a template. The template should be defined from existing data standards. OSCRE (Open Standards Consortium for Real Estate) is in the process of developing a standard for the transfer of property level financial and operational information between real estate owners. Utilizing this standard, an advisor could mandate the automated transfer of information without forcing a partner to move away from their existing systems and internal business processes. Once this information is transferred it can be integrated directly into the business intelligence platform.
Selecting an enterprise-wide business intelligence strategy should not be approached lightly. Real estate organizations should never undertake these strategies without the assistance of a vendor that is an expert in business intelligence and real estate. Many real estate organizations attempt and are sometimes successful at building their own reporting solutions. Once the solutions are built they spend an inordinate amount of time maintaining and upgrading the solution. Resources leave and with them goes the intellectual knowledge required to manage that solution. A commercial real estate company’s corporate focus is not software development. Executive management should be careful to direct their information technology (IT) staff away from development and focus instead on management, support and vendor selection.
An Informed Decision
A primary factor in the selection of a vendor should be their breadth of real estate industry experience. The selection process should include a detailed RFP (request for proposal) that identifies the initial scope of the project but makes it clear that data sources will change over time. The RFP also should attempt to identify the key audiences across an organization and their analytics requirements. High-level factors to consider include: a real estate-specific architecture, the degree of warehouse flexibility, the number of transactional data sources, reporting requirements, security, auditing, dashboards, portfolio consolidations, drill through, drill down, cubes and, most importantly, a logical, easy-to-navigate user interface.
Information transparency and the ability to assemble and analyze information quickly is an essential requirement for the success of any business intelligence strategy. With constant changes in investment strategy and the movement of real estate portfolios between owners, automated integration of data is imperative for the industry. Real estate organizations should look to vendors who take a “best practices” approach to application development and have a proven history of delivery to implement their business intelligence platform.
