It is no surprise that leaders not trained in real estate strategy may rely on instinct or casual chatter when making real estate decisions?nor is it a surprise when those decisions fail. Leaders need real estate intelligence: accurate data, synthesized into relevant information, interpreted in the context of corporate and competitive realities. This kind of intelligence allows them to understand trade-offs and to connect real estate decisions to corporate strategy. The foundation of real estate intelligence is a database that includes square footage, occupancy costs, uses, capital values, utilization levels, and other relevant information, arrayed by line of business, function, and location. The data warehouse for a typical portfolio can be voluminous, with 50 or more unique fields for each of hundreds or thousands of properties. The quality and effectiveness of the database increase with scale. So, leaders need a dashboard that focuses only on fundamentals and synthesizes the key issues.
Wise leaders pay more attention to internal measures of facilities? costs, productivity, and utilization than to fluctuations in the real estate market. Four ratios link real estate to business economics:
- occupancy cost per person and per unit
- occupancy cost as a percentage of revenues and/or expenses
- utilization of building space and land, per person and per unit
- asset performance (measured by return on total investment)
Leaders should also insist on periodic reporting of those internal ratios across business units, markets, submarkets, and building types. Benchmarking peers and competitors is no less important, but those data are hard to capture and it may be difficult to find strictly comparable properties in competitors? portfolios.
Real estate deal makers are known for quick back-of-the-envelope analysis. The typical business leader may not be as facile but can use many tools, such as space budgeting, lease decision analysis, and employee location mapping (see the exhibit ?Assess Your Real Estate Performance?). What used to take weeks of effort with occupancy cost formulas and P&L impact analysis can now be done in days or even hours with models that permit real-time iterations as assumptions or goals change.