Revenue Management for Today and Tomorrow
Guest Blog Post by IREM staff memberJoel Felix, Senior Curriculum Developer from the Institute of Real Estate Management (IREM).
Revenue management system-based pricing, once reserved for the biggest real estate management companies, has become an increasingly common strategy to establishing apartment rental rates. The basic principle of revenue management has been around for decades: to produce the highest possible yield of revenue. What’s notable today is the growth in implementation of modeled revenue management data lease strategy.
Knowing the real-time forecasting of demand for apartments in a given market is the essence of revenue management. Profits are optimized when leasing strategies are adjusted by not only supply, but by the buying characteristics of specific consumer profiles. For example, business travelers have less flexibility in travel plans than other travelers. The customer with less flexibility is likely to pay a higher price for the flights and hotels than other customers. Having the data at hand to determine the highest-yielding price in apartment leasing situations already implemented in leasing offices of larger management firms. Vendors such as Rainmaker Multifamily, Yardi, YieldStar™, RentRoll™, and AMSI deliver suggested rent prices to property managers by weighing some or all of the following factors: Seasonality, recent demand level, lease application lead times, traffic, lease lengths, concessions, incentives for renewal, and future supply.
Revenue management is both a pricing strategy and a lease administration method. The cost of implementing this strategy has become increasingly approachable for companies with mid-size and smaller portfolios. The impact of wider use of revenue management data is that activities of the leasing office, and the skill sets required for on-site staff, are changing in the multifamily industry. And with change, as ever, comes resistance to change. Many onsite managers may still be resistant to revising their leasing plans based on suggestions from a data-driven model. Many others resist for another reason: property owners may not want to invest in the data without seeing research that proves return on investment.
Despite these resistances, the market of revenue management products is exploding. Is it only a matter of time before the skeptics sign on and present the case for investment in data? And is only a matter of time before revenue management jumps the divide to office and retail leasing? How would access to sophisticated real-time data modeling affect the negotiation between real estate brokers and the office/retail space manager? If the most favorable deal goes to the one with the most data, the future for all lease deals could be data-driven.