Is revenue management just a “black box?” Have the technical challenges been solved in creating a software that can optimize the rent yield in apartment communities? What’s the math behind revenue management? A new technical white paper answers these questions and many more.
In a recently published white paper, “The Implementation of an Apartment Dynamic Pricing System,” Dr. Jian Wang, vice president of research and development for The Rainmaker Group, describes in great detail the implementation of an apartment dynamic pricing system with particular emphasis on setting optimal rental rates for new leases. The system he describes “has been helping several leading apartment operators offer prospective tenants a menu of rent options for the last six years. It sets the optimal rents everyday, which are presented in the form of unit type, move-in week and lease term.
Apartment operators struggle with a myriad of issues, one of the most important is setting rental rates for new and renewal leases. Traditionally, rents are typically set with the goal of achieving market share, maintaining occupancy and remaining profitable. Rents are determined by various factors including market condition, competition, condition of property, and vacancy rates. Management experience also plays a role in determining rental rates.
Revenue Management (RM) has emerged as another way to determine lease rates for apartment operators. This methodology uses data-driven pricing to find the optimal price for individual apartments based on current and forecasted market conditions. Apartment Revenue Management Systems (RMS) is a rapidly growing trend for setting rental rates in the apartment industry. Once limited to the airline and hotel industries, RMS has seen significant growth in the apartment industry since multifamily-specific software hit the market several years ago.
The article includes a study of the characteristics of apartment rental firms compared to hotels from a revenue management perspective. The characteristics that apartments and hotels share:
- Both are perishable products (they are worthless until they are occupied again)
- Both have constrained supply (there’s only so much to go around)
- Both are effected by advance consumption decisions (customers reserve product before using)
- Both have censored demand observations due to product availability and/or pricing constraints
However, the apartment industry does distinguish itself with the following characteristics:
- Longer lengths of stay
- Fewer transactions
- No repeat customers
- More renewals
- Riskier decisions
- No group booking
- No walk-ins
Dr. Wang outlines his expert view on the design of an optimal multifamily revenue management system with modules including:
- Data Aggregator – links the property management systems and the RMS
- Statistics Operator – estimates a number of business statistics based on the aggregated historical data
- Demand Forecaster – predicts the remaining unconstrained demand for a finite planning horizon, which will be fed into the Rent Optimizer module
- Supply Forecaster – predicts the number of units available for lease for a finite horizon of future weeks
- Reference Rent Calculator – estimates reference rates
- Rent Optimizer – calculates optimized rents from which the optimal rental rates are derived in the Rent Recommender module
- Rent Recommender – module that recommends optimal rents by disaggregating optimized rents
Dr. Wang has more than 16 years of experience in mathematical modeling, system architecture, and implementation in engineering and software vendor industries. He’s a demonstrated leader in operations research and is published in several top journals.