Apartment / Multi-family Housing
About the industry
The Bureau of Labor Statistics considers the Apartment/Multi-family Housing industry to be part of the Real Estate and Rental and Leasing sector. In a brief overview of this sector, the BLS writes, “The Real Estate and Rental and Leasing sector comprises establishments primarily engaged in renting, leasing, or otherwise allowing the use of tangible or intangible assets, and establishments providing related services. The major portion of this sector comprises establishments that rent, lease, or otherwise allow the use of their own assets by others. The assets may be tangible, as is the case of real estate and equipment, or intangible, as is the case with patents and trademarks. This sector also includes establishments primarily engaged in managing real estate for others, selling, renting and/or buying real estate for others, and appraising real estate. One of the main components of this sector are the real estate lessors industries (including equity real estate investment trusts (REITs)).”
How do we serve your industry?
Competitive Analytics delivers data and analytics solutions to best in class apartment companies such as Irvine Apartment Communities, Camden Realty Trust, Western National Group, FarWest Management Corporation, C.J. Segerstrom, E&S Ring Management Corporation, Sares Regis Group, Shea Apartment Communities, Lyon Realty Advisors, and Shores. Competitive Analytics collaborates with owners, managers, and investors of multifamily portfolios by conducting proprietary portfolio and market analyses – empowering executives to make better and faster decisions. Typical assignments include rent optimization, premium optimization, demand & supply forecasting, product segmentation, competitive rankings, development and acquisition feasibility analysis, rehab ROI decision modeling, demographic and psychometric forecasting, and integration of our proprietary software, DECIPHER™. In essence, Competitive Analytics collaborates with forward thinking apartment owners that place a high priority on business intelligence and predictive analytics.
Our proprietary RVO model (i.e. Rent-Value-Optimizer) is an innovative profit maximizing tool based on six vital forces: 1) Renter’s relationship between “rent” versus the “value” assigned to all tangible and intangible features and amenities for a specific neighborhood, apartment community, floor plan, and unit; 2) Identifying target and market equilibrium occupancy levels; 3) Competitive and analogue price/value relationships; 4) Unit by unit value/premium adjustments; 5) Micro-economic trends; and 6) Macro-economic trends. In essence, our RVO model is based on the pure additive and synergistic relationship of rent paid versus a renter’s perspective and assignment of value of the tangible and intangible amenities received. This is truly unlike any method for evaluating the economics of multifamily development, operations, and management. Additionally, our RVO model allows for myriad assumptions to be adjusted by the client for an infinite number of scenarios to be evaluated. In contrast, software programs such as YieldStar, Rainmaker, and Yardi, albeit excellent inventory pricing and property operations software, require significant upfront fees, extensive training, high per unit costs . . . and do not provide feature-specific valuation estimates nor provide external micro and macro “market driver correlation” to apartment market performance.
CA’s custom “unit-by-unit” premium analyses provides unit-by-unit pricing via myriad primary premium/discount drivers. Each unit within an apartment community is assigned a unique premium/discount based on the location of the unit within the complex, the characteristics of the unit, and the externalities which positively and negatively affect the unit. A dynamic heat map is also employed to visually display the premiums/discounts for all units, buildings, and floor levels.
Demand & Supply Forecasting
CA’s demand and supply models evaluate historical, current, and forecasted apartment demand for myriad consumer segments cross tabulated by numerous product types. Competitive Analytics employs over 30 unique apartment demand models which calculate “net demand” and “relative net demand” which leverage off our extensive time series database of well over 100,000 economic and market indicators.
CA’s analysis of apartment product trends are classified through a taxonomy of nine primary “segmentation attribute categories” encapsulating over 800 specific product segment features. Our proprietary product segmentation models are designed with interactive data visualization dashboards in order to quickly determine which product segments are in high or low demand and/or which product segments are trending positively or negatively over historical and forecasted time periods.
CA provides custom and interactive ranking models and heat maps by company, apartment community, and/or geo-submarket.
Development and Acquisition Feasibility Analysis
Our development and acquisition feasibility analysis includes extensive revenue scenario analytics overlaid with comprehensive risk assessment modeling (i.e. project, competitive, geo-submarket, market, and political risks) which output to interactive multi-scenario ROI forecast models.
Rehab ROI Decision Modeling
CA conducts comprehensive rehab feasibility analyses which evaluate the cost and rent/value relationship of all potential upgrade (or downgrade) scenarios that may involve internal and/or external amenities. Models also involve the analysis of marginal rent increases/decreases and break even analysis when amenities are upgraded/downgraded. Our extensive rehab ROI analytics process involves identifying, assessing, analyzing, and recommending key amenity components driving market rental rates within a designated competitive market area. Methodologies include conducting comprehensive primary and secondary market research as well as econometric modeling, distribution analysis, statistical modeling, scenario analysis, and the incorporation of several proprietary valuation models.
Demographic and Psychometric Forecasting