Selecting Target Markets and Asset Allocation
Client Challenge: On behalf of a private hotel investor with nine large luxury and upper upscale hotels located in downtown locations throughout the U.S., we were recently commissioned to identify the tenth city to help ‘diversify’ the investor’s portfolio. While the investor sought ‘mid-to-high teens’ leveraged returns he had attempted to minimize risk by having no more than about 10% of his portfolio in any one market.
Action: We initially derived the efficient frontier for the portfolio of potential markets for the investor. We then constructed an efficient frontier that incorporated existing holdings and after a series of diagnostic tests, we derived the optimal portfolio allocation for our client.
Impact: Our findings, conclusions, and recommendations were delivered three weeks after we were engaged on this assignment. We recommended that the investor sell two hotels and ‘double’ his investment in three cities as this would provide greater returns with less risk than investing in a 10th city, even after accounting for transaction costs. Our recommendations appeared counter-intuitive to our client but after several discussions and presentations, our client is moving forward with our recommendations.
Note: Despite significant efforts to manage asset-level risk, the investor had spent little time on risk management at the portfolio level. Many investors still discuss diversification in terms of the number of markets and hotel types in which they are invested but spend little time talking about the overall risk level of the market and the extent to which their hotels’ returns are correlated with each other. How volatile are the markets in which the portfolio is invested? How do the market exposures interact with one another and affect the overall volatility of the portfolio? Many investors have the misguided view that risk is proportionately reduced with each additional hotel in a portfolio, when in fact, risk could be growing if the added returns are highly correlated with the returns of existing assets.
Identify Disposition Hotels and Review Role of “Non-Core” Hotels
Client Challenge: On behalf of a medium sized REIT, we were commissioned to model its portfolio and identify the hotels that were or were likely to become impediments to its performance over the next five years. The REIT had initiated a program of harvesting and redeploying capital and had identified six “non-core” hotels for disposition.
Action: Utilizing both univariate and econometric models, we developed RevPAR and annual return forecasts for the portfolio’s hotels and markets. We then optimized the hotel portfolio seeking the highest returns for a given level of risk identified and defined by the REIT.
Impact: On the basis of our work, we recommended that only one of the “non-core” hotels be sold. Retaining five of the “non-core” hotels was likely to increase returns and minimize risk over the next five years. Three hotels, which were perceived as “stars,” were identified as candidates for disposition as they were likely to detract from the portfolio’s performance due to their correlations and future risk profiles. The exposure to “non-core” metros was likely to be helpful in reducing the overall risk of the portfolio over the next five years.
Note: Perhaps the most disconcerting fact about diversification is that it leads to the following paradox: A well-diversified portfolio will always be invested in some hotels that are not performing as well as others. Put differently, such a portfolio will almost always have both sterling and mediocre performers. In many ways, that’s the whole idea. Even so, it requires a lot of financial discipline to stay diversified when some portion of your portfolio seems to be performing in a mediocre way. The payoff is that, over the medium to long run, a well-diversified hotel portfolio should provide much steadier returns and be less prone to abrupt changes in value.
Investment Strategy and Target Market Selection
Client Challenge: On behalf of a new hotel fund, we were commissioned to help formulate an investment strategy, develop overall risk and return objectives, recommend optimal portfolio allocations and target market selection which included cities in Europe and Asia. Our advice was sought on how to implement the portfolio management process and establish a performance benchmarking and monitoring system.
Action: We canvassed a range of options including core, core plus, value-added and opportunistic type hotel investments across high-end chain scales. Detailed risk tolerance standards were developed and risk/return benchmarks were established for a range of potential investments. We established different time horizons and constraints for different markets and derived both strategic and active asset allocations for the fund. We evaluated different portfolio structures and investment vehicles. Finally, we developed performance benchmarking measures to monitor the portfolio’s performance against its own investment objectives and strategies, established benchmarks and competing investment funds.
Impact: The fund has purchased ten hotels in targeted cities and is proactively managing the search process in other targeted cities.
Note: Buying, holding and simply creating a larger portfolio will not necessarily provide the best returns. Once the fund has acquired a minimum number of hotels, diversification hurdle rates will be applied to each new investment to ensure that the portfolio’s risk-adjusted return is not compromised. By embracing MVO at the outset of the fund’s life, the fund is likely to avoid a major and potentially costly strategic repositioning in the future.
PRODUCTIVITY AND PERFORMANCE MEASUREMENT ANALYSIS
Client Challenge: On behalf of a hotel investor who purchased a 28 limited service hotel portfolio, we were commissioned to identify and quantify potential cost saving in all the major hotel departments, including rooms payroll, rooms other, administrative & general payroll and utilities. In addition, the client sought to:
- Identify star performers to locate “best practice”
- Identify under-achievers to locate “poor practice”
- Set realistic, peer-based improvement targets
- Uncover the largest potential efficiency gains
- Allocate portfolio resources more effectively
- Monitor efficiency changes over time, and
- Identify where to give rewards for good performance
Action: Three main stages were involved in conducting the efficiency study:
- Defining and selecting the hotels to use in the analysis
- Deciding which factors to use for inputs and outputs;
- Using Data Envelopment Analysis and interpreting the results.
Impact: We identified potential expense savings of 16% or $4.7 million on total operating expenses of $29 million. This amounted to $253,000 per inefficient hotel.
Note: Surprisingly, productivity analysis of lodging facilities is still performed using measures that fail to capture the complexity of today’s operations. Traditional partial-factor productivity measures do not account for relationships among input resources. Labor productivity, in particular, is often used as a surrogate for overall operational performance, without regard to other relevant variables. Data Envelopment Analysis is a technique that allows for measurement of the relative efficiency of hotels and departments. Its main strength lies in its ability to capture the interplay between multiple inputs and outputs, a process that cannot be satisfactorily probed through traditional ratio analysis which forms the basis of the lodging industry’s benchmarking efforts.