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Lease-analysis programs.

Throughout the 1970s and early 1980s, many real estate ventures were structured on the back of an envelope and supported with rudimentary cash-flow analyses. Today, however, most analysts agree that the real estate industry is becoming more conventional. There are fewer mavericks and more institutional players. Real estate assets are assessed using sophisticated financial software to determine their current market values and monitor their income performance.

As lenders and investors look for more solid returns from their real estate portfolios, property managers should be looking for the most efficient way to forecast and monitor the bottom line.

Where we came from

The first automated valuations were performed with pencil, paper, and a ten-key adding machine. By the early 1980s, automated spreadsheets such as VisiCalc and SuperCalc were the rage of financial analysts until the introduction of Lotus 1-2-3. Overnight, Lotus revolutionized the process of analyzing the financial feasibility of potential real estate deals.

The original version of Lotus was reasonably priced, user friendly, and very flexible. In no time, developers, consultants, and lenders were using it to perform cash-flow analyses of potential projects. The beauty of the product was that these spreadsheets could be instantaneously recomputed simply by changing either a value or formula in the spreadsheet, allowing the user to generate as many "what-if" scenarios as time and imagination permitted.

Lotus spreadsheets running on personal computers became the standard of the day. This combination of hardware and software could not be beaten--or so we thought.

Predictably, with the passage of time new competitors crept out of the woodwork with enhanced features and capabilities. We saw the arrival of Microsoft's Excel and the introduction of database management systems such as dBASE II. These products were generic enough to be used by analysts in a wide variety of industries.

Some software houses, however, recognized an incipient demand for analytical tools specific to an industry. In the case of real estate, industry-specific requirements went beyond the capabilities of the simple cash-flow projection with receipts and disbursements spread over time on a generic Lotus spreadsheet.

In order to produce meaningful reports, cash-flow models for real estate needed to combine database management, spreadsheet technology, and graphic representation. They would have to allow users to perform lease-by-lease analysis, prepare before- and after-tax cash flow projections, calculate internal rate of return and net present value for various cash flow scenarios, and perform model financing alternatives that would include both debt and equity.

Thus, real estate-specific software would have to be designed to develop and maintain database information pertinent to a project. The type of information stored by the system would be the property's book value and outstanding debt, lease terms including lease start and expiration dates, and renewal options, as well as economic assumptions such as inflation and vacancy factors.

In addition, any industry-specific software would need to perform both simple algebraic equations and sophisticated calculations for computing annual rent increases, pass-through expenses, escalations, and percentage rent.

Necessity being the mother of invention, software vendors accepted the challenge of satisfying pent-up user demand by developing real estate-specific analytical programs. The first generation of products to hit the market were crude and difficult to use. But as time and technology marched on, these programs evolved into highly complex but efficient modeling systems.

The benefits of industry specificity

The real estate-specific analytical tools of today combine the best features of the leading spreadsheet, database, and graphics software programs. Like Lotus, the primary function of these modeling systems is to generate cash-flow analyses and compute internal rates of return. When using one of the new analytical tools, the user has the option of generating numerous "what-if" scenarios by altering the assumptions, just as in Lotus.

What makes today's analytical tools far more powerful than Lotus is that they are able to closely simulate the projected timing of receipts and expenses on a lease-by-lease basis, whereas Lotus spreadsheets usually are generated using assumptions at a macro or global level with no reference to the specific parameters defined in each lease.

Figure 1 will help clarify the differences between a generic Lotus spreadsheet and an industry-specific tool when creating a property's monthly cash-receipts forecast. Note that the primary difference between the two reports is that the underlying assumptions of the Lotus spreadsheet are processed manually outside of the spreadsheet by the user and the outcome is keyed into the appropriate cell.

On the other hand, the analytical tool takes the terms and conditions of each lease, automatically calculates their financial impact and includes conclusions in the cash-receipts report.

Another distinct advantage of an analytical tool is that the programs have decision-making logic built into them, whereas a generic Lotus spreadsheet has no inherent intelligence. Most real estate analytical tools recognize revenue on a lease-by-lease basis. When a lease expires, the systems generally terminate the recognition of revenue.

In some products, the system is programmed to decide whether it makes good economic sense to assume that the lease would be renewed or accept a new tenant at the market rate with a lease-up factor. This decision incorporates both database and financial information. The expiration date and the renewal option terms are database fields, and the market rate is either stored in a table or computed using the base rate multiplied by an inflation factor.

Another advantage of an industry-specific analytical tool compared to a generic Lotus spreadsheet is that the programs and data in the former are independent of each other. The user is responsible for the assumptions stored in the static data files but has no access to the programs. Thus, when a project is saved, the user is saving only information associated with the project and not the programs.

Conversely, when a Lotus model is saved, the data, formulas, and spreadsheet are saved together. Hence, if a project has multiple scenarios, each individual version must be stored separately. The result is a higher probability that a calculated cell may be accidentally amended. And because most financial analysts maintain a library of many scenarios, there is a strong likelihood that they may eventually lose track of what file is saved and where it is stored.

The new analytical tools also provide both financial and non-financial standard reports. The financial reports include traditional balance sheets and income statements as well as cash-flow projections. The nonfinancial reports include vacancy, aged receivables, leased-versus-leasable square footage, and lease expiration. Furthermore, most of the leading products offer the ability to export data into a generic spreadsheet package for further analysis and consolidation.

Choosing an industry-specific program

A decade ago, there was a proliferation of real estate-specific spreadsheet software. As the needs and demands of analysts become more complicated, so do the programs required to satisfy them. In the last few years, for example, users have seen the release of a number of software programs targeted specifically to asset managers, institutional investors, and lenders. Some of these programs have fallen by the wayside; others have been enhanced to better serve the market.

Yet even with the presence of several real estate-specific analytical programs on the market, there is no one product available that will handle the reporting needs of every potential user. Thus, when looking for software, it is critical that the user's requirements be defined and compared to the features and functions of the product being considered. This process of mapping requirements against features helps ensure that the user's expectations will be met.

Commercial programs

For those interested in commercial and retail property management, it is essential that the product being evaluated have the ability to calculate pass-through expenses based on a tenant's prorata share of square footage. In the case of retail, the system should have the ability to compute percentage and overage rent based on tenant sales data.

It is these ancillary computations combined with the ability to generate rent rolls, exercise renewal options, and calculate Consumer Price Index increases that differentiate one product from another.

As a general rule, when reviewing a product to determine whether or not it has the ability to satisfy current needs as well as future requirements, evaluators should compare the reports generated by the new program to the standard reports generated by the analytical tool currently being used.

The cornerstone of any analysis for office, retail, or industrial buildings is based on the terms and conditions defined in each lease. It is the financial impact of these terms that is computed and analyzed with the assistance of an industry-specific analytical tool. The common denominator of leading products on the market today is that they are lease-driven, which allows the user to generate an analysis that closely simulates the actual terms defined in each lease on a lease-by-lease basis.

Some programs allow a model or standard lease to be created in the absence of actual lease data. These standard leases usually require minimal information such as the lease identifier, leased square footage, recurring charges, and lease commencement and expiration dates.

When evaluating a program to analyze commercial property, the reviewer should make sure that the system can handle the basic routine processes such as generating a monthly rent roll, computing escalation increases and pass-through recovery calculations, as well as generating nonfinancial reports. Some of the more advanced products permit the user to handle complex multi-tenant properties with intricate lease structures and many unique rent roll charges.

Multifamily programs

Software programs that serve the needs of multifamily residential analysts are often less demanding and easier to use than office or retail analytical tools. While most of the leading packages are still lease driven, residential leases tend to have many fewer terms and conditions than commercial ones.

Lease information may require a significant time investment on a commercial program, whereas residential systems usually require only a small quantity of data. This information may include tenant name, monthly rent, security deposits, and lease expiration dates.

At first blush, an analyst may decide to use the same commercial analytical tool for a residential property. In theory this solution is workable, but because commercial systems have so many required fields, a user may quickly recognize the benefit of investing in another product specifically designed for multi-family. Note that a multifamily product seldom, if ever, has the ability to support commercial, industrial, and retail properties.

Future options

Computerized analytical tools such as those described in this article have set new standards in the real estate industry for evaluating both current and potential projects. However, the systems are fairly complicated and require an understanding of the intricacies of real estate and financial statements to operate successfully. They are not for the average user.

Integration of financial analysis software with off-the-shelf accounting packages will be the next step in the evolution of real estate systems as additional reporting requirements are taken on by institutional owners and investors.

The current lack of integration means that the user must manually move data from the primary accounting system to the analytical tool, a process that may include reformatting and converting the data prior to the upload. This transfer may not be technically difficult for an experienced programmer, but it can be very complicated for the average user.

Software vendors, recognizing the need and demand for seamless integration, are starting to design their systems with the appropriate "hooks" in place to send and receive data from other systems. This concept of integrating different systems to support a variety of functions based on the information residing in a centralized database will clearly underlie the next generation of computerized financial-analysis systems for the real estate industry.

[Stuart B. Siegel is a manager in the Management Information Systems Group of Kenneth Leventhal & Company's Los Angeles office.]

[Kenneth Leventhal & Company is the country's eighth largest accounting and consulting firm, known for its expertise in real estate and financial services. It has offices in 13 cities and is affiliated internationally with Clark Kenneth Leventhal.]
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Title Annotation:Computers; real estate investment analysis software programs
Author:Siegel, Stuart B.
Publication:Journal of Property Management
Date:Sep 1, 1992
Previous Article:New demands from pension fund investors.
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