case study accounting

This case examines the financial reports for a tourism improvement district and discusses its need to develop a revenue forecast. Assessment revenue is collected by tourism improvement districts and is used to fund destination marketing initiatives. The Ventura County Lodging As- sociation has identified an opportunity to more effectively manage a large cash reserve ac- count and the expected revenue it may collect moving forward. Students are provided with the resources to develop revenue forecast scenarios using tourism district and hotel performance benchmarking data.

Introduction

The four-city area is in the western coastal part of Ventura County, separated geographically by the Santa Monica Mountains to the east and north. This area has several recreational areas including the Channel Is- lands National Park, beaches, and hiking trails that attract visitors seeking to escape to the outdoors. These cities naturally joined together to promote the region and are adjacent to established tourism districts (Tucker, 2019c) serving the Santa Barbara area to the north and Conejo Valley to the West .

Source: VCLA

The VCLA mission is to drive tourism or room night demand through targeted marketing, event development, sales, and public relations (Tucker, 2019b). The advisory board that oversees the association’s activities cur- rently consists of operators of the lodging properties, such as hotel general managers, hotel sales directors, and representatives from city level tourist boards. There are more than 60 lodging properties in the area, which can be classified as hotels, motels, bed and breakfasts, and recreational vehicle (RV) resorts. The as- sociation receives assessment revenue to fund its promotional activities through a 2% assessment collected from the four cities that are part of the VCLA. This assessment is collected proportionally on every room night a guest stays at a lodging accommodation. Once the city has collected the assessment from the lodging prop- erties, the funds are deposited in the VCLA’s bank account. Therefore, the revenue generated by the VCLA is contingent upon hotel demand and the daily rate visitors to the area spend at lodging properties.

Since its inception in 2011, the VCLA has been building a cash reserve for emergencies and other short-term needs. As a result of only depositing funds in the account, and never needing to make a withdrawal, the re- serve had grown to over USD 2 million by late 2018. The funds had been held from the start in a simple money market account at a regional bank.

At one of the VCLA board meetings, it was decided to investigate options to manage this reserve account more effectively and to address two concerns. The first concern was that the VCLA funds were in a simple ac- count that was not earning optimal interest rates which may be available through other financial institutions or instruments. The second concern involved the Federal Deposit Insurance Corporation (FDIC), which insures coverage only up to USD 250,000 per entity. In other words, if the bank failed, the VCLA would be at risk of being unable to recover USD 1.75 million, since the funds were held at one institution. Hence, the VLCA de- sired a prudent short-term asset account management strategy that offered additional insurance protection, competitive rates of return, and alignment with its financial goals. To determine the best financial instruments to invest the USD 2 million already in the account, as well as the revenue it expected to receive in the coming year, an assessment revenue forecast was required.

Assessment Districts

An assessment district is an entity “formed to finance improvements when no other source of money is avail- able” and is created “by a sponsoring local government agency, such as a city or county” (California Tax Data, 2020). The Ventura County Coast is an assessment district that provides specific benefits to payers by fund- ing marketing and sales promotion efforts for assessed businesses. The district was created in 2011 as the Ventura–Oxnard–Camarillo Tourism Business Improvement District by Ventura City Council Resolution No. 2011-023 (Hoffman, 2015). As a non-profit and assessment district, the VCLA cannot levy taxes itself but is able to partner with city officials to create the tax required to fund its operations.

The assessment rate is 2% of gross short-term (stays less than 31 days) room rental revenue. Based on the benefit received, assessments will not be collected on stays of more than 30 consecutive days. The cities are responsible for collecting the assessment on a monthly basis (including any delinquencies, penalties, and interest) from each lodging business located within their jurisdiction. The cities are expected to take all rea- sonable efforts to collect the assessments from each lodging business.

Transient Occupancy Tax

Taxes are levied by governments on their citizens at various levels, including federal, state, county, city, and district level. The taxes generate revenue that is used to fund a variety of programs and initiatives, including national defense, education, courts, highways, and other infrastructure projects, workforce development, and, as with this case, bolstering a specific industry such as tourism. Taxes can be levied on specific industries or sectors to further support economic development of an area.

Within the hospitality industry, one such tax developed to support city tourism and economic development is a transient occupancy tax or TOT (Tucker, 2019a). Added to the city sales tax, a TOT is a tax levied on guests for each night they stay at a hotel. The revenue from the taxes is then distributed to the entities which proposed the tax to be collected. Depending on the organization and accounting capabilities of the city itself, this revenue is provided to the assessment district in one to three months.

In the state of California, local tourism board assessments range from 1–4% of the nightly rate, depending on the specific city (Civitas, 2017). It may also take the form of a flat rate per night ranging from USD 1–4.50. In the City of Camarillo, for example, a hotel guest pays taxes of 13%, or an extra USD 13 on a USD 100 per night rate. This rate is composed of 9% in city TOT taxes, 2% assessment to support the Camarillo Hotel and

Tourism Association, and 2% to support the VCLA. While a hotel may record a room sale in a given month, it may not provide its tax receipts to the city until a month later, which in turn provides the VCLA with its assess- ment revenue a further two months later.

As occupancy rates and the daily rate increase, so too will the city TOT revenue. With stable public and pri- vate funding for tourism marketing efforts, annual occupancy rates should increase significantly as new mar- keting and sales promotion programs are implemented. Greater occupancy will also produce an increase in TOT and assessment revenues from tourist spending. This represents a substantial return to cities and to tourism improvement districts.

Effect of Seasonality in Hotel Demand

According to Kenton (2019), “Seasonality is a characteristic of a time series in which the data experiences regular and predictable changes that recur every calendar year”. Hartman (1986) referred to this seasonality related to tourism as the reliable and predictable recurrence of tourists. Seasonality for each destination is dif- ferent, but they are commonly impacted by factors such as weather, public holidays, cultural traditions, leisure or business events in the area, family behavior such as summer vacations, as well as their own local attrac- tions (see Figure 2).

Although the number of visitors is a measurement for tourism seasonality, the seasonality of hotel demand can be measured in terms of room nights or, as defined by Smith Travel Research (2020), “as the number of rooms sold in a specified time period.”

Smith Travel Research (STR) provides its clients with various reports that detail key hotel performance met- rics such as demand. One type of report that can capture this data for multiple cities is a trend report. This report can provide performance data by month for multiple years, which can be analyzed to chart the season- ality of the destination. Reviewing this type of data for the four-city area can illustrate the seasonality during the year, which naturally peaks during the summer months when the area’s beach attractions are most popu- lar.

Source: Authors, based on VCLA data

Forecast Development

Any business entity that is accountable to stakeholders or shareholders tries to reduce uncertainty. Business- es plan to be prepared and to anticipate any challenge or opportunity to remain as financially stable as pos- sible within the expected accuracy range (Chien, 2014a). Budgeting and forecasting vary based on the inten- tion and frequency of use. Businesses prepare budgets toward the end of their fiscal year cycle to plan for the following year’s strategies. For most companies, once the budget is finalized before the new fiscal year begins, there is no further change. In contrast, a forecast is not set in stone (Chien, 2014a).

The process of budget preparation often involves different types of forecasting. After a business’s strategies are prioritized and set for the following fiscal year, the next step is to forecast revenue (Besley & Brigham, 2018). Revenue forecast determines the resources required for the operations needed to meet the strategies, as shown schematically in Figure 3. Hence, a business often uses three years of a historical revenue less

expenses (R−E) statement to determine how to adjust past spending trends to support the new strategies (Sowa, 2017). However, the operation budget cannot be fully in place until the capital expenditure budget (CAPEX) is complete and available (Besley & Brigham, 2018). Therefore, businesses often examine neces- sary investment projects to meet their strategies (Chien, 2014b).

The CAPEX involves three types of cash flow forecast: (a) initial outflow of the investment; (b) operational cash flow during the length of the project; and (c) terminal cash flow at the end of the investment project period (Besley & Brigham, 2018). Once the CAPEX cash flow is in place, the finance department evaluates whether the investment project meets specific pre-set criteria. Each business defines criteria based on in- dustry specifics. Examples of criteria measurement tools include payback period, net present value, modified internal rate of return, and economic value add (Matias & Hutchinson, 2016).

Source: Modified by the authors from Besley & Brigham (2018) and Chien (2014a).

When the management team approves the investment project(s), the finance department determines the ad- ditional funds needed (AFN) while forecasting the balance sheet statement. Once the AFN are in the balance sheet, the amount of the capital cost circles back to the R−E to finalize the new year’s budget (Besley & Brigham, 2018). However, the process continues throughout the fiscal year to re-forecast when the manage- ment team monitors the budget compared to the actual spending. Re-forecast can occur weekly, monthly, or as frequently as needed in the business (Chien, 2014b).

Revenue Forecast Application

A revenue forecast is needed to determine the expected income for the VCLA accounts. The development of a revenue forecast and the accuracy of the forecast starts with various assumptions. There are several assumptions that VCLA needed for a five-year revenue forecast. Both macroeconomic and microeconomic indicators of future hotel demand should be evaluated. There are three types of assumptions to consider: (a) industry growth rate benchmark; (b) overall U.S. economic indicators; and (c) internal historical sales trend.

Industry Growth Rate Benchmark

Two hotel performance benchmarks in the hospitality industry are the reports produced by STR and Coldwell Banker Richard Ellis (CBRE). STR produces various hotel performance reports that allow hoteliers to bench- mark their performance relative to competitors on key performance indicators, and to understand how a mar- ket is performing overall. The CBRE report provides information on real estate market conditions.

Both STR and CBRE reports provide local data and historical trends to help establish local industry bench- marks. Analyzing these local industry benchmarks helps lodging properties to set their sales goals. Hence, the first key assumption is the local industry growth rate, which can be used in forecasting VCLA revenue.

The STR and CBRE reports can provide occupancy and average daily rates, room demand, and room rev- enue for properties that report their data. Room demand and revenue are particularly valuable in illustrating historical trends. The average local industry growth rate trend is determined by averaging monthly changes in demand and revenue using the last five years of data; that is, by taking the five years of monthly changes in demand and averaging them into one number. The result represents the average growth rate for forecasting purposes. Additionally, the average growth rate can be used to determine how the VCLA is performing rela- tive to the local industry and where it will be in the future—and thus how to account for future projects that VCLA will need to implement to meet any further demand.

Overall U.S. Economic Indicators

Besides industry growth rates, firms need to consider more broadly the current health of the U.S. economy by using the Federal Reserve interest rate, inflation, unemployment, and wages growth figures. These macro- economic indicators are often used in forecasts in the context of understanding how the U.S. economy may affect demand within the cities of the VCLA. Macroeconomic indicators ultimately affect how much revenue the VLCA will generate in the next few years.

Historical Sales Trends

The last assumption arises from analysis of the historical R−E. The historical R−E illustrates the trend of growth (or loss) in the sales and net profit margin. In a not-for-profit organization, the net profit is added to the assets in the balance sheet. Net profit margin is net income divided by sales. Unlike for-profit organizations, the net income of not-for-profit organizations is recorded in the assets (or reserve) in the balance sheets, rather than as retained earnings. The historical R−E trend informs us about the average monthly operating expenses needed to support the growth of the sales trend. The average monthly operating expenses also determine the need for how much liquid short-term assets need to be set aside in case of emergency.

Short-Term Reserve Accounts Management Strategy

The short-term reserve accounts management strategy of the VCLA is shown schematically in Figure 4 and is as follows:

· Operation account is for daily operations such as fixed or variable expenses.

· Emergency funds account is liquid and provides necessary cash in case of deficiency of the opera- tion account.

· Short-term reserve account is a short-term reserve that houses an investment time horizon of less than one year.

· Long-term reserve account is a long-term reserve that houses an investment time horizon greater than one year.

Source: Developed by the authors

Each of the accounts houses 3 months’ worth of average monthly operating expenses. The strategy of four separate accounts was included in the request for proposal (RFP) for local financial institutes to bid for the account management. Five of the 16 bidders were selected to present their plans to the VCLA board. Two firms were selected to implement their short-term reserve account management strategy for VCLA.

Table 1 illustrates four accounts and the appropriate insurance. The Securities Investor Protection Corpo- ration (SIPC) protects in the event that a brokerage firm fails. SIPC insurance covers deposits up to USD 500,000 per entity and per financial institution. Some financial institutions offer extended SIPC coverage to their customers.

Competition and Risk Scenarios

The neighboring counties of the VCLA area, such as Santa Barbara and Los Angeles, are also competing for tourism and lodging business, as are all other counties in California. This competition was part of the impetus for the VCLA to form originally, because even though the hotels within the association compete with each other, their goal is to increase aggregate demand such that all members benefit.

The 2008 Great Recession was integral in spurring the creation of the VCLA. Economies experience cycles, so it is only a matter of time before the next downturn, which could once again severely impact demand for VCLA member business. When another downturn occurs, the VCLA would likely increase its spending on marketing activities with the hope of increasing, or at least maintaining, market demand.

To anticipate competition and macroeconomic risk, it is necessary to develop scenarios for sensitivity testing of the forecasts. To execute multiple scenarios, assumptions for demand growth need to be established to reflect changes or the impact on the R−E.

The revenue available to the VCLA for direct marketing activities is contingent on the amount received through assessment collections, which governs how large its budget will be for the year. Should demand sig- nificantly fall, the VCLA would need to use its short-term assets to supplement its funding for annual market- ing projects to help increase demand and drive more revenue. By examining the effects of demand swings, such as a 10% increase or decrease, strategies can be formed for how to address such scenarios. The VCLA occupancy rates are between 75% and 80%, so if they drop into the percentage range of low 70s to high 60s, they would likely begin to start withdrawing from their reserves to try to increase demand. If they were to increase demand so occupancy rates were in the 80%+ range they would view this as a very healthy signal and would focus on identifying what marketing strategies helped lead to that success.

Since the four short-term assets accounts have been identified, it is necessary to forecast three years of ex- pected revenue so that it can be defined how these are funded. Additionally, baseline, worst, and best-case scenarios are required to reduce uncertainty and determine allocation to the short-term assets accounts.

Further Reading

Association for Financial Professionals. (2014, June). AFP financial planning and analysis learning system ( 2nd ed.). Association for Financial Professionals.

Davidson, W. N. (2017). Financial forecasting and decision making. American Institute of Certified Public Ac- countants.

Sacks, A. , & Ryan, A. (2017). Lodging tax burden assessment. Oxford Economics.

Samonas, M. (2015). Financial forecasting, analysis, and modelling: A framework for long-term forecasting

(Wiley finance series). John Wiley & Sons.

Smith Travel Research. (2019). Trend report: Ventura, CA area selected properties. Hendersonville, TN.