Case Study Hard Rock Cafe

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Case study:Forecasting at Hard Rock Café

1. Hard Rock uses a 3- year weighted moving average to evaluate to evaluate managers and set bonuses and determine the café sales. A moving average is also used in which they applied 20% to sales 2 years ago. Using multiple regression, managers can compute the impact on demand of other menu items if the price of one item is changed.

The three other areas which we think Hard Rock could use forecasting models are: •Computerized Scheduling software- plugs in people based on their availability for the daily forecast •Monthly forecast of guest counts, retail sales, banquet sales, & concert sales at each café •Point-of-sale (POS)

2. The heart of the sales forecasting system is the point-of-sale system (POS), which, in effect captures transaction data on nearly every person who walks through a café’s door. The sale of each entrée represents one customer, the entrée sales data are transmitted to Orlando Corporate Headquarters’ database. There, the financial team, headed by Todd Lindsey, begins the forecast process. Lindsey forecasts monthly guest counts, retail sales, banquet sales, and concert sales (if applicable) at each café. The general managers of individual café’s tap into the same database to prepare a daily forecast for their sites. A café manager pulls up prior years’ sales for that day, adding information from the Local Chamber of commerce of Tourist Board on upcoming events such as a major convention, sporting event, or concert in the city where the café is located. 3. If café general managers exceed their targets, a bonus is computed. Todd Lindsey, at Corporate Headquarters, applies weights of 40% to the most recent year’s sales, 40% to the year before, and 20% to sales 2 years ago in reaching his moving average.

4. Unit sales, hourly sales, payroll and interest rates are some of the variables that could be used as good predictors of daily sale2s in each café.

5.

Months...
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