Question

1.A) In abut 5 lines explain how associative methods of forecasting differ from Time series methods of forecasting.

B) Which one would you use to explain how the demand for pork might affect the demand for beef?

2. What all does Hard Rock Cafe's Point of Sale (POS) system capture? At what level is the information aggregated?

3. A) In about 5 lines, discuss the key differences between Time Series method of forecasting and Qualitative Methods of forecasting.

B) Name 3 methods of forecasting under each method.

Forecasting at Hard Rock Cafe

With the growth of Hard Rock Cafe from one pub in London in 1971 to more than 145 restaurants in 60 countries today came a corporate-wide demand for better forecasting. Hard Rock uses long-range forecasting in setting a capacity plan and intermediate-term forecasting for locking in contracts for leather goods (used in jackets) and for such food items as beef, chicken, and pork. It's short-term sales forecasts are conducted each month, by cafe, and then aggregated for headquarters view.

The heart of the sales forecasting system is the point-of-sale (POS) system, which, in effect, captures transaction data on nearly every person who walks through a cafe's door. The sale of each entree represents one customer; the entree sales data are transmitted daily to the 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 cafe. The general managers of individual cafes tap into the same database to prepare a daily forecast for their sites. A cafe manager pulls up prior years' sales for that day, adding information from the local Chamber of Commerce or Tourist Board on upcoming events such as a major convention, sporting event, or concert in the city where the cafe is located. The daily forecast is further broken into hourly sales, which drives employee scheduling. An hourly forecast of $5,500 in sales translates into 19 workstations, which are further broken down into a specific number of waitstaff, hosts, bartenders, and kitchen staff. Computerized scheduling software plugs in people based on their availability. Variances between forecasts and actual sales are then examined to see why errors occurred.

Hard Rock doesn't limit its use of forecasting tools to sales. To evaluate managers and set bonuses, a 3-year weighted moving average is applied to cafe sales. If cafe genera 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.

An even more sophisticated application of statistics is found in Hard Rock's menu planning. Using multiple regression, managers can compute the impact on demand of other menu items if the price of one item is changed. For example, if the price of a cheeseburger increases from $7.99 to $8.99, Hard Rock can predict the effects this will have on sales of chicken sandwiches, pork sandwiches, and salads. Managers do the same analysis on menu placement, with the center section driving higher sales volumes. When an item such as a hamburger is moved off the center to one of the side flaps, he corresponding effect on related items, say french fries, is determined.

Answer 1

1. Associative, and Times series methods use the past data to forecast. The time series method has an assumption that history will repeat itself, and there are identifiable patterns in all the behaviors in the present and the future. The method is useful in the earlier short term stages of the product. There are two types: additive and multiplicative. The additive method includes adding or subtracting the quantities, whereas the multiplicative method helps the researchers to get a percentage. On the other hand, the associative method is also a casual model. It is a method that finds other variables that can predict the primary variable for its interest. It assumes that there is a historical relationship between the dependent and the independent variables. It also states that each variable is easy to predict. The associative method can provide a better relationship between the demand of the pork and the beef demand. It is because these are two variables dependent on each other. They also have a historical relationship.

2. The Point of Sale method of forecasting captures the consumers' data as soon as they enter the café. The method records the sales of each customer. The Hard Rock Café transfers the data to the Orlando corporate office to record the financial data and predict for the future. The forecast happens daily, based on sales. However, it is also possible that the forecast might be wrong because of the changing environment.

3. The time series method of forecasting uses past data to forecast the sales or gains. The method involves numbers to forecast. On the other hand, the qualitative method of forecasting involves the researchers' judgments and opinions. The time-series data is better because it uses numbers to prove the data. Nevertheless, the qualitative method only uses judgments, which can differ from one researcher to the other.

4. The time series method of forecasting includes auto aggression, moving average, and vector auto aggression. On the other hand, the qualitative method of forecast includes Delphi Method, Executive Opinions, and Salesforce polling.

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