BUS-P301 Operations Management

Project

Total Points: 150

Forecasting at Hard Rock Cafe

With the growth of
Hard Rock Cafe – from one pub in London in 1971 to more than 110 restaurants in
more than 40 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. Its
short-term sales forecasts are conducted each month, by café, and then
aggregated for a headquarters view.

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 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 café. The general managers of individual
cafes 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 or Tourist Board on upcoming events such as a
major convention, sporting event, or convert in the city where the café 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
stations, which are further broken down into a specific number of wait staff,
hosts, bartenders, and kitchen staff. Computerized scheduling software plugs in
people based on their availability. Variances between forecast 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 café sales. 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.

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 $6.99 to $7.99, Hard Rock can predict the effect
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, the corresponding effect on related items, say
french fries, is determined.

Hard
Rock’s Moscow Café

Questions:

1. Describe three different forecasting
   applications at Hard Rock. Also identify the nature (qualitative or
   quantitative forecasts) of the forecasting techniques at Hard Rock.

• What is the role of the POS system in
  forecasting at Hard Rock?

• Justify the use of the weighting system
  used for evaluating managers for annual bonuses.

• Using data for the past 10 months (see the
  table), what should you do to determine the best method or methods to forecast
  these date? Explain why if you think a time series model or a regression model
  is better suited here?

• Develop a least squares regression relationship
  and then forecast the expected guest count when advertising is $65,000. Please
  first show the procedure manually on a separate sheet, and then show the
  procedure using MS Excel.

• Name several variables besides those
  mentioned in the case that could be used as good predictors of daily sales in
  each café.

(Note: Please
show your answers in a separate Word/Excel sheet)

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