With the growth of the Hard Rock Café franchise—from one pub in London in 1971 to more than 129 restaurants in more than 40 countries today—came a corporate-wide demand for better forecasting. Hard Rock Café 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 cafe, 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 cafe’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 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 $5500 in sales, for example, translates into 19 workstations, 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 Café doesn’t limit its use of forecasting tools to sales. To evaluate managers and set bonuses, a three-year weighted moving average is applied to cafe sales. If cafe 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 two years ago in reaching his moving average.
An even more sophisticated application of statistics is found in Hard Rock Café’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, they 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 centre section driving higher sales volumes. When an item such as a hamburger is moved off the centre to one of the side flaps, the corresponding effect on related items, say French fries, is determined.
Using the information about Hard Rock Café provided, write a report that addresses the following areas:
• Describe three different forecasting applications at Hard Rock Cafe, and why you think they are used the way they are. Name three other areas in which you think Hard Rock could use forecasting models.
• The role of the POS system in forecasting at Hard Rock Cafe.
• Justify the use of the weighting system used for evaluating managers for annual bonuses.
• Name several variables besides those mentioned in the case that could be used as good predictors of daily sales in each cafe.
• At Hard Rock Cafe’s Moscow location, the manager is trying to evaluate how a new advertising campaign affects guest counts. Using data for the past 10 months (see the table), develop a least squares regression relationship and then forecast the expected guest count when advertising is $65 000.