Food and Beverages at Southwestern University Football Games
Southwestern University (SWU), a large state college in Stephenville, Texas, 30 miles southwest of the Dallas/Fort Worth metroplex, enrolls close to 20,000 students. The school is the dominant force in the small city, with more
students during fall and spring than permanent residents.
A longtime football powerhouse, SWU is a member of the Big Eleven conference and is usually in the top 20 in college football rankings. To bolster its chances of reaching the elusive and long-desired number-one ranking, in
2010 SWU hired the legendary Bo Pitterno as its head coach. Although the number-one ranking remained our of reach, attendance at the five Saturday home games each year increased. Prior to Pitterno’s arrival, attendance
generally averaged 25,000 – 29,000. Season ticket sales bumped up by 10,000 just with the announcement of the new coach’s arrival. Stephenville and SWU were ready to move to the big time!
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With the growth in attendance came more fame, the need for a bigger stadium, and more complaints about seating, parking, long lines, and concession stand prices. Southwestern University’s president, Dr. Marty Starr, was concerned not only about the cost expanding the existing stadium versus building a new stadium but also about the ancillary activities. He wanted to be sure that these various support activities generated revenue adequate to pay for themselves. Consequently, he wanted the parking lots, game programs, and food service to all be handled as profit centers.
At a recent meeting discussing the new stadium, Starr told the stadium manager, Hank Maddux, to develop a break-even chart and related data for each of the centers. He instructed Maddux to have the food service area break-even report ready for the next meeting. After discussion with other facility managers and his subordinates, Maddux developed the following TABLE 1 showing the suggested selling prices, and his estimates of variable costs, and the percent revenue by item. It also provides an estimate of the percentage of the total revenues that would be expected for each of the items based on historical sales data.
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