If you’re in line for a coffee at the local Starbucks, analysis conducted by graduate students at Rutgers University suggests that the probability of waiting more than five minutes for your tall, hot, three-pump, sugar-free vanilla, one-pump mocha, half-soy, half-nonfat latte with whip is very high.

Brandon Theiss and Matthew Brown used a reliability engineering project to combine their passions for Starbucks’ coffee and gathering and analyzing data with Minitab Statistical Software.

Theiss drew on his work experience in crafting the study. Currently a principal industrial engineer at Medtronic, he previously was a Six Sigma Master Black Belt at American Standard Brands, and a systems engineer at Johnson Scale Co. In 2010, the American Society for Quality named him one of its Top 40 Leaders in Quality Under 40.

“Virtually anything can be characterized as a process and measured,” Theiss says. “Once you have the data, you can use a tool like Minitab to draw conclusions and hopefully improve the process.”

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