The article explores how to plan experiments efficiently by using statistical methods to get the most information with the least amount of work. It introduces different types of experimental designs, like full-factorial and fractional-factorial designs, to identify important factors in a list. The researchers set up a 12-run Plackett–Burman screening design to find the most crucial factors from a list of up to 11. They also explain how to analyze the results using free open-source software.