Many software companies now learn their policies via data-driven methods. Modern practitioners treat every planned feature as an experiment, of which only a few are expected to survive. Key performance metrics are carefully monitored and analyzed to judge the progress of a feature. Even simple design decisions such as the color of a link are chosen by the outcome of software experiments.
This subject will explore methods for designing data collection experiments; collecting that data; exploring that data; then presenting that data in such a way to support business-level decision making for software projects.