Many assume that the measure of success for an optimization program is a high testing velocity. The problem here is that in order to support a high velocity, other parts of the test development pipeline become neglected, including developing a well thought out hypothesis.
How critical is a test hypothesis to the success of a test? What goes into developing a test hypothesis and why is it important? What happens when that part of the process is neglected? What is more important, velocity or proper planning? Is there a metric above all others when it comes to measuring the success?
On this episode of the 33 Tangents podcast, Jim is joined by Jason Boal to wrap up the series on optimization programs. They discuss why a test hypothesis is a key part of the processes of running an optimization program and gaining support from executive leadership.
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