Menlo Machine Learning

In software engineering identifying a flaw in production is two orders of magnitude more expensive then finding it in the design phase.

Similar patterns holds with machine learning.  Spending the effort up front to think hard about how to frame the question almost always pays off in lower costs and better results.  As Clayton Christensen reminds us “asking the right questions is more important than getting the right answers”.