I've come across this quote numerous times:
To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of. -- Ronald Fisher (1938)
To me, it seems perhaps a little presumptuous. The only examples I've ever found describing how experiments die without good design are around lack of controls, or poor controls. For example, experiments that control for the application of a fertilizer, but fail to control for the environment required for the application. Maybe it's just me, but it seems that a quick read through the Wikipedia section on Fisher's design principles would cover most bases.
As a statistician, how often do you see design of experiment-related problems with data? Are they always related to those few factors mentioned by Fisher, or or there other serious pitfalls that we non-statistically trained scientists should be looking out for?