Great input
Wow, thanks for all the input- A few points seem to stand out:
1. Although realtime maybe questionable, it sounds like collecting the data, building the 'normal' models, and looking at variations might be useful for training, safety, design.
2. The qualitative vs. quantitative aspect is a very real and is always an issue- In the diapers=beer sales example, it took exit surveys to understand the correlation; mom yelling go get some diapers, dad going to the nearest store and grabbing the beer to calm the nerves.
But considering underfire's example 'low on glideslope, would required a whole bunch of real-time in/out data correlated with the ground, the landing system at the airport, ATC instructions', with enough data collected and crunched ahead of time, it seems logical that a normal profile, that includes lots of variation, would emerge. Equipment, performance parameters, lots of other variables would be predefined, so real time analysis would be limited to conditions well outside of normal-
If the dive is to avoid a flight of geese, the pilot knows what he did and why he did it and the system could award him for quantifying unusual behavior.
Yes the GE program looks extremely interesting, but I have nothing to do with it - I work with non-aviation technology and healthcare companies to collect user needs, the thinking of 'thought leaders' (who provide the 'out of the box' aspect), and look for matches with short term and long term feature-functionality. Add some risk/benefit and return on investment analysis and we put together product roadmaps-
It's fun to project this thinking into aviation and it's always fun to find other like-minds out there, so thanks for the input!
Cheers,
ZS