KM and the experience curve - a chance to test the model?

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The concept of the Experience Effect has been around for a long time, "first observed by the 19th Century German psychologist Hermann Ebbinghaus according to the difficulty of memorizing varying numbers of verbal stimuli" (according to Wikipedia).

Basically, the experience effect means that the more times you do or produce something, the faster and cheaper it becomes.  The experience effect is measured as a percentage, and its the percentage of the initial cost reached through each doubling of production. So if the first 1000 cost £100 each, and the second 1000 cost £90, the experience effect is 90%

NASA quotes the following experience curves

Aerospace 85%
Shipbuilding 80-85%
Complex machine tools for new models 75-85%
Repetitive electronics manufacturing 90-95%
Repetitive machining or punch-press operations 90-95%
Repetitive electrical operations 75-85%
Repetitive welding operations 90%
Raw materials 93-96%
Purchased Parts 85-88%

Now it struck me that here is the opportunity to test KM. KM also has an effect on the learning curve, and theoretically at least, good KM should result in steeper learning curves and a lower Experience Effect percentage. With poor KM, or no KM, the experience effect should still be there, but a higher percentage.  With good KM, it should be accelerated.

So my question is - is it? Is it actually accelerated? Are percentages lower?

Do we have enough data on learning curves from (say) Shell or Exxon Mobil, where KM is applied rigoroously, to show that good KM can beat the natural Experience Effect?

Or do we have data from Ford's heyday in KM, to show that they could drive costs down faster than "natural experience"?
I don't know the answer, and would be interested in any input. Does anyone have good statistics on learning curves that could answer this?