Yes, but they tell things and maybe forget to mention certain things or contradict other data they have given you. Now we may not notice it initially until we make an experiment and get the results. Something is wrong and we have to find out what. Talk to the customer again. Fix experiment. Repeat. Faster experiments means the latency from new data to results is less and we finish the project faster. Errors become less expensive and cause less delays. People make errors and data quality is often horrible so the shorter iterations are nice.
But the experiments aren't two weeks of boilerplate. Or if they are, something else is really fucked up in the stack.