To answer your question quickly, not likely.

Do you still have the experimental units? Can you repeat the measurements of them? If so you may be able to reduce the measurement error by averaging the repeated measures.

The first question I would ask the customer is what is practical significance? How much of a change in the response is of practical value? If the practical significance is <0.1, then your measurement system is not adequate. If it is more on the order of >1, then perhaps your measurement system is OK.

If the effective discrimination of the measurement system is to the tenths place, the numbers after that are just random numbers. The problem with measurement system discrimination issues is we don't know if the measurement system is rounding the "true" value up or down or consistently. So errors may be over or under estimated. Whether it matters depends on practical significance.