When there is difference between component variables and the sum, which should be chosen? Assume a simple example: A survey asks people how much they spent in the last week in total amount and in individual days. As a hypothetical response, one may answered that the Total amount = 10 and every single day (Sun to Sat) = 1. So they are not the same.
What should we do if we find out this difference? E.g., in the data cleaning process in which we sum individual measures to see if it matches withe the total amount. Let's also say that these numbers quite make sense, i.e., they fall within the expected/acceptable range.
 A: To answer this question, you should think about the possible reasons of why the two ways of reporting give different results. Ideally, you should ask each individual respondent what they meant when they gave two different answers. This is rarely possible.
Some ideas. Perhaps your definition of a "week" was different to the one of the participants (e.g. Sun to Sat vs Mon to Sun). 
It's also possible that they thought about specific days, but a typical (as opposed to the last) week, since this is a more abstract category than individual days.
A rounding error might have occurred: only rough estimates were given for daily spending and the uncertainties accumulated.
They might not have remembered their spending for a specific day, but paying closer attention for weekly allowance, memorized their spending better.
Finally, you should keep in mind that the participants might not have cared about such discrepancies; as a participant, I have answered with non-compatible answers, myself. Some information might be hidden in the divergency, perhaps giving you feedback on the quality of your questions. A valid question (thanks to @Tim for hist comment) to ask yourself might also be whether the discrepancy occurs for all participants or just some individuals. If the latter is the case, can that tell you anything about them? 
Another important aspect to the question of what to do with it is what you intended to measure. Is it average daily spending for the week? Then it's probably reasonable to average the individual day-answers, rather than dividing weekly spending by 7. Is it average weekly spending? Then this is an estimate in any case, so an option might be to average the sum and the weekly-response.
Thinking about your specific wording of the questions should help you decide what reason is the most plausible for different results and guide you in resolving the disparity.
