Multiple data points per subject? Aggregation to mean with or without considering subjects

I am currently arguing with someone on how to correctly treat data with multiple observations per subject. More specifically data was gathered from 100 participants 8 times per day for 5 days (resulting in 40 observations per participants for each variable of interest).

So now we came up with two way of analyzing the data:
1)aggregate data per variable and analyze it further with PROCESS macro by Hayes (however here is my problem - wouldn't data from the same subject not be completely independent?)

2)aggregate data to a mean for each variable PER subject and then analyze it further.

I am firmly for the second option, however I am not 100% if it is a valuable one. Every opinion will be appreciated


Less is more. Stay pure. Stay poor.
Please describe the purpose of the project and primary out come. Without knowing more info it is hard to give recommendations. Also what is sample size and how are variable formatted?
Ops, sorry about that, so I am conducting an experience method sampling study to observe the relationship between recovery and performance, mediated by job crafting (the mediation is also moderated by transformational leadership). Sample size is about 105 employees who will fill in the questionnaire up to 8 times a day for 5 days. Hope that is enough :)
I'm not a specialist in statistics. Just trying from my knowledge. I think if for an individual, the 40 observations suppose to be different, and show some trend, averaging them might not using the information sufficiently. Actually for each individual there is a relation between recovery and performance, luckily it fits a simple linear regression, then the slope and intercept would be representative. Based on them you can find the difference between individuals. By the way, is this the dataset that called "repeated measures"?