Peter Flom knows a lot more than me, but I'd venture to say that the answer is "no" unless you have enough additional information about the respondents (and non-respondents) to push it into the "yes" column.

Some questions:

1. Can you be more specific about your responses? Are we talking things like sales reports from individual employees? Or letters of praise/complaint sent to a site by customers? Or something else? Who is eligible to submit a "response", that is: what is your actual population?

Depending on how you answer this, some of my other questions may or may not make sense...

2. In the month that you got 29 responses from one site, what percentage does that represent from the total that could have been submitted at that site? That is, are there 290 people asked for responses and only 29 responded? (And then only 5 responses from that site another year?)

3. You mention "regional office", and "from one site". What's your response rate in each region look like in terms of total sites in the region, and similarly at the regional level?

4. I'm assuming these responses are self-selected, that individuals decide whether they want to respond or not?

5. Do you have demographic information on all possible respondents, at the individual, site, and region levels? (That is, could you describe those who did respond and those who did not respond, noting substantive differences.)

I've totally edited this answer based on your comments, below.

So what you have is technically called unbalanced panel data. You have a fixed set of sites that report daily productivity on a daily basis, where each site's data has missing days that are not reported. The number of missing days varies between sites, and within a site over time. Productivity is defined as the percentage of orders received and fulfilled that day.

Your suspicion is that sites will be more likely to report on days that are especially productive because they want to bump this fact up the chain. You want to calculate productivity on a monthly basis per region (collection of sites), comparing the same month across years, but you're worried that the mixture of sites that report a significant number of days in a particular month may change over time and thus not be representative of the region.

This went in a different direction that I originally thought, so I'm mainly clarifying so that someone like @Peter Flom might give better advice.

Two last questions from me: How many years of data do you have? Has the number of sites that exist, or the way they're grouped into regions changed over the time you've gathered data or has it been pretty static (except for the actual reporting, of course)?