Tesla's monthly delivery data is definitely volatile. If you look at the Barclay's graph of NA deliveries over the past year for instance, the difference between the 1st month and the last month of a quarter can approach 2:1.
Imagine if Tesla had released monthly information while the plant was shut down for 3 weeks. The overreaction to both the lows and the highs would be far higher than it is today.
Other car manufacturers have significant amounts of inventory sitting on lots to buffer production variances. Tesla does not. For example, Cadillac churned out a couple thousand ELR's pretty quickly and then that plant switched back to making other cars. That inventory now sits on dealer lots and it might take a year or more to sell through that inventory. Other car manufacturers are able to produce a car model in volumes exceeding demand and then switch to another car model. They have other plants to produce vehicles when one plant is idled for upgrades, maintenance, or whatever. They have inventory sitting at dealer lots. All of that buffers the variance and therefore the monthly sales figures are usually not in a demand constrained environment and reflect actual demand. Tesla's build to order model of a single car combined with production constraints means that the delivery variance reflects a single plant's production and delivery delays that would need smoothing in order to make sense of it.
The biggest problem is that people are still equating deliveries to demand which is not true for Tesla, at least not yet. The only reason to have more granular data is to have more insight into Tesla's business, specifically customer demand. However, none of the delivery information will give you a true view of customer demand since Tesla is clearly still production constrained.