THIS IS A POST I WAS WORKING ON ALL DAY LONG WHILE I WAS DOING OTHER THINGS.
Over at Frugal Makes Sense Two there was a discussion of weekly menu planning. As you may remember, we are fans of menu planning— making a weekly menu, basing the grocery list on the menu, doing the big shopping once a week. (See for example this Books Bygone essay.) This got me thinking about all of the virtues of meal planning, one of which, many contend, is saving money.
I’ve been saving the receipts from our weekly shopping for over two years. I have a nice little spread sheet set up which allows me to analyze our spending.
Caveats: 1) We do our main shopping at the Piglet (small Piggly Wiggly in town). If it happens to be out of something, we’ll stop in at the Super-lu. Receipts for these side trips, which are usually under $10, are not included. 2) Often, we have a “later in the week” list. These are items that we don’t want sitting around, or items I have to pick up in Starkvegas. Typically under $20, these are not included. 3) We don’t buy paper products, laundry detergent, etc. at the Piglet. So our grocery expenditures do not include these sorts of items. 4) Food dollars Daughter C, Miss M, and A.Leland spend for themselves are also not included. Finally, 5) We eat well. Last evening’s venison stroganof with rice pilaf was great!
I can explain the big up tick in October 2012. December 2014 is an outlier– holiday travels and whatnot.
Looking at October 2013 through November 2014, it’s remarkably consistent, don’t you think?
Average = $119
Range = $105-131
Standard deviation = $5
That’s amazing. Since October 2013 (and not including December 2014), our average weekly spending, month by month, differed by only $5 two-thirds of the time.
As we all know, though, looking at averages is a good way to get the overall picture and can be very useful in planning, but averages wipe out variation.
October 2, 2012 – February 2, 2014
Average = $116
Range = $54-192
Standard deviation = $21
Those lines are distracting, but telling.
Here’s another way of looking at the data.