2:45 PM, January 22
Apartment, Montreal, QC
Dear Fellow Arts Students,
I am enjoying a leisurely afternoon away from the office, away from classes (in my humble–or not so humble–opinion, waking up at 8:30 is worth it if your classes end by 1:00…thoughts?).
Business is good. I have been tackling Revenu Quebec documents one at a time (not very fun if you do not know French), planning some changes to our accounting software, and awaiting the release of our Financial Statements. Our auditor has promised a preliminary draft “by the end of this morning”. I am hoping to have some sort of pseudo-corporate ‘Financial Statement Unveiling Reception’.
Moving to the feature of this post…
I have been analyzing (if you can call it that) samosa sale data for the Leacock Lobby. What started as an idle curiosity turned into an attempt to find an accurate method for projecting sale revenue and then into an attempt to contribute to the study of Economics and finally into a near-forgotten project, just one step above an incomplete DIY woodshop project buried in your garage.
Due to an insufficient sample size and an inability to control for extraneous variables, I will not be able to produce statistically significant results. Nonetheless, I would like to present some of my preliminary analysis, perhaps a preview of a potential submission to an undergraduate journal (we’ll see).
What I would like to deem The Fundamental Theory of the Samosa Sale, or perhaps the Sellout Conjecture is the claim that all Leacock Lobby samosa sales sell out (barring any significant obstruction to this).
It will be most fruitful to introduce a few variables, and then we can formalize our claims. Let R stand for the revenue collected from a samosa sale. Let S(t) stand for the total amount of samosas sold during a given sale. Let S(1) be the number of samosas sold at $1 for 1 samosa. Let S(3) stand for the number of samosas sold at the rate $2 for 3.
The Sellout Conjecture then means that S(t) is a known value prior to the sale. Now, the goal of a seller is to maximize revenue. Since the S(t) is known (and is now a parameter instead of a variable), revenue becomes a function of S(1) and S(3). More explicitly:
R = (2/3) * S(t) + (1/3) * S(1). Call this the Samosa Revenue Formula.
Clearly, it is advantageous to sell as many samosas as possible at $1 per samosa. We can then focus on the ratio between S(1) and S(3). At times it is convenient to employ the following two variables: P(1) = number of purchases at $1 / samosa. P(3) = number of purchases at $2 / 3 samosas. Note that P(1) = S(1) and P(3) = S(3)/3.
Given a parameter S(t), S(1) and S(3) are uniquely determined by R. After deriving a few tautological equivalences from the Samosa Revenue Formula, we can determine values of S(1), S(3), P(1), P(3). We can even determine the total number of purchases made at a samosa sale [P(1) + P(3)].
If the Sellout Conjecture holds, then we can gather a lot of data from just one parameter and one variable–quite fascinating, and informative for various purposes. Verifying this conjecture would be a tedious, and very difficult task. What I know is that all (or most) samosa sales end with no samosas left, but I do not know whether or not our samosa vendor is honest.
However, if everything I have said above is a close approximation of reality, then the following, rather startling, hypothesis comes to mind. Call it the Inverse Quality or the Customer Dissatisfaction hypothesis (there is room for a more creative name):
Revenue is inversely proportional to the quality of the samosas being sold and the service at the samosa sale. This follows from the assumption that the sale will inevitably sell out, and that revenue is thus maximized by a large amount of people opting to by only one samosa instead of three.
Wishing you the best,