I confess that I don’t mind Christmas items in stores before Thanksgiving. While I agree that it’s too early, I understand why it’s sometimes a good business decision. Christmas items are similar to other “perishable” items like newspapers, produce, blood, and fashion, that go bad after Christmas in this case. These supply chains are managed differently than the supply chains for non-perishable items. Anna Nagurney has some excellent posts on perishable supply chains, blood banks, and blood supply chains.
I discovered an article about this by Kori Rumore in the Chicago Tribune that goes into detail about Christmas supply chains. Below I list a few supply chain observations I thought about or learned when reading the article. I use “Christmas” here generically because “holiday” is ambiguous, although other winter holiday items are often included with Christmas items (Christmas items make up the bulk).
- Christmas and holiday items are seasonal items in stores. Many box stores have a fairly large section dedicated to only seasonal items, where they put out many items for the next season. A typical seasonal section may rotate through the following merchandise: Valentine’s Day, Easter/spring, summer/beach, back to school, Halloween, and Christmas items. After Halloween, the next “season” associated with a lot of merchandise is Christmas. It’s better to stock the seasonal section with Christmas items than let it remain empty.
- Some stores like craft stores also have to deal with the crafting supply chain: you have to make holiday decorations well in advance of the holiday, so the holiday craft supplies need to be available for purchase crazy early. Christmas craft supplies often come out in the summer. I’m a regular at the craft store, but this never fails to surprise me.
- Seasonal items can sell out, so many consumers like to shop early while there a selection of items, and retailers have an incentive to cater to early shoppers (even if this irks most shoppers).
- The holiday items you see in the summer may be a tiny fraction of what you will eventually see after Thanksgiving, when the bulk of Christmas items grace store shelves. Some retailers only put out a few select items, such as collector’s items. The US Postal service and Hallmark sell to stamp and ornament collectors, respectively, and they put out Christmas items early for the collectors, not non-collectors like me. It had never occurred to me that I might not be the target audience for those early Christmas items.
The Chicago Tribune notes that 40% of consumers like to start holiday shopping before Halloween. I am one of them, but I usually shop for gifts, not holiday items. I’m a bargain hunter and usually buy holiday items like cards and wrapping paper when they are deeply discounted (the day after Christmas).
On a final note, supply chains are not why stores sometimes play Christmas and holiday music before Thanksgiving. There is no excuse for that🙂
Where have you seen many Christmas items for sale?
Clinton is starting to pull away from Trump in the various election forecasting models, but it’s clear from the forecasting models that Trump still has a chance:
In 2012, FiveThirtyEight forecast had Obama’s win probability at only 61.1% on October 11, 2012 with less than a month before the election (November 6, 2012). I showed the time series of the 2012 forecasts below, to show how the forecast firmed up and turned toward Obama before the election. Obama won in a landslide with 332 votes. The last FiveThirtyEight forecast right before the election had the actual election results as the most frequent outcome in the simulation (Nate Silver nailed it). Most of the other forecasting models picked at least 49 states correctly within a week of the election, but they were not nearly so accurate a month before the election. I’m showing FiveThirtyEight’s 2012 forecasts here to illustrate that it’s hard to forecast a landslide victory.
FiveThirtyEight’s 2012 Presidential Election Forecast
There is no guarantee we will see a similar pattern in 2016, but polls lag public opinion, and the polls taken since the debate last week show a huge bounce for Clinton. There is some information on Vox below about what the polls mean and where the bounce is the biggest for the 2016 election.
Election Analaytics @ Illinois has Clinton with the win at 99% if the election were held today, which is up from 77% last week. A lot has changed in a week. They are showing Clinton as a heavy favorite, even if the election were to lean heavily toward Trump.
I’ll try to blog some more about the election in the next month. I’m pretty interested in methodology used in the forecasting models. If you have any requests, let me know.
Eric Dubois, one of my PhD students, interned at the RAND Corporation this summer. He gave a presentation about his internship to my lab.
I learned that dynamic programming is still of great importance at RAND. Richard Bellman introduced dynamic programming in 1953 while working at RAND. He spent most of his career at RAND, and his many contributions to dynamic programming are still cherished. You can download his 1954 RAND Report “The Theory of Dynamic Programming.” Every summer, RAND employees celebrate dynamic programming’s anniversary with cake.
I would love to celebrate dynamic programming with cake and with the cake eating problem (optimal depletion of an uncertain stock).
Note: the cake eating problem can be solved with dynamic programming.
The RAND Corporation began to provide analysis for the Air Force after World War II. Soon thereafter RAND branched into nuclear deterrence. A (fake) RAND analysis on nuclear deterrence is mentioned in Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb.
The Dr. Strangelove character is based on RAND scientist Herman Kahn.
What I’ve been reading
What I’ve been listening to
It’s almost the end of the summer, which marks the end of writing season in academia. Here is some advice for writing a scientific paper, as told through a series of tweets. What would you add?
Legendary engineer George Heilmeier came up with a set of questions to help program managers evaluate proposals while he was director of DARPA (1975-1977):
- What are you trying to do? Articulate your objectives using absolutely no jargon.
- How is it done today, and what are the limits of current practice?
- What’s new in your approach and why do you think it will be successful?
- Who cares? If you’re successful, what difference will it make?
- What are the risks ?
- How much will it cost?
- How long will it take?
- What are the midterm and final “exams” to check for success?
This list is still used today. I most often see this list in presentations by National Science Foundation program officers who are interested in helping researchers write competitive proposals.
I love this list.
This list has stood the test of time because it’s a great list. I find questions #2 and #4 to be particularly helpful. I do so because my first inclination is to talk about why my research is interesting and exciting to me. I wouldn’t start research in a new area unless the topic were interesting and unless my skill set were brought something to the table. Being excited about my interesting research is not sufficient for giving a good answer to #2 and #4. Not all research that is “interesting” is also “important.”
When I write with my students, we talk about how we need to answer #1-#4 in the paper, although we answer slightly different versions of the questions since the research has already been successful if we are publishing the results.
I once summarized how to answer an abridged version of the Heilmeier questions in the first couple minutes of a thesis defense. When a student did so, it made for a memorable defense (in a good way!) and I tweeted about it.