I had the first class meeting of my introduction to business analytics course yesterday. Over the weekend, I had decided that I would start class by using tic-tac-toe to explain analytics to my students. I had never done this before so I was rather nervous and anxious going in.
When the clock ticked over to the start of class, I greeted my students with a “Good afternoon” and started drawing the 3-by-3 tic-tac-toe grid. While I was doing this, I asked the class if they knew what I was doing and somebody said I was drawing the tic-tac-toe outline. I was glad somebody in the class knew the game because if nobody did, it would have been, as the kids would say, a “fail” for me. (BTW, do the kids say that anymore?). Read More…
There were several interesting posts floating around the OR-blogosphere recently on the importance of how to communicate the results of an OR or analytics work. First up, Nathan Brixius with his interestingly titled post “Yes, Virginia, there is a difference between optimization and prescriptive analytics“:
Prescriptive analytics concerns an entire process, and this process typically involves assembling data, building models, evaluating them, and presenting the results. Optimization comes into the play for the middle two steps, but the first and last are every bit as important. In fact, many times the first and last steps – assembling the data and presenting results in a form that people understand – are the most difficult and time consuming ones.
It should not be much of a surprise that large corporations have been the early adopters of analytics as these organizations are always on the lookout for ways to make themselves better (i.e., more efficient, more profitable, etc.). As such, many analytics stories have focused on these large organizations and their successes.
It was refreshing then to read a piece on analytics and SMBs (“Why Small and Medium Businesses (SMBs) Are a Big Opportunity for Business Analytics“). In the article, the author writes that SMBs can benefit just as much as their larger siblings by using analytics.
It is well known that in a successful data-driven corporation, everything starts at the management level. The management has to embrace analytics and then trickle it down throughout the entire organization. SMBs are no exception in this regard. The big advantage of SMBs is the fact that their organizational structure is more shallow and narrower in size. For this reason they are usually quicker to buy into analytics.
It is easier (in theory) for SMBs to adopt analytics because their size allows them to be nimble and to quickly adjust however necessary to something new. There is one important factor though that cannot be overlooked: the cost associated with acquiring the analytical tools available on the market. Read More…
A while back, the New York Times published an article about how companies are attempting to learn more about their customers through predictive analytics.
For many people who read the article, the main-take away was that Target is creepy. If you have not read the article or heard about this from other sources (e.g., Stephen Colbert’s “The Word” segment on his show “The Colbert Report”), here’s a summary:
After applying predictive analysis models on a database containing their customers’ information, Target was able to determine that a teenager was pregnant. The company then sent pregnancy-related coupons to the teenager’s home in an effort to get her to shop at Target. Unfortunately, the teenager’s father was not aware that his daughter was pregnant, and taking umbrage at the promotional mailing, he caused a commotion at a local Target store. The father eventually found out that his daughter was indeed pregnant, and was apologetic when he was later contacted by Target.
Target’s use of predictive analytics to better target (sorry, I couldn’t resist) certain sections of their market feels like an unwanted invasion of privacy and is just plain creepy. So, is Target really creepy? And by extension, is predictive analytics creepy? Read More…
In a previous post, I wrote about how holders of season tickets of various basketball teams could benefit by selling their tickets on the resale market when their teams host a “must see” visiting team. It comes as no surprise that sports franchises themselves are looking into using some form of revenue management to increase revenues from ticket sales.
This is certainly not a new development as I have seen articles about this in the past. Major League Baseball’s San Francisco Giants has been in the forefront in utilizing dynamic pricing to price their tickets (e.g., here, here, here, and here). What is interesting, however, is the number of sports franchises that have adopted this practice. Only four MLB teams have used dynamic pricing prior to the 2012 season. Here’s one possible explanation from the Planet Money article: Read More…