Playing on a Seesaw vs. MBA experience

Have you ever played on a seesaw? I’m sure many of you have. As it turns out, it is not only a fun physical exercise, but it teaches us about important concepts in physics, statistics, and negotiations. And with any luck, I will try to illustrate that it also might teach us a lesson or two about MBA grades.
In one of my posts I mentioned that marks are probably one of the hardest ways to differentiate yourself in an MBA program. I’ve received number of emails from readers curious to find out why that might be the case.

Throughout our lives we are instilled with a notion that being great means being better than your peers. In high school we were happy when we got the top grade in class even though it might have been only 72%; it was all the same, as long as we were at the top of the hill. That is precisely why the question of whether one would chose a $10,000 bonus if it was the highest bonus in the company or a $25,000 if it was a lowest one becomes hard to answer. It is as true in an MBA as it is in any other environment, and probably even more so in the MBA as everybody here is a type-A personality and everybody is aiming for a win.

Let me make myself clear here, what I’m not trying to do is to prove that marks are not important, as they definitely are. Especially if you are targeting Top Five consulting and finance firms, they are going to be scrutinizing your MBA grades in addition to other quantitative pieces of information such as your Undergraduate marks and GMAT score.

What I am trying to convey here is that while concentrating on maintaining good marks there has to be a definite focus on trying to differentiate yourself though other means, such as extracurricular activities, your professional network, depth of knowledge about the industry, and the list goes on.

By now you are probably wondering why I threw in the seesaw analogy at the beginning of this post. The reason being is the intimate curve. It is near and dear to a lot of us here in the MBA program, even though it does feel a bit tight at times. Curve is a tool which statisticians refer to as a normal distribution, in reality you can think of it as a semi-flexible seesaw; the central point being the mean value. If the two people at sitting right at the opposite ends of seesaw they are two standard deviations away from the mean (central value). Interesting property of this type of distribution is that 68% of values fall within one standard deviation away from the mean and 95% fall within two standard deviations away from the mean. Furthermore, a lot of distributions of values in the world fit well under this type of description, and the ones that do not fit are sometimes force fitted.

And now the big secret that schools and majority of employers know about: mean value of MBA grades is 78% with standard deviation of approximately 2%. If we assume an average class size of 100 students that translates into 68 students being somewhere in the 76 to 80% range as far as their final marks, another 27 students being somewhere in the 74 to 82% range, one or two students around 72% and finally two or three in the 85-90% range. Combined with the fact that dean’s list is top 25% of the class, grades might mean that the difference between student on a dean’s list and the one who is not on it might be in the order of a tenth of a percent.

One thing that I didn’t mention when I introduced the concept of a curve is the fact that it has to balance on both sides of the mean. The seesaw analogy comes in handy here again, as similar to the game, if somebody is on one side there has to be somebody on the other side, at approximately the same distance from the center for seesaw to balance. You can think of a curve as playing on a seesaw with multiple people on each side.

And finally one curious fact about the curve, let’s take a hypothetical situation: say Bob decides that his future depends on getting 88% in an ABC course, he works nights and days, doesn’t sleep or eat to get that grade. At the same time John works hard as well but tries to maintain some sort of a balanced lifestyle. The curious thing that John starts to discover soon enough is that even though he is putting solid effort into the course, his mark for ABC is starting to slide because there has to be somebody offsetting Bob’s outstanding results on the “other” side of the mean. At this point John gets scared as he also wants a great job which depends on him being on the dean’s list, so John decides to up his efforts and cut back on sleep for the next couple of weeks. To Jane’s surprise, her marks in ABC are suddenly sliding quite fast to “balance” both Bob’s and John’s increased contribution. But now comes the B-School reality, at the end of the day any school is faced with a choice: would they rather have Jane really upset despite the fact that she paid $xx,000 for the program and put solid amount of work into the course while John and Bob would be quite happy with their marks, or would the school rather have everybody not unhappy to various degrees. Hence a tight curve with a fixed mean and resulting need to differentiate yourself through means other than marks.

Please don’t hesitate to contact me if you have any questions or comments about this or any other posts on this blog.

Till next time,
George