What I never expected to learn while getting my MBA | MBA Learnings

First-year student Rohan Rajiv is blogging once a week about important lessons he is learning at Kellogg. Read more of his posts here.

Many of us are in graduate school to learn. There are many interesting things we expect to learn, like how to develop understanding of strategy and marketing, for example, or how learn to work better with teams of diverse people.

I believe the most important thing we are being asked to learn is something we might not have expected: Decision making and trade-offs.

Kellogg students get inspiration from Seth Godin

I had been looking forward to a Skype interview with Seth Godin at school for many months. It took me a few months before I was sure the technology would work. I promised him a good experience and I definitely felt a bit of the pressure of the promise in the days leading up to it. It all worked well (thank you to KIS – our tech team!) and the interview was a real treat.

I got admitted to B-School! Now what? | MBA Learnings

How can a relocation and a significant life move not be stressful, and instead be a growth opportunity?

This was the question I asked myself when I got my offer of admission for graduate school. I hate relocation. It was going to be a pain. But I needed to figure out a way to make it better. Framing it this way appealed to me because there were likely a few more relocations coming up. This was how I broke it down.

Designing for introversion | MBA Learnings

A lot of modern day office work or work that requires “connection” requires a certain degree of extraversion (the research world, on the other hand, is predominantly introverted). After all, you are working with people. Over time, however, it has led to a huge bias for extraverts and, I think, the early rise of extraverts into senior positions has also led to systems that work best for extraverts.

Amazon’s Udaan problem | MBA Learnings

We recently looked at why Amazon’s first physical bookstore in Seattle made sense.

The central theme was that different products are suited to different kinds of retail channels. As you might imagine, shipping individual cartons of milk or toilet paper isn’t cost effective as the delivery costs likely outstrip the cost of the good.

Additionally, it is easy for stores to carry excess milk or toilet paper as these goods are cheap. However, when the good becomes niche and expensive (e.g. diamonds), delivery becomes cheaper, and it then makes a ton of sense to centralize warehouses as carrying inventory in store is a very expensive proposition.

So, as retailers get larger, it becomes essential to adopt a “hybrid” or “omni-channel” approach to supplying goods to customers. It is the only way to stay competitive.

When we then consider an emerging market like India, retailers like Amazon are faced with additional problems.

Why Amazon’s first physical bookstore was smart, and inevitable | MBA Learnings

Amazon opened its first bookstore in Seattle earlier this week. This led to a many interesting questions in the media: Has Amazon taken a step backward by jumping back into traditional retail? Didn’t Amazon start an online store to improve on the traditional bookstore model?

To understand this, let’s begin by taking a walk down memory lane and look at Jeff Bezos’ initial rationale for starting an online bookstore.

Notes from my Big Data and Analytics course | MBA Learnings

This past summer, technology analyst Benedict Evans shared an interesting image from a classic 1960 film “The Apartment.” The scene is set in the office of a large insurance company in New York – drones laid out at desks almost as far at the eye can see. Each desk has a telephone, rolodex, typewriter and a large electro-mechanical calculating machine.

It is clear that the capabilities of analysis tools in 1960 were far below our ability to analyze them today. So Microsoft Excel and other spreadsheet programs offered huge benefits simply because they helped bridge the gap between the average manager’s ability to analyze data and the tools available to do so. This, in turn, spurred businesses to collect more data in the hope of extracting insights. So, over the late 1990s and the 2000s, every junior consultant and investment banker became an Excel ninja. Being able to use the tool to the best extent possible added real value.

All was well. Until “big data” entered the picture.