Last week, in my blog post Thinking MBA for Career Growth? Hang on..., I touched some nerves among All Analytics community members over the question of whether or not analytics professionals seeking career advancement would be better served by an MBA or a Master's in statistics or another advanced degree.
The opinions were varied and equally passionate on both sides of the argument.
One community member wrote, for example, that an MBA has been a disappointment:
I'm a generalist and my MBA has not done much for me. I'm beginning to think that I would have done better if I had specialized. I have noticed that the generalists are passed over for more specialized skills in different areas. And even I am finding it hard to decide the best jobs for me.
Another community member, on the other hand, pointed out that pursuit of an advanced degree wasn't necessarily warranted (or maybe even advisable): "You don't need to get a degree to learn advanced statistics or business management. Indeed, university professors will teach you outdated material."
I was thinking about this thread as I reviewed notes from a recent conversation I'd had with Radhika Kulkarni, vice president of advanced analytics R&D at SAS (this site's sponsor) and our latest Women in Analytics featured professional. (Read our Q&A with her.) Kulkarni shared some great advice for professional development that's applicable to this discussion.
Radhika Kulkarni, SAS
In a nutshell, her message is that how you learn is more important than what you learn. "Be open to input -- it can come from any source," she said, continuing:
What you do as an academic, as you start learning in the particular field that you specialize or do your PhD in, at the end of the day you may end up using that throughout your career... or you may not. The most important lesson learned as you pursue an advanced degree is the ability to craft new things, to learn new things, and to apply them... That's a lesson that will stand you in good stead anywhere.
Focusing too narrowly is ill-advised, Kulkarni added. "You might specialize in a particular area, and go deep. But always listen and look at all the surrounding disciplines and learn about them."
Perhaps you're working on hard-core mathematical programming and learning deterministic optimization and mixed-integer programming as your thesis topic. "Know that there are other aspects of operations research, other analytical areas, all of which are going to be needed to solve any business problem," she said.
You might apply one algorithm very well, but that won't guarantee project success, Kulkarni said:
You need to be able to handle data, you need to be able to create the model that's going into your optimization problem, and you need to be able to implement it in the environment that the business needs it to be implemented in. All of these aspects need to be considered, and you need to have an understanding of the big picture.
Don't panic. Kulkarni isn't suggesting you need to be an expert in each of these areas. What she does say, though, is that you need to be able to work with the experts and bring all the pieces together. "So at the end of the day, a successful project is not done by a single hero. It's done by a team of people working together."
That, Kulkarni said, is a lesson that everybody must learn:
You need to understand that a multidisciplinary approach is important for success. You should be able to work with others and explain your technique to others in ways that they can understand. And you should be able to recognize the value of what others bring to the table and determine how all the pieces can fit together.
Always remember, she added, "The whole is bigger than the sum of its parts!"
Does Kulkarni's advice resonate with your experience? Tell us why or why not below.
@Louis, my favorite managerial tactic is the "side swipe." It occurs when they (and you) know you're making a good argument, offering a good solution, etc., so they don't attack your idea directly; they find something wrong in a minor point of your presentation and attack that, derailing the discussion and often whole meetings.
@Noreen, most health systems people I talk with are licking their chops at the exchanges and health reform in general. There will be millions more people accessing health care now than previously were. It is a big win for providers (hopefully nurses included).
Being a good team player is so important, but so often team leaders forget how important it is to capitalize on the skills of the team members. Anne Robinson brought this up in her Women in Analytics profile piece, too. As she said, you want to have people on your team that are smarter than you. That raises everybody's effectiveness!
Great economies love generalists and bad economies prefer specialists.
@Seth Interesting way to view economies. I agree this is a basis of contrast, but I am not so sure bad economies are reflected by a dependence on specialist. I think it depends on what the speciality is - many countries have been sucessfull by just focusing on two or three profitable specialities and seeking to become know as the best to provide them.
It does stand to reason "generalists" are better suited to help the whole than would a specialist if we are talking about an hyrid society, which I believe you are ?
"I'm a generalist and my MBA has not done much for me."
Interesting I thought about an MBA, when I was fresh out of school, but the benefits and the economy quickly faded. Would it be more beneficial than an Masters in Statistics ? Well depends on your ultimate goal of course, but if it is Analytics then the latter choice is probably more beneficial.
I understand and agree with Ms. Kulkarni's position as well, you will need a broad understanding of many subjects and motivations to be effective in the end. And you probably can't do it alone either ; )
Below is a very interesting video where it is explained on why healthcare is so high U.S. And it really is a combination of things. For example, here Dr.'s have to take loans for schools, hence they charge more because they need to pay them on top of malpractice insurance. Additionally, since we have so many providers vs. one universal provider, our negotiation strenth on cost and quality of service is less than other nations. We actually wind up subsidizing other nations because we pay so much for new drugs and technology that is for less than other countries. (I wonder if that is the same for cellphone service?) If the video doesn't show you can see it here.
When people don't have health insurance, such as in a down economy, they can't afford to get treatment in either a clinic or hospital. Thus, hospital revenue goes down. The hospital I worked out, cut out all the middle nurses -- the licensed vocational nurses. RN's must handle more responsibility and CNA must handle all of the grunt work.
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