Why an MBA is necessary for a data analyst/scientist

Note — The article, for simplicity, considers data scientist and data analyst to be similar; roles that make sense of data and deliver actionable insights. It is written to help data scientists grow significantly in their careers.

Had I written this article a few years ago, I’m sure I wouldn’t get many readers. Data scientist was not a profession that was heard of. But thanks to the tons and tons of promising and overwhelming articles on AI, ML and other disruptive technologies, data sciences has become a profession that is not just well recognized but extremely sought after. To quote HBR, “The sexiest job of 21st Century”.

So, if you are a data scientist yourself and caught in one of those Sophie’s Choice moments of ‘MBA or not’, I strongly urge you to keep reading.

An engineer by background, I spent 6 years in the field of data sciences working for a pure-play data analytics company. I helped leading Retail, Pharmaceutical, and FMCG companies’ directors and senior executives make data-driven decisions. The environment in my company was highly competitive. Most of my peers, who wanted to stick to analytics, went on to do Masters in Data Sciences in renowned universities across the world. I, however, chose to pursue an MBA. It was a difficult decision since there were only a handful of people who had followed this route. However, half-way into the course at one of the elite universities in Europe, I believe my decision was right and I wanted to pen down my thoughts to help fellow colleagues make a more informed decision.

There are 3 crucial skills an MBA helps a data scientist develop.

The ability to connect dots

This by far has been my biggest learning. Being a GREAT data scientist is not just about writing smart algorithms or designing good models, but possessing the business acumen to understand how decisions across horizontals can affect one another. For example, while analyzing the drop in sales of a product X, one of the most common hypotheses is that an increase in Marketing spend might attract more customers and thereby bring back the demand. Now while a regression on the past data may back this hypothesis, it is important to take a step back and inspect changes made in other departments. For starters, a change in Brand Positioning of X could be resulting in loss of customers OR a decrease in Sales Force could be resulting in lower reach OR a switch in suppliers could have led to low quality of products on shelves.

By being exposed to the roles of Marketing, Sales, Finance, and Operations departments, and solving case studies of multi-national brands that explain the interconnectedness, helps in arriving at more pertinent solutions.

Becoming more creative

One of the attributes that distinguish a data scientist from the herd is Creativity in problem-solving. And it is important to note that creativity comes with collaboration. A B-school offers multitudes of experiences to perform in distinct groups/teams. One of them is working in a diverse group for regular coursework. Your work-group could be a 5 member team that consists of an Architect, a Teacher, a Marketing expert, and an Entrepreneur, the sort of backgrounds that you usually don’t work with on a regular basis. Further, you don’t just spend a day or week with such a team but almost 12–24 months, cracking cases, making presentations, developing products and even bonding over beers. The exposure to the opulence of ideas helps you expand your horizon and makes you think of approaching problems in newer ways. This attribute, in particular, is what most clients look for from data science teams since if the approach was only logical they would do it themselves.

Developing a character

One of my dear friend who works as a data scientist in a leading company once told me that she and the fellow scientists weren’t allowed to present their results to clients. Their job was to simply churn out useful numbers and let the Project Manager present the findings. I hope you’re someone who’s looking for far more from a data scientist role than just that. To take charge and face clients means you need to be able to negotiate methodologies, articulate insights, influence stakeholders and present in a confident manner. These innate skills are not just taught in dedicated ‘Behaviour’ sessions in the MBA, but, you’re also thrown, literally, into challenging scenarios where you’re forced to practice them.

Consider the diverse work-group mentioned in the previous point. Suppose the Innovation Professor hands your group a case study on a large conglomerate contemplating to increase spend on Big-Data systems, and you decide to be the lead as the group feels it right. Now your task will be to not just quantify the benefits from the case but to also convince your team to follow your lead by explaining your final decision. And getting that consensus will not be easy. You’d also have to present the case in class and tackle questions head-on that the professor and your super smart peers throw at you. And while this is just one example, consider a week full of such group meetings, assessment center visits, company interviews, presentations, competitions, club gatherings, and not to forget, the ever so occasional ‘Capitalism vs Socialism and Ronaldo vs Messi’ debates over late-night beers. You’ll be constantly challenged, constantly rejected, constantly outwitted but exponentially learning. This builds character more than anything else (Nassim Taleb’s ‘Anti-Fragile’ explains how stressors help you grow). What’s more, if you study at a foreign university these experiences will fourfold as you’ll strive to learn cultures, languages, and behaviors of your friends and colleagues, thus becoming more adaptable to a global company atmosphere.

So, to summarize, while coding, math, and technologies are competencies you can keep learning online, the skills mentioned above are only learned through simulation, through experience, and through dedicated time investment. The MBA provides you with all the artillery you need to play a bigger and more impactful role in the organization.