The Intersection of Everything: Why I Study Business, Politics, Computer Science, AND Math

Written by Nikesh | Oct 26, 2025 6:46:20 AM

"Why are you taking so many different subjects?"

I get this question a lot. Usually followed by: "Wouldn't it be better to focus on one thing?" My IB subjects—Business Management, Global Politics, Computer Science, Mathematics—seem scattered to people. Like I couldn't make up my mind about what I wanted to study, so I just picked everything. But here's what I've realized over the past two years: the most interesting problems don't live in just one subject. They live in the spaces between them.

The Question That Started This

Last year, during my ApniDukaan e-commerce project, I was trying to figure out pricing strategy. Simple question: how much should I charge for products? Business Management taught me about profit margins, competitive pricing, and value-based pricing. Useful frameworks.

But then I started thinking about the actual customers. Who were they? Why would they buy from an unknown store run by a teenager? What political and economic factors influenced their purchasing power? Global Politics kicked in. I started considering: What's the economic situation in India right now? How do global supply chains affect local prices? What role does consumer trust play in e-commerce in developing markets?

Then the technical side: How do I build dynamic pricing into my system? What algorithms make sense? How do I collect and analyze customer data ethically? Computer Science and Math entered the conversation. No single subject could answer my question. I needed all of them talking to each other.

That's when I understood: these subjects aren't separate. They're different lenses for looking at the same complex world.

How Computer Science Changed How I Think About Politics

Here's something weird: learning to code made me better at analyzing political systems. In Computer Science, you learn to think in systems and feedback loops. If this happens, then that happens. What are the inputs? What are the outputs? Where are the bottlenecks? When I started applying this thinking to Global Politics, everything became clearer.

Take my research on Hyderabad's lake pollution and urban development policies. I wasn't just analyzing "government bad, corporations bad, environment suffering." I was mapping it like a system:

  • Input: Urban development demand, political pressure for growth
  • Process: Policy creation (or lack thereof), enforcement gaps, stakeholder conflicts
  • Output: Environmental degradation, public health issues
  • Feedback loops: Where does pressure come from? Who benefits? What incentives exist?

Thinking like a programmer—breaking down complex problems into logical components—made political analysis less overwhelming. I could identify where the system was breaking. Not just point at problems, but understand the mechanisms creating them.

How Global Politics Made Me a Better Business Student

Business Management class teaches you about markets, competition, operations. All useful. But Global Politics taught me: nothing happens in a vacuum. When we studied trade policies and international relations, I started seeing how global dynamics shape business decisions. A company doesn't just "expand internationally." They're navigating trade agreements, cultural differences, regulatory environments, political risks.

During my CuriousRubik internship, we had a client who wanted to expand their business to Southeast Asian markets. My Business Management knowledge said: "Analyze market size, competition, entry strategies."

My Global Politics knowledge added: "What are the regulatory environments in these countries? How stable are their governments? What are the cultural attitudes toward foreign businesses? How do regional trade agreements affect operations?"

These questions made my analysis actually useful instead of generic textbook responses.Business strategy without understanding political and cultural context is just theory. Global Politics gave me the context that Business Management sometimes skips over.

Math: The Language Everything Else Speaks

I used to think Math was separate from my other subjects. It felt pure, abstract, disconnected from messy human problems. Then I started working on my machine learning research project—building a predictive retail price optimization system. Suddenly, Math wasn't abstract anymore. It was the foundation everything else was built on.

  • The algorithms I was coding? Mathematical functions.
  • The business problem I was trying to solve? Optimizing a mathematical equation under constraints.
  • The political-economic context of retail pricing? Expressed through data that needed mathematical analysis to make sense of.

Linear regression, decision trees —these aren't just Math concepts. They're tools for solving real business problems, analyzing political trends, building functional code. Math became the language that let my other subjects talk to each other. Without it, I could have business ideas and political understanding and technical knowledge, but I couldn't connect them rigorously.

The Conversations Between Subjects

Here's what happens when you study multiple disciplines simultaneously: they start having conversations with each other in your head.

  • During Business Management class: "This marketing strategy makes sense theoretically, but how would you actually implement it technically? What does the code look like? And would this work in markets with different political structures?"
  • During Global Politics research: "This policy sounds good, but what are the economic incentives for stakeholders? Can we mathematically model the outcomes? How would you build a system to track implementation?"
  • During Computer Science: "This algorithm is efficient, but what business problem does it solve? Could this technology be misused politically? What ethical frameworks apply here?"
  • During Math: "This is beautiful abstractly, but where does this apply in real systems? How do businesses use this? How do governments model policy outcomes with this?"

I'm not saying I have answers to all these questions. Most of the time, I don't. But I'm learning to ask them. And the asking itself makes my understanding deeper.

What This Looks Like in Practice

Let me give you a concrete example: my machine learning research project on retail price optimization.

  • The Business Question: How should retailers set prices to maximize profit while staying competitive?
  • The Computer Science Component: Building a system that uses regression models (Decision Tree, Linear Regression) and clustering (K-Means) to predict optimal pricing.
  • The Math Foundation: Understanding the algorithms, evaluation metrics (RMSE, R²), statistical significance, feature importance.
  • The Political-Economic Context: Why does this matter? How do pricing strategies affect consumers differently across economic classes? What are the ethical implications of dynamic pricing? How do market structures and regulations constrain pricing decisions?

If I only knew Business Management, I could talk about pricing strategy theoretically but couldn't build anything. If I only knew Computer Science, I could build the system but wouldn't understand the business problem or ethical implications. If I only knew Math, I'd understand the algorithms but miss why they matter in the real world.

I needed all of it. Not just knowing each subject separately, but understanding how they connect.

The Questions I'm Asking Now

This interdisciplinary thinking has changed what questions interest me:

  • Not: "What's the best algorithm for this problem?" But: "What business problem am I solving, and is technology actually the right solution? What are the broader implications?"
  • Not: "What's the optimal business strategy?" But: "How does political context shape what's actually possible? How would you technically implement this? What does the data say?"
  • Not: "What's the mathematical model?" But: "What real-world system am I trying to understand? How accurate does this need to be for the business decision? What am I missing?" These richer questions lead to more interesting answers. They also reveal how much I still don't understand.

Why This Matters for What I Want to Study

People ask what I want to study at university. Engineering? Business? Something else? Honestly? I want both. Not because I can't decide, but because I think they need each other.

Engineering gives you the tools to build solutions. Business ensures those solutions actually reach people and create value. Politics and Math provide the context and language to think rigorously about what you're building and why it matters. I want to learn in environments where it's normal to ask questions that span disciplines. Where you can talk about technical implementation and business strategy and ethical implications in the same conversation. Because the real problems I care about—making technology accessible, building sustainable businesses, creating systems that work for people—don't fit neatly into one academic department.

What I'm Still Figuring Out

I don't have this all worked out. Most days, I feel like I'm barely keeping up with each individual subject, let alone synthesizing them brilliantly. Sometimes I wonder if I'm spreading myself too thin. Should I just focus on becoming really good at one thing instead of being mediocre at several? But then I work on a project that needs multiple perspectives, and I'm grateful I at least have basic literacy across these different domains. Even if I'm not expert-level at any of them.

I'm also still learning how to actually integrate these subjects, not just study them in parallel. Knowing Computer Science AND Business Management doesn't automatically mean you can build a good tech business. The synthesis is its own skill that I'm still developing.

The Messiness Is the Point

Here's what I've realized: real problems are messy and interdisciplinary. They don't arrive with labels saying "this is a Computer Science problem" or "this is a Business problem." A challenge like climate change? That's science, politics, economics, engineering, social behavior, international relations, data analysis. All of it. Simultaneously. A question like how to make technology accessible in developing markets? That's understanding technical constraints, business models, cultural contexts, political structures, economic realities.

The world doesn't organize itself by academic department. Why should my learning? Maybe I am taking "too many" subjects. Maybe I'm not going as deep into each one as I could if I specialized. But I'm learning to think across boundaries. To see connections others might miss. To ask questions that combine technical feasibility with business viability with ethical considerations. That feels more valuable than being expert in one narrow domain while missing how everything connects.

What This Looks Like Moving Forward

I don't know exactly where this interdisciplinary approach will lead me. I'm 17, still figuring out so much. But I know I want to keep learning at the intersections. Keep asking questions that don't fit neatly into one subject. Keep building things that require multiple types of knowledge. Because the most interesting problems—the ones worth solving—live in the messy spaces between disciplines.

And if I'm going to work on problems that matter, I need to be comfortable in that messiness.

Do you study multiple different subjects? How do they connect for you? I'm curious how others think about the intersections between what they're learning.