When I arrived at MIT to attend the Supply Chain Management Master’s Program, I wanted to learn how supply chains are built from the ground up, and better understand the logic beneath the decisions I had been executing. At Apple, I tracked inventory for product launches. I knew the rhythms of a well-tuned supply chain: safety stock, sell-through rates, new-product launch timelines. I was good at it. But being good at executing within a system is different from understanding how that system should be designed in the first place. I didn’t expect that the sharpest lessons I learned would come from domains where operational discipline and frontier technology have no choice but to figure each other out.

Every Node Has Its Own Agenda

The first of these lessons came not from my supply chain coursework, but from teaching AI agents how to fail gracefully at the AI Venture Studio at the MIT Media Lab. I’ve been building multi-agent systems with specialized AI models that coordinate to accomplish tasks no single model handles well. The design problem isn’t purely technical. Each agent operates with partial information and its own failure modes; if one agent fails, it can cause others to fail in sequence, so resilience must be built into the architecture before the first line of code is written.

I recognized the same structure from my supply chain work. A global supplier network is a multi-agent system in everything but name: each node operates with its own objectives, constraints, and blind spots, and alignment between those nodes isn’t a default state you configure once but something that must be architected from the start. The difference is that in supply chain, a misaligned node delays a shipment — a visible, traceable failure. In a multi-agent system, it can corrupt the entire output silently, with no early warning signal of the kind a delayed shipment provides. Working on multi-agent systems showed me what my previous supply chain work was hiding: alignment is never a given; it has to be designed into the architecture from the start.

Growth Is Not a System

That instinct to build structure before scaling got its next test at the Martin Trust Center, where I’ve been using AI tools to compress the iteration cycle for early ventures: faster prototyping, faster assumption testing, faster validation with less capital burned. The tooling has gotten good enough that a small team can now do in days what used to require months of customer discovery and a real-world pilot that burns through funding.

But the most useful thing I brought into that room wasn’t an AI tool. It was a supply chain instinct about the relationship between velocity and structure. Startups are taught to prioritize growth, and AI makes it easier than ever to move fast, but moving fast without well-structured operations in place leads to problems that compound quietly. The per-unit economics that look fine at 50 customers break at 5,000. Cash cycles that were invisible at low volume become fatal at scale. These aren’t edge cases; they’re the default trajectory for ventures that treat operational structure as something you bolt on after product-market fit rather than something you design for from the first transaction.

What AI tools enable, when used well, is the ability to stress-test those assumptions — about unit economics, cash cycles, and operational structure — earlier and more cheaply than before. That’s the iteration that matters: not just how fast you can build, but how early you can find out where the system breaks.

That question, about where structure enables and where it suffocates, took on a different dimension when I joined the team organizing the MIT Global Startup Workshop (GSW) 2026 in Daegu, South Korea. Now in its 28th year, MIT GSW is a student-run conference that convenes in a different startup ecosystem each year, bringing together founders, investors, academics, and government stakeholders for two days of programming built around one question: How does entrepreneurship take root in a specific place and culture? Hosting it alongside Kyungpook National University means working at the intersection of two innovation cultures that approach venture building differently. It’s a reminder that the operational infrastructure a startup ecosystem takes for granted — logistics networks, financing mechanisms, regulatory clarity — is itself a supply chain problem that must be solved before venture building can scale.

The Problem That Doesn’t Fit Anywhere

The most disorienting project I’ve worked on this year starts with a question most engineers would dismiss in the first five minutes: Why are we building elaborate cooling systems on land when placing a data center underwater offers a vastly more efficient thermal sink?

Working with Prof. Luis Perez-Breva in iTeams, an MIT program that helps deep tech projects find their path from research to real-world impact, I’ve been exploring the feasibility of underwater data centers. The underlying problem is concrete: AI data centers consume enormous amounts of power, and a significant fraction of that power becomes heat that must be removed. Water is a vastly more efficient thermal sink than air. When done correctly, underwater facilities could reduce energy consumption by orders of magnitude. Microsoft and Google have run experiments, but neither has committed to deploying such a solution. The concept hasn’t scaled.

Not because the physics are wrong, but because the problem doesn’t fit anywhere institutionally. It’s too capital-intensive and cross-disciplinary for academic research cycles, and too speculative for corporate quarterly timelines. It lives in the gap between theoretically feasible and operationally real, which is exactly where iTeams operates.

Our job isn’t to solve the full engineering problem. It’s to identify existing technologies — likely from adjacent industries — that could make a first testable version viable, and to define precisely what scaling would require rather than defaulting to the assumption that it will never work. Structurally, it’s the same question supply chain practitioners face when standing up a new network from scratch: How do you design a system that allows an idea to move from concept to deployment, without building in the failure modes that will eventually kill it? That question reframed something I thought I already understood: supply chain expertise doesn’t just live in the optimization; it lives in the gap between what’s feasible and what’s operational.

What Connects All of This

Three different projects, and one lesson that kept arriving uninvited: The hardest part of any system isn’t building it; it’s designing it to hold when your starting assumptions turn out to be wrong. In multi-agent AI, that means anticipating failure modes before they cascade. In early ventures, it means stress-testing unit economics before scale exposes their shortcomings. In deep-sea infrastructure, it means defining what “testable” even looks like before committing capital to a concept that has no institutional home.

The through-line across all three wasn’t a particular background. It was a willingness to be seriously wrong about something, early enough to rethink a design approach before committing to implementation. The MIT SCM program gave me the tools to work rigorously on problems that resist easy categorization. The broader MIT ecosystem gave me the room to test those tools on problems that haven’t found their institutional home yet.

Rui Yang Teo is a graduate candidate in MIT’s Master of Applied Science in Supply Chain Management (MASc-SCM). He spent several years at Apple Inc. managing channel operations and inventory strategy across the APAC region, where he developed a precise appreciation for what well-designed systems can do and what they can’t. He holds an MS in Analytics from Georgia Tech. He is interested in the places where operational discipline and frontier technology have no choice but to figure each other out.

When you arrive at MIT, it is easy to be intimidated by a rigid image of what “expertise” looks like. You might imagine “expertise” as a static badge earned after years of specialized study. You might think that Cambridge is divided into “tech people,” “strategy people,” coders and leaders … and maybe even that you need to pick a lane and stay there.

But you will quickly learn that those walls are imaginary. The defining characteristic of this community isn’t that everyone is already an expert, it’s that everyone is willing to step into the unknown before they have a map.

Building Without a Blueprint

At some point, many MIT students likely find themselves facing a project that, on paper, they have no business building/completing based on their prior experience.

For me, that moment came during my capstone. My partner and I needed to build a data pipeline to extract unstructured data from maritime shipping contracts using local Large Language Models and Retrieval Augmented Generation architecture. When the project began, I didn’t have experience with maritime contracts and I didn’t have a background in advanced machine learning.

In any other environment, that lack of qualifications would be a stop sign. Here, it is simply the starting line. You don’t build things because you are already qualified … you build them to become qualified. You will find yourself straying from the class syllabus to learn more than you otherwise would have because the problem demands it. You will realize that “technical barriers” are often just psychological ones, and that the only way to overcome them is to dive in while the clock is ticking. The MIT community encourages this every day.

The Price of Admission

This mindset will also change how you show up in rooms where you feel out of your depth.

You might find yourself, as I did recently at the Sloan Tech Summit, sitting in roundtables or panel discussions with industry leaders like the CEO of Cerebras AI or the security lead of Anthropic. You might be listening to them debate the ethics of agentic AI and the future of inference, feeling like an imposter because you don’t have a PhD.

But if you listen closely, you will realize something crucial: even the people writing the future are figuring it out as they go. The very definition of a “frontier technology” requires that the conversation about agentic AI doesn’t have an ending yet. The story is being written right now by the people who are willing to ask the questions and implement solutions. You will learn that expertise isn’t the price of admission to these rooms. Curiosity is.

There is a phrase we use here: “No Half Sends.“

It means you don’t wait for permission to be interested. You don’t wait until you feel like an expert to start. You commit fully to the attempt, regardless of the outcome.

If there is one thing you should take with you from my experience at MIT, it’s that the only real prerequisite is passion, and the only true barrier is the hesitation to move.

Don’t wait. No Half Sends.

Stephen C. Day III is a business operations professional from Washington, Pennsylvania with a background in project management, process optimization, procurement, and other management functions. He began his career working on various programs at Lockheed Martin, where he developed a passion for innovation and efficiency. Eager to expand his expertise, he looks forward to collaborating with peers and gaining new insights throughout the program. 

If you ask people what makes the MIT Supply Chain Management Master’s Program special, you’ll get technical answers first: analytics, optimization, quantitative rigor, operations research, supply chain strategy. All true. But the first surprise for me wasn’t the curriculum—it was the people and the sheer diversity of why they were here.

In one classroom, you might find someone who wants to improve global vaccine distribution sitting next to another who cares about humanitarian logistics. Another individual might have expertise in network design working on a project with someone in transportation.

Different industries. Different missions. Different versions of purpose.

What connects everyone isn’t background—it’s a shared curiosity for how systems work and a desire to make them work better. After seven years as a Surface Warfare Officer, immersed in engineering, navigation and shipboard tactics, that mindset felt familiar.

On a ship or in a port, operations don’t exist as abstractions. They demand coordination, timing, accountability, and execution. Systems tested in real life either work or they don’t, and the consequences show up quickly. That’s always appealed to me more than work that lives on PowerPoint.

That same mindset shaped how I thought about my next step. Leaving the Navy was a leap—the kind that doesn’t come with a neat roadmap or a guaranteed destination. But I knew I wanted to keep solving real operational problems, and I wanted to be in environments where decisions, tradeoffs, risk, and reliability mattered. MIT SCM felt like the right place to make that leap because supply chain management lives at the intersection of purpose and practicality.

One thing I’ve appreciated about the program is how purpose shows up quietly—often in what people care about improving. For some, it’s resilience. For others, it’s sustainability, performance, or access. And unlike in theory-heavy fields, the stakes here are real: medicines will reach patients or they won’t; raw materials either arrive on time or production stops; humanitarian aid either makes it through a corridor, or it sits in a warehouse. Operational work has consequences—even when it’s invisible.

For prospective students, I wouldn’t stress about having the “perfect” background. The program doesn’t reward sameness. It rewards curiosity, the willingness to learn new tools, and the ability to bring your own lens to complex problems. In my case, that lens came from the military—where systems, teams, and missions had to work in the real world, not just in theory.

One of the things I’ve come to appreciate most here is how many different versions of purpose can coexist in one cohort. Some classmates are driven by sustainability, some by resilience, some by performance, some by access, some by innovation, and some by service. None of those purposes are mutually exclusive. And yet each one shapes how people approach the same case study, the same dataset, the same model, or the same industry question.

That diversity of purpose isn’t just interesting, it’s also productive. It forces you to see around corners you wouldn’t have noticed on your own.  And it reminds you that operations and supply chain touch the real world in too many ways to have a single definition of impact.

Different industries. Different missions. Different purposes.

Same classroom.

To me, that’s the heart of the MIT SCM experience—and why I’m glad I took the leap.

Ben McGrath is a graduate candidate in MIT’s Supply Chain Management Master’s program. Ben graduated with a BS from the United States Naval Academy and recently completed seven years of active duty service. Throughout his career, Ben has deployed to the Arctic, Mediterranean and across the Middle East aboard multiple guided missile destroyers with a focus in operations, engineering, and weapon systems. His career has allowed him to see transportation and shipping on a global scale, including transiting through the Suez Canal and the Bab el Mandeb strait.

I joined MIT’s Supply Chain Management (SCM) master’s program to become a new type of leader: one who could navigate today’s complex global supply chains with confidence. I knew I needed more than just textbook knowledge; I needed a deeper analytical toolkit, a truly global perspective, and hands-on experience. What I’ve found is an experience built on four core pillars: a curriculum that challenges old ways of thinking, a cohort that brings the world to the classroom, research that puts theory into immediate practice, and a unique campus culture to tie it all together. 

The Curriculum:  

The MIT SCM program’s curriculum is designed to challenge conventional, linear views of supply chains. One standout example is the elective course on System Dynamics, which was a concept pioneered here at the MIT Sloan School of Management. System Dynamics provides a powerful framework for mapping causal loops inherent in any complex system. The course is about modeling networks of stocks, flows, and feedback loops changing over time to understand the outcomes of complex systems. Before MIT, I had heard the term “systems thinking,” but the MIT Sloan course really brought the concept to life for me. Understanding system dynamics ultimately equips supply chain professionals with a systems-level mindset — vital for understanding the true behavior of supply chains, which operate as dynamic systems shaped by countless interacting variables. 

Beyond the core supply chain management related curriculum and electives, I took the unique opportunity to cross-register at Harvard University this Fall. I enrolled in a corporate law and finance course at Harvard Law School because I wanted to take a course that stood out from my others, would widen my professional network, and still learn in an area relevant to supply chain management. The course features professors from law and business schools who present their empirical research studies with the class. After the presentations, we have open-ended discussions on strengths, weaknesses, areas for improvement, and implications of the research presented. My prior work experience, helping a major technology firm navigate trade regulations on semiconductors and supercomputers, makes these discussions particularly relatable.  

The Cohort: 

One of the MIT SCM program’s most significant assets is the composition of the cohort itself. The learning environment is profoundly shaped by the diverse professional and cultural backgrounds of the students. With nearly half of the class being international and a wide range of industry representation, including several military fellows, in-class discussions are enriched with broad perspectives. The atmosphere is also intensely collaborative, fostering a culture where complex problems are examined from multiple viewpoints, mirroring the cross-functional nature of modern supply chain management. Learning to see a problem through the eyes of colleagues with different backgrounds, whether cultural, industrial, or generational, is the perfect training for a career in supply chain, which is fundamentally about leading diverse, cross-functional teams to solve complex, global challenges. We all drink from the MIT fire hose together.  

Applied Research:  

MIT’s SCM program places a strong emphasis on bridging theory with real-world application, most notably through its corporate-sponsored capstone projects. The level of engagement from my team’s corporate sponsor, a leading global oil and gas firm, has been incredible; they recently flew our research team to Houston, Texas for a deep dive visit and global headquarters tour. Our team is building a machine learning/natural language processing data pipeline to extract demurrage-related terms from our corporate sponsor’s unstructured, historical shipping agreements and load them into a normalized database. This 3NF-structured database will then serve as the foundation for future stochastic optimization models aimed at minimizing our sponsor’s demurrage costs. Projects like this exemplify MIT’s “mind and hand” philosophy — combining technical rigor with tangible impact.  

Campus Culture: 

Of course, the MIT experience isn’t confined to lecture halls and libraries. The vibrant culture at MIT is infectious, filled with traditions that are as brilliant as they are quirky. For example, taking out a sailboat from the MIT Sailing Pavilion on the Charles River is a common way to decompress. When the Boston weather forces both MIT sailors and students indoors, that same spirit of fun just moves underground. The campus is connected by a labyrinth of tunnels, which double as the perfect, low-friction racetrack for office chair races: a uniquely MIT way to blow off steam between classes. And then there are the hallmarks that are pure MIT. Take the “Banana Lounge”, a room on campus that offers free bananas 24/7, restocked throughout the day. It’s a small thing, but it embodies the supportive, student-focused spirit of the school. 

Ultimately, the power of the MIT SCM experience lies in how these pillars converge. The curriculum provides the advanced frameworks, the cohort provides the diverse perspectives to enrich them, and the capstone project provides the platform to apply them under real-world pressure. Layered on top of this is the culture — the creativity, humor, and shared drive that make MIT not just a place to study, but a community to belong to. It’s this intense, integrated approach that makes the MIT SCM program so transformative.

Wathila (Wally) Ekanayake is a graduate candidate in MIT’s Supply Chain Management Master’s program and a recipient of the MIT Supply Chain Excellence Award. Prior to MIT, he graduated from Texas A&M University with a bachelor’s degree in supply chain management and worked in server supply chain planning at Dell Technologies. At MIT, his interests include supply chain analytics, data science, and digitalization.

When people hear about MIT, some think of a superhero movie, others think of the university's prestige in innovation and research, and still others imagine that the people who study there are just nerds who spend all day studying.

When I was in my junior year of Industrial & Systems Engineering at Monterrey Tech back in 2018, I had the opportunity to participate in a national competition run by the MIT Sustainable Logistics Initiative (now part of the MIT Sustainable Supply Chain). I never imagined that agreeing to participate in that project would lead me to spend my senior year as a Visiting Student working for Dr. Josué Velazquez Martínez and learning about the MIT Supply Chain Management program.

In my first weeks of 2019 at CTL, I confirmed that the students do spend all day studying, but they also dedicate part of their time to creating memories together and supporting each other whenever needed. It was then that I decided that, regardless of the results of the Supply Chain Excellence Award, I had to make it my goal to be part of the program in the future. After finding out that I was the scholarship winner and seeing my family receive the recognition, I knew I had to start my plan to fulfill the promise I made to the team at my last monthly lunch: ‘I’ll be back for my master’s in a couple of years, so I’ll see you soon”.

So here we are in 2025, halfway through the program, after taking the MicroMasters courses in Supply Chain Management, talking with alumni to learn more about their experience, and learning about the supply chain in areas like procurement, replenishment, inventory, and warehousing at the largest home improvement retail company in Mexico.

Dr. María de Jesús Saenz wasn’t kidding during orientation. MIT truly lives up to its ‘drinking from the firehose’ reputation—p-sets, case studies, conferences, and exams are relentless. But amidst the intensity, there’s another vibrant reality: creating unforgettable memories and leaving a lasting footprint. Every student has a different way to approach it, so next I will give you a little bit about a day in my life as an MIT SCM student. There’s no single ‘right’ way to experience MIT SCM. I’ll give you a snapshot of my day if you’d like to see how one student navigates it.

10:00 – 11:30

My day kicks off with Dr. Eva Ponce's E-commerce Omnichannel Strategy class. Today, we dove right in with a quick quiz, followed by a lively discussion of key takeaways from our previous session with industry speaker Vik Gopalakrishnan, VP SC Engineering at Walmart. Today, we also tackled commercial returns and circular supply chains. This elective is a highlight for me—it's packed with real-world case studies and insights from industry experts, giving us a deep dive into effective omnichannel strategies.

11:30 – 12:30

As class representatives, Tejveer, Ginny, and I meet bi-weekly with Dr. Saénz. We collaborate on upcoming plans, share student feedback, and brainstorm innovative ways to enhance the SCM program experience for our community.

12:30 – 12:50

12:50 – 1:00: Lunchtime! A much-needed pause to recharge and connect with friends. We swap experiences, share laughs, and enjoy each other's company. It's a heartwarming reminder that the SCM community is a supportive family, a home away from home.

12:50 – 1:00

Joining Tejaswini, Bharti, and Anshuman for the walk to class. Since some of our courses are on the main campus this semester, walking through the Infinite Corridor is a tangible reminder – a 'yes, I'm at MIT' moment.

1:00 – 2:30

Global Supply Chain Management class with Dr. Sean Willems. In this class, we  learned that using heuristics is a valuable approach for approximating real-world problems, and that we can continuously refine our solutions through practical implementation and observation.

3:00 – 3:30 (Not pictured) Quick Zoom check-in with Justin Snow, our SCM Career Development & Alumni Relations Counselor, to get some recruiting tips and strategize for my job search.

3:55 – 4:00

A quick walk with Elisa and Marie before our next class, a chance to catch our breath, make weekend plans, and remind ourselves that there's more to life than just studying (even at MIT!)

4:00 – 5:30

Time for Data Science & Machine Learning for Supply Chain Management Lab with Dr. Elenna Dugundji and Dr. Thomas Koch! You will always find SCM students discussing and supporting each other with our projects and finding different ways to improve our coding skills.

In this week after ‘drinking from the firehouse’, I will always remember the Friday night party with friends in one of the grad houses, celebrating my fiancé’s birthday with our closest friends on Saturday and finishing the famous Boston’s Freedom trail on Sunday.

This is just a glimpse into my world at MIT. Your journey will be filled with its own unique adventures and memories.  Don’t forget to enjoy every moment with your SCM family and explore all that student life has to offer, especially on weekends!  These experiences will stay with you and be part of the footprint that you are living here!

Back in high school, my strongest subjects were English, Social Studies, and Art, while I struggled with math and science. This cultivated a fear of STEM subjects, and as a result, I self-labeled as an “arts and humanities” person. In hindsight, that label was a fence I built around my own potential.

When I pursued my undergraduate degree in Business, I concentrated on marketing and international business, areas I felt were complementary to my skills. This decision was largely driven by my desire to maintain a high GPA and be competitive for job opportunities. I avoided quantitative courses out of fear I wouldn’t perform well. Imagine my surprise when I got an A in an upper-level Business Data and Decisions class, the final required course in my degree.

Even more unexpected was how much I enjoyed the class, especially the module on solving linear programming problems using Excel Solver. That class planted a seed that would remain dormant for years to come.

After graduation, I began my first job in management consulting. I wasn’t placed in a specific functional area but was consistently assigned to roles that did not ignite any spark within me. As someone who “lives to work,” I needed my job to contribute to a greater purpose. (For any personality test nerds, my top CliftonStrength is Significance, which translates into doing meaningful work that is part of something larger than myself.)

The first two years of work taught me a lot, but they weren’t fulfilling. I hypothesized that my dream role might lie at the intersection of business and non-profit but had no idea how to make that a reality.

In consulting, it’s encouraged to take on extra projects like volunteering for employee resource groups, supporting proposals, or leading internal initiatives. I decided to say “yes” to everything that came my way, in hopes of better understanding what kind of work I was interested in. One day, a proposal landed in front of me that would completely change the trajectory of my career.

It was a proposal focused on developing responsible labor practices for a group of clothing retailers. I remember thinking, “This is it.” I couldn’t explain why, but I felt a sense of connection greater than anything I had felt towards my other work. I decided to follow that intuition.

Over the next year and a half, I sought out coffee chats, joined mentorship programs, and researched the supply chain field. With every conversation, it became clearer: this was the path I was meant to follow. When I discovered the Supply Chain MicroMasters offered through my employer, I signed up without hesitation.

The commitment required for the MicroMasters was substantial —five courses and a comprehensive final exam, all while balancing my full-time job and personal life. Colleagues who participated in the program warned me about the heavy workload and quantitative focus on math and statistics. The thought of diving back into math was daunting, but I knew this was necessary to pursue my passion. The fear that once held me back had faded, and I wanted to be capable of more.

It took me three years to finish the MicroMasters. During that time, I continued working full-time and studied during evenings and weekends. My study buddy and I spent more time together than I did with my family (love you, Victoria!). There were countless late nights, weekends sacrificed, and moments of teary frustration. I was determined to finish no matter how long it took as this set me up for my next milestone: applying to the Supply Chain Management Blended (SCMb) program at MIT.

That milestone became my north star—sometimes shining brightly in the distance, other times barely visible against a clouded sky, but always there, guiding me forward.

Fast forward to today: I’ve accepted my offer to join the class of 2025 SCMb cohort and have been living in Cambridge for two months. Every day, I feel fortunate to learn from world-class professors, collaborate with incredible peers, research with a brilliant capstone partner, and immerse myself in a field I love.

I look back fondly at the twists and turns that brought me to the world of supply chain. From growing up with a fear of math to diving headfirst into analytics, data science, and machine learning, my journey to MIT has been one of personal growth, hard work, and sacrifice. There are moments when I regret not pursuing my intuition from that Data and Decisions class sooner—what might my life look like today if I had listened to myself? But whenever that regret creeps in, I remind myself of this proverb:

The best time to start anything was yesterday. The second best time is today.

Pre-MIT: I came to visit MIT in Aug 2023 prior to applying for SCMb, and got to see the campus and meet the famous Dr. Josue Velazquez

A family photo with my roomies (we’re all in SCMb)

Christina (my capstone partner) and I at the SCALE Research Expo

My team making the finals for the Supply Chain Network Design challenge, taking a photo with our instructor Austin

My study buddies from work (Victoria, Ashley, me) and I finally getting together after I moved to Cambridge and meeting the famous Dr. Caplice in person

‘Guru’ is a word adopted from Sanskrit, which has come to mean “expert” in English (e.g. “Operations Guru”), but originally meant something closer to “prophet” or “mentor”.  In South Asian cultures, educational attainment is one of the highest values one can aspire to, and as such Gurus are regarded with God-like status. There is a famous story from the Hindu epic Mahabharat, where an aspiring archery student voluntarily chops off one of his thumbs and offers it as a tribute to his Guru as a symbol of his commitment to his teacher. While admissions requirements have (thankfully) evolved from chopping off one’s appendages to submitting essays and test scores, the reverence for experts that chose to impart their knowledge to starry eyed pupils remains.

Dr. Goentzel is my capstone advisor. In the fall, he is often seen holding his Supply Chain Finance class outdoors, standing with his notes, surrounded by students sitting on lawn chairs, or cross-legged on the grass, in a scene reminiscent of the old school Gurus in South Asia. Dr. Goentzel leads the Center’s Humanitarian Supply Chain Lab, which gets activated by FEMA whenever a natural disaster strikes to assess infrastructure damage, forecast relief supply needs, and coordinate logistics between responders (all in real-time). While I have never seen what the activation process looks like, I like to think it is something like a bat signal pointing into Dr. Goenzel’s office calling for his help.

Over the course of a single semester, Dr. Acocella, via her Logistics Systems class, has equipped us with enough knowledge to confidently call ourselves Supply Chain experts for a lifetime. She has demystified forecasting methods, Sales & Operations planning, inventory policies and freight procurement among others. She has armed us with an arsenal of equations, grounded with numerous real-world applications from her practice, to tackle demand planning and inventory management woes for organizations at all levels of supply chain planning maturity.

While Dr. Janjevic gives her Advanced Network Design lectures in English, I am convinced Math notation is her first language. She has the superpower of being able to translate any supply chain network problem into nodes, arcs, constraints, decisions and objectives almost instantaneously, generating maps that depict optimal scenarios for entire value-chains as the class looks in awe. Dr. Janjevic leads the Center’s Supply Chain Design Lab, and has taught us the value of good network design in moving supply chain management from a cost control engine in an organization to a more strategic role that can maximize revenue, lower carbon footprints, and improve service.

In the traditional South Asian education system, students lived with their Guru in a setup called a “Gurukul”. Apart from our living quarters being separate, building E40 comes close to this setup. Our instructors, advisors and TAs have offices on the 2nd floor, and on the 3rd floor we have the SCM lab – the spiritual home of the SCM student. Coming into the program, I didn’t fully appreciate the value of this space, but now I see it as one of the biggest reasons our cohort is so tightly knit. This is the space where we spend countless hours working on PSets (MIT way of saying Homework), developing our capstones, listening to guest speakers, or just drinking coffee and chatting about life.

The diversity (and yet interconnectedness) of our professional and cultural backgrounds, and the sheer amount of time we have gotten to spend with each other, has made the SCM cohort itself my Guru—both in the English sense of expertise and the Sanskrit sense of a selfless guide. Name any sort of expertise and someone in this class will have it: we have Python gurus, procurement gurus, case prep gurus, endurance racing gurus, and musical gurus to name a few. But what has left the deepest impression on me is how this class embodies the Sanskrit notion of a guru. My classmates’ willingness to share their time and insights enthusiastically, never treating their knowledge as proprietary, but rather as something to be shared to move us all forward together, has been inspiring. While I don’t see myself chopping off my thumb in tribute to them anytime soon, my gratitude for my classmates and professors is immense.