Operations Research
Operations Research on Beyond Market Intelligence: a running collection of 5 stories we have gathered and hand-picked because they are worth your time. Every post here touches on operations research in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around operations research, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
MS in Operations Research vs Data Science
Choosing between an MS in Operations Research (OR) and Data Science after a Data Science undergraduate degree presents a strategic career decision. While specialization in Data Science offers continued focus, an OR degree can broaden your problem-solving toolkit and potentially unlock unique opportunities, especially given your current Operations Research Analyst role. OR is demonstrably math-intensive; beyond your existing calculus, linear algebra, and statistics foundation, expect to delve into optimization, stochastic modeling, and simulation.

Los Movimientos, Part II: Solving Large Pickup-and-Delivery Problems with Adaptive Large Neighborhood Search
Tackle complex pickup-and-delivery logistics with "Los Movimientos, Part II," a practical guide to solving large-scale routing problems. This post details the construction of an Adaptive Large Neighborhood Search (ALNS) heuristic in Python, addressing vehicle routing, time windows, capacity constraints, and essential driver breaks. We demonstrate a future-focused approach to optimization, empowering data scientists to build efficient solutions. For a broader perspective on leveraging AI within business contexts, explore "What Professionals Should Know About Data Science and AI" for essential considerations.

“Los Movimientos”: The Routing Problem That Nearly Broke My Spirit
Facing a complex pickup-and-delivery problem with tight time windows? “Los Movimientos”: The Routing Problem That Nearly Broke My Spirit details a challenging optimization journey, demonstrating how mathematical techniques can tackle real-world logistical hurdles. This post explores the intricacies of routing, offering practical insights for anyone grappling with similar constraints. Discover how careful problem formulation and optimization algorithms can yield surprisingly effective solutions—a process that underscores the power of data science.

When Data Science Makes Us Sad: The Story of an Overbooked Flight
Data science isn't always a victory. Sometimes, it highlights uncomfortable truths, as revealed in "When Data Science Makes Us Sad: The Story of an Overbooked Flight." This compelling piece explores a real-world scenario where algorithmic decisions resulted in an $8 million payout versus a potential $5,000 resolution—and the possibility of significant public backlash. Discover how seemingly rational data models can lead to unexpected, and costly, outcomes. For a deeper dive into optimizing AI performance, explore "Prompt Compression Techniques."
Are there some textbooks that take a primarily engineering approach to machine learning (as opposed to a "scientific" approach)? [D]
Many find the transition from theoretical machine learning to practical software implementation challenging, especially when navigating complex organizational structures. While many textbooks prioritize a scientific, statistical foundation, fewer focus on the engineering principles needed to build robust, production-ready ML components. If you're seeking a more pragmatic approach—one that emphasizes efficient software development and integration—consider exploring resources that prioritize engineering workflows. As discussed in "Platform Engineering for Everyone," successful ML implementation requires more than just technology; it demands a well-defined platform.