100K downloads and counting!

If you've ever visited a hospital emergency department, chances are you've experienced one of its most persistent challenges: waiting. For hospitals, reducing those wait times can seem like a capacity problem. More patients require more beds, more staff or more space, right? But what if one of the solutions is simply making better decisions about how the resources already available are used? Joining me today is Agni Orfanoudaki, Oxford University, to share new research on a data-driven approach to determining which patients actually need a traditional emergency department bed and who can be treated in alternate locations. Ultimately, this reduced emergency room stays by 11 minutes, all without adding staff, beds or technology, and without compromising patient safety.

Organizations have more data, more dashboards, and more sophisticated analytics tools than ever before. And yet, many still struggle to make confident decisions quickly. Sometimes the problem isn't the data itself. It's what happens between the insight and the action: unclear ownership, competing versions of the truth, slow review cycles, and analytics that sit beside the business instead of helping shape it. In today's episode of Resoundingly Human: The INFORMS Podcast, I'm joined by Ritish Chugh, Senior Analytics Engineer with Airbnb, to talk about what it takes to move from producing analytics to building an organization that actually knows how to use it.

Joining me today is Katalia Chen, recipient of INFORMS Doing Good with Good OR Award, which recognizes outstanding work using operations research to create meaningful social impact. Katalia's research tackles a question that affects hundreds of thousands of animals every year: how can we help animal shelters make better decisions when resources like kennel space, staff time, and foster homes are limited? By combining operations research, optimization, survival analysis, and causal inference, her work demonstrates that smarter allocation of these scarce resources can dramatically increase the number of lives saved – without building new facilities or increasing capacity.

Reaching 100,000 downloads isn't just a milestone – it's a reflection that the stories featured on Resoundingly Human matter. It means there are thousands of people who are curious about how analytics can solve meaningful problems and who want to hear directly from the people making that happen. To celebrate, let's take a look back at our top five favorite conversations from throughout the years. These aren't necessarily the most downloaded episodes – they're simply five conversations that challenged our thinking, taught us something unexpected, or perfectly captured what Resoundingly Human is all about.

Few topics generate more debate than elections. But long before voters head to the polls, important decisions have already been made about how communities are grouped into districts and how representation is structured. While redistricting is often discussed as a political issue, it's also a fascinating operations research problem – one involving competing objectives and complex constraints such as geography, population, representation, and legal requirements, as well as competing definitions of fairness. My guest today, Ian Ludden, Assistant Professor of Computer Science and Software Engineering at Rose-Hulman Institute of Technology, will share how computational methods and OR/MS are helping researchers evaluate district maps and better understand the choices that shape our democracy. We'll explore questions of fairness, representation, and how data-driven approaches can help us better understand one of the most consequential – and often controversial – processes in American democracy.

Today, we're talking about a topic that sits at the heart of the INFORMS mission: public engagement. While many people think of analytics and operations research as tools used in businesses, universities, or research labs, these disciplines also play an important role in informing public policy, improving government decision-making, and helping communities tackle difficult problems. Joining me today is someone who has spent his career not only advancing the field, but helping others understand its value and impact. Jim Cochran is a professor at the University of Alabama, an internationally recognized educator, researcher, and advocate for analytics and operations research. He is also the recipient of the 2025 INFORMS Advocacy and Governance Committee Award for Public Engagement.

Earlier this year, we kicked off 2026 with INFORMS President Mark Lewis, talking about his vision for the year ahead. Now, just after the INFORMS Analytics+ Conference – his first major event as president – we're checking back in to reflect on what we've seen so far, what stood out, and what's still ahead for the INFORMS community.

In this episode, we're diving into something every one of us experiences - but may not always think about strategically: customer relationships. Why do we stay loyal to some brands and leave others after one frustrating interaction? How are analytics and AI helping companies predict churn, personalize experiences, and build trust in a world where customers have more power than ever before? Helping tackle these questions is Ankit Agrawal, whose work sits at the intersection of analytics, customer experience, and business strategy. We'll talk about what companies are getting wrong about loyalty, how CRM has evolved, and why the future of customer relationships may depend as much on empathy as it does on algorithms.

In the final epiosde of our special series highlighting the finalists of the 2026 Franz Edelman Award, members of the team from Microsoft share special insight on their project, which is transforming how global cloud infrastructure is supplied and delivered. As demand for cloud services continues to grow, the logistics behind delivering the hardware that powers data centers have become increasingly complex. To meet this challenge, Microsoft developed a platform – the Intelligent Fulfillment Service – that combines machine learning, mathematical optimization, and generative and agentic AI to automate global shipment

This latest episode in the mini-series highlighting the 2026 Franz Edelman Award finalist featues members of the team from Google, whose project is advancing a new approach to managing energy and computing resources across the company's global data center network. Data centers power the digital services we rely on every day, but they also require enormous amounts of energy. To address this challenge, Google developed a first-of-its-kind system that intelligently shifts flexible computing workloads across both time and location to take advantage of cleaner energy sources. In this episode, we'll hear more about how this innovative system works and the impact it's having.