Designing Supply Chains for Volatility - with Dr. Gopalendu Pal of Target

**Daniel Faggella** (0:12)
Welcome, everyone, to the Emerge AI in Business Podcast. Today's guest is Dr. Gopalendu Pal, Director of Operations at Target. Dr. Pal joins us on today's episode to unpack why volatility exposes the seams between forecasting, procurement, and operations, and why traditional human-driven scenario planning can't keep pace with the scale and speed of modern research. He explains that leaders need the ability to run hundreds of interconnected simulations, understand enterprise-level trade-offs, not just team-level KPIs. He also underscores that simplifying and stabilizing core processes is what allows automation and AI to strengthen decision-making rather than magnify existing operational weaknesses. Just a quick note for our audience that the views expressed by Dr. Gopalendu Pal on today's program will not reflect that of Gopalendu Pal or its leadership. Today's episode is part of a special series on AI in supply chain design and network strategies sponsored by OptiLogic. Supply chain leaders, mark your calendars. OptiLogic's Opticon 2026 is taking place June 2nd through 4th in Detroit. The event centers on AI-driven design in action, including demonstrations of how teams are collapsing modeling timelines from months to dates. You'll hear from organizations using design as a competitive edge, connect with 300-plus supply chain professionals facing similar challenges, and take part in hands-on training to run network experiments with outputs. Learn more and register at optilogic.com/opticon206. That's optilogic.com/opticon206.
Now, the conversation with Dr. Paul. Dr. Paul, welcome to the show. It's great to have you.

**Dr. Gopalendu Pal** (1:41)
Thank you very much for having me today.

**Daniel Faggella** (1:43)
Supply chains have obviously always mattered, but it seems over the last couple of years, it's become a real issue in the boardroom. We've seen a lot of volatility on the global scale, and it's created a situation where executive leaders do need more insights, and it's more than planning because it's so volatile, and I'm very interested to see what you're seeing on the ground as being the breaking points in the supply chain at the moment.

**Dr. Gopalendu Pal** (2:06)
Yeah, that is a great question. So volatility in the supply chain exists in a multitude of scales. If you look at past, not just two years or so, not just because of COVID-19 and the tariffs, but even in the past, supply chain is a connected global economy. So any kind of perturbation happens anywhere. It really ripples through the entire chain across multiple organizations, multiple countries, very much. But what we have recently seen, the volatility are becoming more predominant. All the systems are becoming more sensitive to these changes.
And part of the reason it's happening is because we are now much more efficient. We are operating on the very cost of how efficient as, as efficient as we actually can get with these systems. So that means whenever there is a small perturbation that is from the run state of the applications, run state of everything, how it operates. A very simple example, right? So if you have a big rock, and you want to break it up into two parts, the best way to do it is to split it wherever there's a crack, right? Of course, we're not trying to split the system in a supply chain. We're trying to make it more integrated to make it work. But the seams of the organization is where the fault typically shows. Now, seams of the organization by that means is that in a supply chain, there are multiple teams, multiple groups. And every group has a very specific functionalities. They have critical miles, they have KPIs, their business goals. Now, those goals are typically connected across the enterprise, but they still have their own criteria that they optimize.
When there is a volatility and we try to make a change, not all those change quite often ripples through the entire strategic organization. And different teams might try to optimize different goals, differently, without creating an interconnected decisions that is most effective for the whole organization, whole enterprise, rather than one or two or maybe five teams instead of many, many different teams. So some team might have to win, some team might have to lose. So those decisions often, at the seams of the organization, cause this problem when there is volatility. And these environments is large. It's very, very large. We're going to talk about solving the largest data problem come to retail. And you're going to see how volatile these situations are, how many teams make a decisions. And whenever there's volatility, those decisions may not always get optimized. That means individually, each team might try to maximize their own outcome. And that's where the breaking sometimes happens.

**Daniel Faggella** (4:45)
And that makes sense to me because as you said, especially in retail, there are a lot of functions involved and each department has their own KPIs, and that's what they are worried about. Do you see specific points of tension in certain departments? Are there two or three departments that are usually vying for results, which do fight against each other?