Hi Canan, thank you for accepting this interview. To start, could you introduce yourself and share a bit about your academic and professional background?
Sure, my name is Canan Gunes Corlu, and I am currently an associate professor in the Administrative Sciences department of Metropolitan College at Boston University. I received my PhD in operations management from the Tepper School of Business at Carnegie Mellon University in 2010. Before joining Boston University in 2012, I was an assistant professor in the Industrial Engineering department at Bilkent University in Turkey. My areas of expertise are operations management and supply chain management, where I’ve been teaching and conducting research for quite some time now.
Moving on to your paper, which focuses on supply chain risks during catastrophic events, why do you believe it’s crucial for companies to start paying more attention to these risks?
Catastrophic events, particularly natural disasters, were once rare, but unfortunately, we are seeing them more frequently. A recent example is Hurricane Helen in Florida, followed by Hurricane Milton just a few weeks later. These events have devastating consequences for companies—they can completely halt supply chain operations, leading to billions of dollars in damage, and in some cases, pushing companies toward bankruptcy. We have unfortunate examples of this from the past. For these reasons, companies need to think about such events and make plans to mitigate the risks associated with them.
What are some early signs that companies should look for to identify potential vulnerabilities in their supply chain?
First, it’s essential to map out the supply chain and identify vulnerabilities. Sometimes companies aren’t fully aware of the links in their supply chain and how they might be affected by disruptive events. For instance, a company could be located in a stable country but sourcing supplies from a region that is highly vulnerable to natural disasters. Mapping out the supply chain helps highlight these vulnerabilities, and companies can then make plans to address what would happen if a disaster struck in that particular region.
Your paper also discusses the strategy of adding backup stocking locations to manage supply chain risks. What are the benefits of this approach, and how can businesses determine if it’s the right choice for them?
The idea is that companies can have two stocking locations: a primary and a secondary one. If the primary location is hit by a disaster—whether man-made or natural—the company could lose part or all of its inventory. In that case, it would not be able to supply the market, which directly impacts both the company’s bottom line and its customers.
Having a backup location allows the company to transfer stock from that backup to the primary location, ensuring customer demand is met. This is a risk mitigation strategy that some companies already use.
Could this model also be applied to smaller businesses, or is it more suitable for larger companies?
It’s relevant for any company, big or small, that operates a supply chain. The model is applicable regardless of company size.
With the rise of global disruptions, how do you see the strategies discussed in your paper helping companies become more resilient and better prepared for future crises?
One common risk mitigation strategy is holding inventory. Our study helps companies determine when holding inventory at an alternative location is desirable. Having only one location to store inventory is like putting all your eggs in one basket, which we know is not the best approach. Having a second location makes the company more resilient and enables it to continue operations even when a disaster strikes. Using our model, companies can figure out how much inventory they should keep in their primary and secondary locations to mitigate catastrophic risks and improve resilience.
Speaking of the practical impact of your research, what influence do you hope your work will have on the business world?
Risk mitigation is a hot topic in business right now. If companies do not have a secondary location to store their inventory, I hope that our work will convince them to consider it as a strategy and help them decide if they need such a location.
Are there specific industries or sectors that you believe could benefit the most from applying the concepts in your paper?
Any company that holds inventory in its supply chain could benefit, regardless of industry. This work is applicable to companies both big and small. It’s not limited to any specific sector.
Have you identified any companies or projects where you see potential collaboration based on your research?
Not a specific one, but I was motivated by some of the news articles I read, where companies lost their inventory because they only had one storage location. Right now, I don’t have a particular company in mind, but I believe any company could start using this model.
What type of organizations or industries would you be interested in collaborating with based on your research?
Industries like pharmaceuticals, agriculture, and manufacturing come to mind. These sectors could greatly benefit from the strategies discussed in our paper.
Are you considering any future developments or new research directions based on this work?
Yes, there are several ways to extend this research. Our current model is a basic setup, so there is room to explore more complex scenarios. For instance, in the paper, we consider only two stocking locations, but future research could explore multiple locations with cross-location dependencies. If one location is hit by a disaster, there could be a chance that another nearby location might also be affected. How should companies then store inventory across these locations? Another extension could look at dynamic inventory relocation. Nowadays, we often know when a disaster is coming, even if it’s just a few days in advance. Companies might have time to prepare by relocating their inventory dynamically to avoid losses. This is an interesting research question to explore. Lastly, some disasters cause changes in customer demand patterns, which could also be an interesting area for further study.
Currently, I have been working on digital twins for supply chains. With recent technological advances, digital twins have become an essential concept for companies toward their path to digitalization. My research with Dr. Bahar Biller (SAS Institute, Inc) and Dr. Stephan Biller (Purdue University) aims to equip companies with the knowledge on the benefits of digital twins and their implementation.
How do you see the future of decision science over the next five to ten years, especially in the context of Industry 4.0 and automation?
That’s a great question. I think we’re already seeing some of this happening, but over the next five to ten years, decision science will increasingly leverage AI tools and machine learning algorithms, leading to better-informed decisions. I also anticipate growing interest in human-AI collaboration, which was a theme at the conference. We’ll likely see decision science open up to disciplines like cognitive science and psychology to better understand and enhance human-AI collaboration.
