On the Argentus blog, one of our favourite things to share with our readers is interviews with senior supply chain leaders in our network. Through these interviews, we aim to highlight the best and brightest that the supply chain field in Canada has to offer. 

So today, we’re proud to publish the latest interview in our series—with supply chain Director Robin Lahey!

Robin Lahey is an accomplished supply chain leader with a tremendously successful career across the retail and consumer goods industries. He is a true expert when it comes to supply chain systems implementations, especially inventory management and forecasting systems, and he possesses a deep knowledge of the eCommerce space. Robin’s specialty lies in using data to transform supply chain activities from transactional, task-based functions into strategic centres of insight within a business, aligned with broader organizational goals. More broadly, Robin is the kind of strategic systems-thinker that can deliver the organizational change that companies need to improve data insight, supply chain performance and customer service.

It was great to sit down with Robin and discuss some of the topics that animate his passion for the field.

Our interview touched on a number of areas, including: 

• Robin’s career story in supply chain;
• How to align organizations around transformations to help boost overall company strategy;
• How AI and other emerging technologies are transforming the supply chain function;
• What he looks for when hiring supply chain professionals;
• And more! 

We hope you enjoy the interview as much as we did. 

To start with, I’m wondering if you can tell us a bit more about your career story in supply chain. What got you into the field in the first place? 

I think similar to what you’ve heard from a lot of people, I didn’t necessarily plan a career in supply chain from the outset. I took a job in manufacturing to put myself through university, which led to a Supply Chain Analyst position with Levi Strauss. I always had a love of math and numbers, and I was drawn to the data-intensive nature of supply chain. I loved slicing and dicing data, looking for trends and patterns, and I felt I was good at it. That led in turn to some more senior positions within Levi’s. About 15 years ago I decided to make the move to Walmart and a career in the retail supply chain.

Retail is quite different. I would recommend anyone to have some exposure to it during their career. It’s an adrenaline rush. You continuously move from one seasonal peak to the next with urgency. You don’t get to spend a lot of time patting yourself on the back because you’re on to the next thing. The immediacy is fulfilling. 

After managing every type of commodity at Walmart I moved into what we refer to as a solutions role. I led a team that was responsible for developing and deploying tools and processes that the teams use to manage inventory and availability. These roles gave me the opportunity not just to develop supply chain planning platforms, but to build custom platforms from the ground up. 

Most recently I moved into the eCommerce space. As fast-moving as retail is, eCommerce is even faster. The tools that you’re working on to solve problems today won’t necessarily help you the year after because things change. I find that constant change so exciting.

One of your major specialties is in implementing advanced systems and processes to help supply chains become more strategic. You’ve had some major accomplishments in this area, including implementing machine learning and smart demand forecasting. What do you think are the biggest organizational impediments to these kinds of implementations, and how do you overcome them?

People pay a lot of attention to the technical nature of a transition: what roadblocks exist in terms of going from one platform to another platform? The area that doesn’t get as much attention is having a robust change management plan, which is the biggest impediment to a successful implementation, whatever kind of system it is.

As leaders, it’s important to understand that we have associates who are very comfortable using the existing platform and won’t necessarily buy in. People make a career of being a subject matter expert in a certain platform, and it can be difficult to let go. You need to plan for this resistance, and you need to get senior-level buy-in for a change management plan, which I was lucky to have. You need leadership to communicate regularly in town halls and other formats with their teams, establishing milestones, tracking progress, and building touch points into leadership meetings to make sure it’s top of mind. 

In terms of other success factors, you need to involve the users as you build the requirements, which helps build grassroots champions for the project. Education is critical, and not just initial training. You have to monitor the performance of the team and establish re-training as gaps are identified. You need to establish a way for the team to give feedback so that you can address whether something is a system glitch, or a gap in the training. The makeup of the project team is critical. You need to have people who have credibility who are experts with the existing system. People who can bridge the gap. 

Lastly, celebrate the wins and accomplishments. “Look what we were able to achieve!” It’s not just about an increase in percentage of performance. It’s about highlighting that there’s something that we couldn’t pull off, and now we can.

How do you think AI and deep learning algorithms are changing the supply chain function? What do they make possible that wasn’t possible before? Are there any emerging technologies you see on the horizon that have supply chain applications?

Stop me if I get too nerdy, but I’m very excited by the progress in AI and deep learning algorithms. If you think about supply chain, a fundamental requirement is accurate, timely insights to be able to deploy resources. These models are a boon for supply chains, but it’s important to remember that they’re not plug and play. These models still depend on a proper data structure and data integrity. If your data isn’t clean, it doesn’t matter how sophisticated the model is.

In terms of what’s possible that wasn’t possible before, if you look at the progression of machine learning technology, these models don’t learn continuously. They learn in set intervals, with curated data sets, and our decisions about how to train those models are important. There’s an inherent bias, I think, but through the use of both supervised and unsupervised learning, AI can overcome it. Say you have an input (say price), and an output (sales), and you want to predict what the future sales will be. AI can help in gleaning correlations in data that we didn’t know were there, or were ignored. It can find statistical correlations that you didn’t realize. It can help remove some of that inherent bias. 

With emerging technologies, I think of an analogy with the gold rush. During the gold rush, the people who made money weren’t necessarily the miners, other than a handful of very lucky people. It was the merchants who made the pick and shovel to sell to the miners. I like to wonder, what will be the pick and shovel of these emerging technologies? One trend that’s gaining traction is in using RFID for inventory. A tracking device gets attached to every case, to provide you with real-time info about where every item is throughout the supply chain. Is the pick and shovel the actual device, miniaturization and proliferation? Might be. Or is it the tools that we use to process that data to make better decisions? I personally believe it’s the latter. The companies that learn to use and incorporate those tools most effectively will be the ones who will capitalize. 

You have an extensive background across the supply chain function, but eCommerce has been a big focus of yours. eCommerce seems to be its own beast in the supply chain, with its own challenges, and many companies struggle to succeed. What do you think are the biggest factors in companies achieving eCommerce success, and where do you see it evolving from a supply chain perspective?

eCommerce is being embraced at a rapid pace, and that poses unique challenges for companies. Solving the problems of today is only the opening ante for next year’s problems. 

During the pandemic, we had to sell online. We had no choice. Retailers scrambled to increase the order fulfilment capacity any way they could. They established a wide variety of fulfilment options, just to meet the demand. Now they’re being left with complex, multi-channel networks, which have a significant variance in performance and cost across channels and nodes. To achieve success going forward, retailers need to find a deep understanding of tradeoffs in those different networks.

How do they do that? It’s about measuring. Companies need to develop analytics platforms that objectively reflect order fulfilment and costs. I say objectively, because some companies use an average. Really getting at the true costs is crucial. Fulfilment costs are the biggest controllable expense you have in your network, and getting that right is critical.

Once you understand those costs, you need to define the right Key Performance Indicators (KPIs) for fulfilment—the ones that directly impact the customer experience. KPIs are the lifeblood of supply chain. But do we have the right ones when it comes to eCommerce? As we measure these different nodes within our now-complex multi-channel network, we can objectively decide: here’s where we send the order. For example, on a small consumable item, maybe a fulfilment centre performs best from a customer standpoint. For a big, bulky item, maybe store fulfilment is better or drop ship is better. Being able to make those decisions on different commodity types, and utilize your network in the most optimal fashion, is going to be key to long-term eCommerce success. 

When you’re hiring, how do you identify people who will be strong performers?

In terms of hiring, I of course look for individuals who have strong foundational supply chain skills: problem solving, troubleshooting, and having a natural curiosity. Rather than just assuming everything is working well, if you have natural curiosity, you’ll figure out how to slice and dice the data and find things out for yourself. When I’m interviewing candidates, I drill down on problem solving skills. Why did they choose the approach that they did? What were the factors in the decision making? How did they determine the tradeoffs to be made? That helps me understand whether a candidate can operate at a strategic level, or a more task-based execution mindset—which is fine, by the way, because you need that as well! Ultimately, you can’t talk about recruitment in supply chain without talking about tech savvy and analytical skills. These skills were a “nice to have” in the past. Now they’re a minimum requirement. 

I’m looking to see if the person can see the forest for the trees. In a big picture sense, I’m looking for whether someone can get to the “so what?” Are you happy enough just to identify a problem? If you can’t get to the point where someone can make a decision to offer a solution, it’s just the weather. 

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We always enjoy getting to chat with a proven supply chain leader like Robin. Whether you’re looking to build your supply chain career, looking to hire, or just looking to hear a seasoned perspective on emerging supply chain issues, we hope you find his comments as insightful as we did. And stay tuned for more interviews in the coming weeks with other luminaries from the supply chain field. 

And as always, if you have any immediate or upcoming hiring needs in Supply Chain Management, Procurement or their related areas, reach out to Argentus today! Call 416 364 9919 or send an email outlining your requirements to recruit@argentus.com.