When every decision in your supply chain feels high-stakes, how can you be sure your strategies will hold up in the real world? In this episode of GAINS On, host Joe Davis talks with GAINS Product Owner Renee Thiesing about how discrete event simulation helps planners test, refine, and gain confidence in their designs before they go live.
From testing order fulfillment policies to stress-testing resiliency under site shutdowns, this conversation shows how simulation gives leaders visibility into the trade-offs between cost, service, and risk. You’ll learn how GAINS customers are using simulation to turn uncertainty into strategy, and why now is the time to adopt it.
Three reasons to listen:
Hello, once again, supply chain adventurers, strategy aficionados and decision dynamos. Joe Davis here, your Friendly Neighborhood podcast host, welcome you back to GAINS On the Show that lets you peer into the future of supply chain strategy, planning, and design. Powered as always by the brilliant minds at GAINS. Now, when you hear the word simulation, your mind might go to video games, flight training, or let’s be honest, the Matrix. But here in the real world, simulation is quickly becoming one of the most powerful tools in the supply chain toolkit. Today we’re digging into what supply chain simulation actually is, how it differs from scenario planning and why it’s more accessible and more important than ever before. Joining me is GAINS’s own Renee Thiesing, who’s leading the charge on putting simulation into the hands of planners, analysts and supply chain leaders alike. We’ll explore how simulation helps organizations model real world complexity, test the impact of disruptions before they happen, and find the right balance between cost, service, and resilience. Ready to plug in? Let’s get into it. Renee, welcome to the show.
Thanks. I’m happy to be here.
So Renee, we talk a lot about VUCA in supply chain, which stands for volatility, uncertainty, complexity, and ambiguity, right? It’s sort of a shorthand way of saying things are kind of crazy right now between the political climate and the geopolitical climate and our literal climate sort of creating all these disruptions in supply chain. I imagine it’s pretty nerve wracking for folks in supply chain right now, which is why I wanted to bring you on the show today to talk about simulation. Now, I’m familiar with simulation, sort of like we’re living within a simulation like The Matrix, but I don’t think that’s what you’re talking about when we talk about supply chain simulation. So again, if you could break down for me, what do you mean when we’re talking about supply chain simulation? What is it, why do it and why now?
Yeah, yeah, that is a good question. You’re right, this is not at least a airplane simulation, but to be technical, it’s discrete event simulation, which basically means, and it’s been around for decades and decades, it’s really been underutilized though in the supply chain space specifically with being applied towards supply chain design. But it is a technology that allows you to, it schedules events, hence the word discrete event over time. So it’s playing out events over time. Those events are driven by things like customer orders, for example. It’s also driven, another example of an event would be you’re reviewing your inventory and you need to place a replenishment order. Another event is a shipment arrives or a shipment sent. So it really is creating events that simulate day in, day out, the operations that occur, and that’s allowing you then to basically you have this digital twin of your supply chain network so that you can use it to test out, run, to understand your performance. And that’s really what the type of simulation we’re talking about today.
So it’s like a break it before you buy it type thing?
Yeah. Yes, yes, absolutely. Well, let’s not try to break it, but yes, test it before you buy it. Yeah.
So I imagine that simulation, this is something that isn’t new, like you said it’s been around for a long time, but that artificial intelligence has sort of speeded up that process, or at least sort of almost democratize it to an extent that we’re sort of, it’s easier to do than ever. Would you say that’s true?
Absolutely. Yeah. And I think it will just continue to do so as things progress forward and make it easier and easier for our users to use it and actually get the data in a quicker, easier way than they’ve ever been able to.
Is this something that just kind of comes standard with GAINS? Is this something that fits into the bigger toolkit? I know we talk about composable solutions and the ability to plug things in and out. Is simulation one of those things so you can plug in and out to GAINS or your ERP?
Yeah. Great question. So currently you’re going to get the simulation engine accessed through the same user experience as the GAINS Network Optimization. So that’s within Supply Chain Architect. So that’s because it’s complimentary to network design, as I mentioned, and inventory optimization, and it’s often used together in that workflow that includes all three of those modeling techniques. So it’s part of that experience. And so think of simulation as your proving ground for both of those two technologies right. You’re running an optimization, run it through the sim, and then back again. So you might have insights out of your sim and then want to go back into the inventory optimization, for example, and retweak some policies. So it’s all in that same workflow, that same interface. Now, eventually the vision is to provide the integrated workflow into all of the GAINS composable solutions so that there’s a seamless experience for all of our users. So that’s where we’re heading in the future. And I’m just going to beat you to the question. I mean, people ask all the time. So does that mean simulation can’t be used independently? Oh, it can, absolutely. It’s not dependent on any of the other GAINS solutions, it’s just that it’s part of that architect solution, and oftentimes we see it as a combined workflow between the different tools.
So if I were to take you know uh my ERP information and supplier information and my cost tables, all this stuff, I would take all my data and I were able to run that through the simulation. So what you’re saying is that I could test either my existing supply chain design or future supply chain design through the simulation tool without having to have GAINS?
Yeah, absolutely correct. Yep. We’re not dependent on it. It does. Having a network design model or the data ready does help speed up the experience to a simulation because there’s a lot of overlap in the type of data that you need to actually run a design as sim, but it’s definitely not required.
So GAINS is really a composable solution as we know. It’s got a lot of different bits and pieces to it that you can configure to the particular solution that you need. So when we think about the GAINS solutions, something like inventory optimization or something like network design, where does simulation fit into the overall landscape of the GAINS solutions?
Yeah, it’s a great question. I think what simulation’s going to bring to our entire suite is it’s going to bring confidence. That’s probably the best word to kind of describe the entire value proposition. It’s confidence in how your system or how your, the strategic design that comes out of network design or the policies that are coming out of IO, how all of those are actually going to perform and what is the operational feasibility. And it helps our users then be confident that these strategies can actually hold up. And so it’s going to be able to provide that confidence at both the cost level and the service level. And the reason it does this is when you’re running an optimization, you’re aggregating everything up. So you’re not at the level of seeing real orders flow through a network, so you don’t really understand day in and day out what’s happening.
But what simulation can do is it brings this confidence by letting you test policies. So you’re actually going to be able to run your orders your customer orders, whether that’s historical orders, whether that’s future orders through, and you can see how your policies are actually going to perform. So it’s being able to see the impact of things like for example, your order fulfillment, how are my order fulfillment policies affecting my actual order fill rates? And we provide an order fill rate, we provide an order line fill rate, and most tools don’t get to that level. They’re really good at modeling costs. A lot of times cost is our objective, but you need to sometimes make that trade off between cost and service, and that’s what simulation brings. It’s giving you that visibility into the trade-off so you can make those difficult decisions.
It’s all about balance
Correct. Yep, yep. And that’s what operational feasibility is. It’s like, okay, do I go with this policy, this design, I’m going to save myself a lot of money, but at the detriment of potentially reducing my service? And maybe an answer is I’m willing to give up a little service, but you want to have visibility into, well, which customer or which product? And we give you that level of detail so that you can make more informed decisions.
Why is order fulfillment policies such a critical use case?
Yeah, that’s great. That’s a great one. Let’s talk about that. So it, it’s important because it has such an impact on service and the performance of your system and other tools just don’t get into that level of detail. So what does that mean? What do you mean by order fulfillment policies? It’s things like being able to decide what site or what distribution center, fulfillment center manufacturing, which one is the primary fulfillment location for any given customer? And then you can also decide at a customer by customer level, does this customer allow things like back ordering? Right does this, and if so, how long are they willing to wait for a back order to come through? Because that could vary customer by customer, right? Some customers might allow you to partially fill an order, some might not, right? Or a line of an order. And some customers, you have an agreement with them that they’ll allow you to fulfill their orders across multiple sites if you can.
So if your primary distribution center that’s usually used to fulfill orders for this customer, if they’re low on inventory, you’re welcome to go look at another site, a third site, and you can fulfill the order no matter what. Right now, of course, the cost is probably going to go up a bit, but that customer is going to get a better service level. And so that’s something that varies customer by customer, and you’re able to simulate that level of detail in simulation. And these are really, really important because it shapes, this behavior really shapes your inventory levels, it shapes your capacity, and at the end of the day, then of course your service. And so it’s just an important, it’s a great example of the level of detail that you can get to in a simulation model.
Let’s talk some more about service levels. Can you talk more about how simulation provides visibility into service?
Yes. Yes, absolutely. So you can look at your network as a whole and say, overall, I have this percentage of order fill, right, my on time in full for my orders. You can break that down by customer, you can break that down by site, but really you can also look at it day in, day out. So you can also look from a time horizon perspective, how are your service fill rates performing? Maybe there’s seasonality, maybe there’s different peaks and valleys throughout the year. So the simulation really taking that, again, order by order day by day. And so it’s allowing you to see how that’s performing. One example is that really gives you value of seeing this detailed level of services. Let’s say you’ve used our inventory optimization and you’re trying to come up with your ideal policies. And with that approach, you can say that I want to design my inventory policies to meet a certain fill rate.
I have a goal that I need to have a 96% fill rate for my customers and out fitts your inventory policies, well, you can run them through the simulation then. And again, we are applying more operational constraints and realities, and you can test, did I actually get that 90% service rate that I thought I was going to? And the answer might be, yes, on majority of your products, maybe there’s one or two that don’t. But you have that visibility and then you can either decide that you’re okay with the reality or you can go back into inventory optimization and make some tweaks and then retest again.
One thing that I always talk about is that data gives people the power to say no, right. And in the example that you just mentioned, it makes me think if I were to work for somebody, they decided they wanted to have a 100% fill rate. As unrealistic as that is, if you were to say, okay, we will do that for you. We will make sure that we provide you with a 100% fill rate, are you then able to take that data, put it into simulation and have it tell you what it’s going to look like? So the cost of expediting things will cost a certain amount, or having to have a certain amount of on-hand stock in order to make sure that you hit those levels. It can show you that and then come back and say, Hey, a 100% fill rate or whatever, this number is, is unrealistic for these reasons. Let’s see what we can do to get to a more realistic number.
Absolutely. Yeah, hundred. I mean, that’s a great example, right? Because looking, obviously, you have to give things up to get to that a hundred percent, and I’m doing that in air quotes. You really can obviously never get to that, but yet capacity, do you have enough capacity? Are you willing to spend the money on the expedited shipping and the labor? So that’s a great example of being able to really play it out because a lot of times people need to see it, right? They need to see the details, they need to be able to see all that detailed information to be able to really have those light bulbs go off.
So with all that’s going on in the world, and by the time we recorded this, it may be perhaps some sort of alien invasion or a kaiju attack, it’s very difficult to sort anticipate what’s going to come next down the pipeline right. So risk and resiliency is at the top of mind for everyone. And I imagine that this is something that is you know just a perfect fit for simulation.
Yeah. Yes, it absolutely is. I mean, you can use tools, other tools to say, look, for example, let’s start with a facility. Should I put this facility in my network given the fact that there is a high chance it could fail based on its location? Maybe it’s a weather or maybe it’s a political climate. So you could look at it as, should I even put it in my network? And then simulation’s going to help answer that question, but also compliment it with by saying, okay, if this facility does fail, if we decide to put it here and it fails, how is my network going to respond day to day? So simulation is going to play this out, right? It’s going to play out the fact that this facility might go offline for X amount of time, and that X, you can play with different variables.
Does it go down for three weeks? Does it go down for three months? And the simulation will actually do things like rerouting orders that were inbound to that site. It’s actually playing out the fact that capacity in your network is now stressed and you’re going to see your effect on the cost on your service day in, day out. And you also can then get a sense of how long does it take me to recover, right? Because when this back online, it’s going to take time for the network to get back to quote unquote normal. And then what you can also do, taking a step further, is you can run different simulation scenarios that are going to test how these different operational policy decisions, like the decisions that you might make when a disruption happens, for example, which ones of those makes most sense? What is the right thing to do when the site goes down? So in a way, simulation’s helping you make a playbook. It’s your disruption book. So you’re ready, you’re ready to react if God forbid, something happens and the site does go down.
I always think about whenever we talk about a site going down and if having such a huge effect, is that the Irish KFC shortage. I don’t know if you’re familiar with that story where KFC in Ireland decided to move their distribution center to one place that had one road in and out. There was an accident during a sporting event or something like that where a huge traffic jam essentially closed the KFCs. They all ran out of chicken. So I always say when it comes to something like inventory optimization or making improvements to your supply chain, now is always the right time. Well, I guess I take that back before there was a problem is the right time, now is the second best time. So let’s talk about that. Like, why should we be investing in simulation right now? Why should companies come to GAINS seeking a simulation solution? How can we help ’em out today?
Well, I mean, it relates to what we were just talking about with risk and resiliency. I mean, not that all the risks haven’t been around, but it’s so much more visible now, and everybody realizes the impact. I mean, we’re so much more global and supply chains are a lot more vulnerable. We’ve all heard this. And so now you have this tool that can help you prepare and be ready, why not use it? But to address your question of now, not only because it’s going to help your bottom line and your resiliency of your network, but because it’s available, right? It’s available, the learning curve is getting smaller and smaller. I think that there’s been a perceived barrier to entry into simulation and whether or not they’re just afraid of, again, this perceived learning curve or just thinking they need all this data. And I was actually just asked this question yesterday on a different discussion, do you need to wait until you have all of the data and having it be accurate in order to start building the simulation?
And I was very quick to answer no, no, because if you wait for perfect data, you’re going to be waiting forever. And it’s often about to get started with what you have. There’s going to be that some of that data is going to not be accurate. You’re also going to probably have some holes, so fill in the holes with some assumptions and use simulation to actually help you better realize the inaccuracy of your data, better understand, are you okay using some of those assumptions to fill those holes, or are some of those holes really important? So you have to actually go out, spend the time to get that data. But why do that until a simulation? It’s your typical sensitivity analysis that simulation can highlight the fact that, Hey, this is really important. So instead of using some fake data, go off, get the real data, come in and make your simulation that much more accurate. So yeah, I think people need to stop being intimidated about using this technology because it’s really not that difficult to do.
Well, I imagine you talk about missing data, you talk about data that’s not clean, and this is one of the things that I have discussed with our professional services team, is that something that they do. And one of the advantages that we have is that, while I always say before the term snowflake became offensive, that each business was a beautiful and unique snowflake. Everybody has their own individual needs and problems, but there are some problems that are universal or there are some issues or some scenarios that are similar enough where you can sort of extrapolate that data, not by a guess, but more like a calculated estimation. And so having the perfect data, of course, ideal, we want to know where everything is at every time, where it went, who touched it and how it got there. But that’s just not practical. So being able to fill in those gaps and filling those gaps in a knowledgeable and also an educated way is another advantage that we bring to the table.
Absolutely. Yeah, you’re right.
Well, Renee, thank you so much. It’s been really informative. I’ve got a lot to think about, as always. If people want to get in touch, if people want to learn more about simulation and how GAINS does it and how it can benefit them and their supply chain networks, what should they do?
Yeah, great. They can just reach out to us. So happy to have the conversation, happy to show the product, what it looks like, what it can do for you. We’d love to meet and understand their exact needs and work together. Because we’re at the beginning of this journey. So we’re interested in companies that really want to be part of shaping all of the features and functionalities as we’re adding it. So the earlier you can be involved, the better. But yeah, just reach out to us and we’d love to have a conversation.
Great. Well, Renee, thanks so much for coming to GAINS On today.
Thank you very much for having me.
And that concludes our deep dive into a supply chain simulation. A big thanks to Renee Thiesing for joining us and bringing clarity, energy, and just the right amount of matrix references. Here’s what we’ve learned: beyond cool visuals or theoretical exercises, simulation is giving teams a safe, smart way to test decisions before they’re made. Whether you’re evaluating capacity constraints, preparing for disruptions or stress testing network designs, simulation helps you play out what could happen so you can plan for what will happen. And perhaps most importantly, simulation doesn’t replace human decision-making. It strengthens it. If this episode got you thinking about the role simulation could play in your own planning process, head to gainsystems.com to learn more. And if you’re enjoying this season of GAINS On, be sure to share it with a colleague and subscribe. We’ve got lots more insights on the way. Keep learning, keep innovating, and remember: in the very real world of supply chain, we’re all in this together.
This is Joe Davis signing off from GAINS On. Until next time. Want to stay connected with all things GAINS and continue to explore the exhilarating world of supply chain planning and design? Then don’t forget to follow GAINS on LinkedIn where you can be part of our growing and vibrant professional community. And for more content, engaging posts and updates, don’t forget to like and subscribe to GAINS On on YouTube. Trust us, you won’t want to miss what we’re sharing. If today’s podcast episode left you hungry for even more insights, we’ve got you covered. Every episode of GAINS On is accompanied by a detailed blog post for those who wish to dive deeper into the topic. Whether you’re looking to expand your knowledge or find that special morsol of information, our blogs are designed with you in mind. Visit gainsystems.com for more. All the links you need to be found in the subscription below. Thanks once again for tuning into GAINS On. And remember, we are here to help you to code the world of supply chains, one episode at a time.
