Under the agreement, AISPAR will distribute SCM Globe across its network in Africa, giving universities, training programs and institutions access to a hands-on tool for learning supply chain management.

Why it matters

Supply chain education works best when students can practice, not just study. Learning by doing is what turns theory into real skill, and access to that kind of practical tool has not always been easy to come by across the continent. This partnership is a step toward closing that gap.

By pairing SCM Globe’s simulation platform with AISPAR’s expertise and reach in African supply chain education, the two organizations aim to give more students the chance to learn the way practitioners actually work.

About AISPAR

The African Institute of Strategic Purchasing and Research is a Kenya-registered consultancy and research organization with an Africa-wide focus. It connects industry professionals, academics and public-sector institutions, and works to strengthen supply chain professionalism across the continent through consultancy, applied research, training and capacity building.

AISPAR and its founder, Charles Malack Oloo, have worked with governments, NGOs, universities, professional bodies and businesses, including partnerships in Kenya and Zambia. Its work spans strategic purchasing, procurement, supplier development, performance management, monitoring and evaluation, professional training, and research into food systems and resilient supply chains.

About SCM Globe

SCM Globe is a cloud-based supply chain modeling and simulation platform used by universities, companies and training organizations around the world. Its map-based interface lets anyone build and simulate real supply chains without prior technical experience, which has made it a widely used tool for supply chain training.

Looking ahead

The shared goal of this collaboration is simple: give more African students and professionals access to the tools that build real supply chain skills, and support the people already working to raise the standard of supply chain education across the continent.

For more on the partnership, contact SCM Globe at info@scmglobe.com.

What is actually in the battery

A modern EV battery depends on a short list of minerals, each with its own story.

Lithium is in almost every battery type, and graphite forms the anode in nearly every cell. The bigger differences come from the cathode, the side of the cell that largely sets how much energy it holds. The cathode chemistry that dominated for years is nickel manganese cobalt (NMC), valued for range.

None of these are truly rare in the ground. The problem is where they are concentrated, and even more, where they are processed.

Mining is only half the story

It is easy to focus on mines, but the tighter point usually sits one step later, in refining and processing.

Raw ore has to be refined into battery-grade material, then turned into the cathode and anode material that goes into a cell. This middle stage is far more concentrated than mining, with China holding a dominant position in refining most battery minerals and in making cathode and anode material.

The recent move toward lithium iron phosphate (LFP) batteries makes this sharper. LFP has grown from a small part of the EV market to about half, because it is cheaper and has improved. But the LFP supply chain is even more concentrated, with most LFP cathode material and cells made in a single country. A chemistry that lowers reliance on cobalt can, at the same time, raise reliance on one place.

A road full of chokepoints

Follow the physical path and the risk becomes clear. Minerals move from mine to refinery to material maker to cell maker to vehicle assembly, often crossing several continents and oceans on the way.

That long route passes through chokepoints, narrow passages like major canals and straits that a large share of world trade has to go through. When one of them is blocked, whether by drought, conflict or congestion, ships take longer routes, costs go up, and delivery times stretch. For an industry that runs on tight, just-in-time delivery, one chokepoint can send shocks a long way down the line.

The deeper problem is how connected everything is. Because the network is so concentrated, a decision made in one country does not stay in that country. Cobalt is the clearest recent example. The Democratic Republic of the Congo supplies close to two thirds of the world’s cobalt. When it announced a temporary export ban in early 2025, later replaced by export quotas, prices roughly doubled within months. Concentration and long distance together make the chain fragile.

This is also why so much effort today goes not into finding more ore, but into rebuilding the middle of the chain: new refining capacity, regional processing, recycling, and alternative routes that reduce reliance on any one chokepoint.

The decisions this chain forces

If a chokepoint closes, do you reroute and accept the longer transit, or carry more buffer stock upstream so the delay never reaches the plant? If a refining source becomes unavailable, do you qualify a second supplier now at a higher price, or wait and hope? If demand for one chemistry jumps, do you follow it and deepen your reliance on one region?

None of these have an obvious answer, because each one trades cost against risk against service, and the numbers are hard to hold in your head. Extra transit days, extra inventory, extra cost per unit, all moving at once across a network that spans several continents. And what counts as a good trade-off is not universal. It depends on the priorities and constraints of your own company and supply chain.

That is what makes this supply chain worth building as a model. When you lay the network out, run it, and then close a chokepoint or cut off a source, you do not just see the disruption. You have to choose a response, and then watch what that choice actually costs across the rest of the supply chain.

It is also why we are turning it into a supply chain case study, built on SCM Globe, where students take charge of an EV battery mineral network and steer it through exactly these decisions.

We are building it alongside a second one on the AI chip supply chain, which runs into its own version of the same problem. Both should be ready soon.

Here is the road it takes, and why the hardest part of it keeps moving.

From design to data center

An AI chip passes through several different hands before it does any work.

It starts as a design. Companies like NVIDIA and AMD design their chips but do not make them. That job goes to a foundry, mostly TSMC in Taiwan, which turns the design into silicon wafers using some of the most advanced manufacturing there is.

A finished wafer is not a usable chip yet. AI chips need a lot of memory bandwidth, so they are paired with high-bandwidth memory, or HBM, made by a small group of suppliers led by SK hynix, with Micron and Samsung ramping up. The chip and the memory then have to be joined together in a step called advanced packaging (CoWoS), which stacks them onto one substrate. Without this step, a wafer is just silicon that is not a product yet.

Only then is the chip put onto boards, built into servers, and shipped to the data centers where AI runs.

The bottleneck keeps moving

What makes this supply chain a good example is that the tightest point keeps changing.

From 2021 to 2024, the problem was raw capacity. There were not enough wafers, and getting GPUs was the whole game.

By 2025 and into 2026, the tight point moved to advanced packaging. TSMC’s CoWoS capacity was reported sold out through 2026, with NVIDIA taking most of it and the rest shared among a few other companies. Making more wafers did not help if they could not be packaged.

As packaging capacity grew, the tight point moved again, this time to memory. HBM supply for 2026 has been described as sold out, and it is expected to stay tight. Memory, not the chip itself, now sets the limit on how many AI chips can actually be built.

Even the companies trying to get around this, the big cloud players designing their own chips like Google, Amazon and Microsoft, do not escape it. Their custom chips still compete for the same foundry and the same memory as everyone else.

Why the shape of the chain matters

Two things make this supply chain fragile.

1. The first is concentration. A big share of the world’s most advanced chips goes through a small number of factories and suppliers, many in one region. When so much depends on so few points, any problem, whether political, logistical or technical, has an outsized effect.
2. The second is how connected it is. A shortage in one step does not stay there. When memory makers move production toward HBM for AI, normal memory gets tighter for everyone else, and industries with no direct link to AI, like automotive and consumer electronics, feel it too.

That is what makes this supply chain worth studying. It is not just long. It is a system where the tight point keeps moving, where fixing one thing reveals a new limit somewhere else, and where a local problem spreads worldwide.

Seeing it, not just reading about it

A supply chain like this is hard to picture from a description. How capacity, allocation, cost and disruption interact only becomes clear when you can watch it run over time.

That is exactly why it makes a good simulation. When you build the network, run it, and then cause a disruption in one region, you see the effects move through the rest of the chain, and you have to make real decisions in response.

This is the idea behind one of the two case studies we’re building for the fall Supply Chain Competition 26 (see Supply Chain Cup 26 – Spring edition), open to students from universities around the world. They’ll step into the role of the supply chain manager behind an AI chip network and run it under real constraints and disruptions. Reading that the tight point moved from packaging to memory is one thing. Running the chain yourself and watching it happen is another.

The Anatomy of a Modern Logistics Crisis

Global supply chains deliver remarkable efficiency under normal conditions, but a single chokepoint failure can disrupt operations for months or even years.

The 2021 Suez Canal blockage demonstrates this vulnerability at scale (as does the current blockage of the Strait of Hormuz). When the Ever Given container ship ran aground, the incident delayed the delivery of millions of containers and exposed the fragility of the critical maritime highways.

Companies watched helplessly as inventory piled up on one side of the canal while production lines on the other side went dark. The disruption rippled outward for weeks as carriers struggled to reposition vessels and clear backlogs, forcing organizations without contingency plans to absorb massive costs in premium freight, expedited shipping and lost sales.

Building Resilience With Digital Twin Simulations

A digital twin creates a virtual replica of a physical supply chain, mirroring every node, connection and flow in real time. Unlike traditional tracking systems that monitor current conditions, these models enable companies to run simulations that test how networks respond to disruptions before they occur.

The market for digital twins in logistics reached $1.2 billion in 2023, and analysts project it will expand at a 25.7% compound annual growth rate through 2032. This acceleration signals a fundamental shift in how leading businesses approach supply chain management.

Digital twins transform abstract data into actionable intelligence by enabling companies to simulate hypothetical disruptions in their virtual networks. Teams can observe how delays propagate, where bottlenecks form and which suppliers represent single points of failure. This visibility allows organizations to address risks proactively through strategic planning rather than emergency response.

Overcoming Hurdles to AI and Twin Integration

Implementation costs and technical demands are the primary barriers to companies adopting digital twin technology and artificial intelligence (AI) for supply chain operations. The up-front investment in software, data infrastructure and specialized expertise can be difficult to justify without clear evidence of returns.

However, businesses that have implemented AI in supply chain operations have reduced costs by 15% while improving inventory levels by 35% and service levels by 65%. These gains represent fundamental improvements in how supply chains perform under both normal and stressed conditions, not marginal adjustments that appear only in detailed analysis.

The key lies in viewing digital twins as a strategic capability that compounds over time rather than just another information technology project. These systems deliver competitive advantages through accumulated simulation data and refined processes that cannot be quickly replicated.

Key Advantages of a Digital Twin Strategy

Digital twins for supply chains deliver measurable benefits across three critical areas that directly impact competitiveness and operational stability. Enterprises can transform how they develop products, manage operations and respond to market changes.

1) Improve Development Timelines and Manufacturing Yield
Virtual prototyping eliminates the need to commit physical resources before teams validate designs and processes. Companies can test multiple configurations simultaneously in digital space while identifying optimal approaches without expensive trial runs on actual production lines.

Integrating digital twins with comprehensive data management systems can boost manufacturing yield by 60% to 80% by allowing teams to resolve production issues in simulation before they affect real output. These efficiency gains translate directly to faster time-to-market and higher profit margins on new products.

2) Increase Overall Supply Chain Efficiency
Digital twins provide comprehensive visibility that extends beyond individual facilities to encompass entire supply networks. The broad perspective helps organizations identify inefficiencies that go unnoticed when teams analyze isolated segments, revealing patterns that emerge only when viewing the complete system.

Companies using digital twins decrease product development time by 30% while reducing inventory holding costs and improving supplier performance. They can achieve these gains through data-driven insights that reveal the exact sources of delays.

3) Gain Real-Time Visibility Into Container and Asset Flows
Returnable containers and specialized assets often represent significant capital investments that organizations struggle to oversee effectively across complex supply networks. Digital twins for logistics monitor asset flows between facilities while predicting imbalances before problems emerge.

Ford’s implementation demonstrates the practical value of this capability. The company’s digital twin tracks container flows to suppliers and projects future demand to prevent shortages that could trigger premium freight costs or production stoppages. This proactive approach keeps container fleets sized appropriately while avoiding the capital waste of overprovisioning.

A Practical Approach to Simulation and Stress-Testing

Stress testing reveals supply chain problems, enabling organizations to develop targeted responses before crises force reactive decisions. The goal is to understand system vulnerabilities rather than to find a perfect plan that handles every contingency.

Platforms like SCM Globe Enterprise enable teams to run digital simulations to uncover weaknesses by importing data from enterprise resource planning systems. The program, which has both commercial and military applications, provides collaborative tools that allow supply chain operators to share insights and coordinate responses.

Teams gain the most value by systematically causing deliberate supply chain disruptions in their digital models. The simulations reveal which suppliers represent unacceptable risks, where inventory buffers fall short and how transportation failures spread. Organizations use these insights to redesign networks, diversify suppliers and build resilience.

The Future of Logistics Is Proactive, Not Reactive

The next major supply chain disruption is inevitable, but digital twins provide the foundation for building supply chain resilience that limits impact and accelerates recovery. Organizations that prepare through simulation and stress-testing will manage crises with confidence while unprepared competitors scramble to respond. Learn more about our Enterprise real-time supply chain simulation, planning and collaboration platform.

Blog post contributed by: Lou Farrell
Lou is the senior editor of supply chain and manufacturing pieces at Revolutionized Magazine. He has over five years of experience covering transformative tech and industry advancements, and their impacts on management and sustainability.

From March 18 to March 27, 2026, students from six universities worldwide stepped into the shoes of supply chain managers navigating a global smartphone operation under pressure. Armed with SCM Globe’s map-based simulation platform, they were tasked with rebuilding, optimizing, and reshoring a supply chain in the middle of geopolitical disruption, a challenge that mirrors the very real pressures facing supply chain professionals today.

A Competition Built Around Real-World Stakes

This year’s case study, Smartphone Global, placed participants in charge of a fictional global smartphone manufacturer facing cascading operational challenges. The competition ran in three progressive challenges:

• Challenge 1: A Working Supply Chain. Before anything else, students had to get the existing supply chain to run without breaking for 30 days. A seemingly simple task that quickly revealed the fragility of complex global networks.
• Challenge 2: Break Even. With the supply chain stabilized, the pressure shifted to profitability. Students had to optimize routes, vehicles, and facility configurations to generate a positive P&L over 30 days of operations.
• Challenge 3: Reshoring Incentives and Supply Chain Overhaul. The most demanding challenge of the three. Rising US-China tensions and new incentives tied to the India-Middle East-Europe Economic Corridor (IMEC) forced students to relocate their assembly operations to India while keeping the supply chain profitable, lean, and geographically realistic. Final scoring was weighted on profit, average on-hand inventory, and CO2 emissions.

Six Universities. One Winner.

Supply Chain Cup 2026 brought together students from universities worldwide, including the University of Pittsburgh, the University of Moulay Ismail, and Georgia Tech, among others.

Participants competed solo or in teams of up to three, submitting their SCM Globe simulation files, results sheets, and P&L reports through a centralized grading process managed entirely by the SCM Globe team.

After careful review and ranking of all submissions, the winning team is from Katz Graduate School of Business, University of Pittsburgh School of Business:

• Pratyaksh Jain – Masters in Supply Chain Management and Business Analytics – Expected Graduation: December 2026 (LinkedIn)
• Yash Panda – Masters in Marketing and Business Analytics – Expected Graduation: December 2026 (LinkedIn)
• Naveen Srinivas Akoju – MBA – May 2026 graduate (LinkedIn)

Congratulations. Their supply chain design demonstrated outstanding performance across all three scoring dimensions: profitability, inventory efficiency, and environmental impact.

What Participants Said

We asked the winning team to share their experience.

On why they took part: “This competition was introduced to us by our Supply Chain Professor, Dr. Prakash Mirchandani. We decided to participate in the Supply Chain Cup because we wanted to challenge ourselves in a practical, competitive supply chain environment beyond the classroom.

The competition provided an opportunity to adopt a holistic view of supply chain management in a realistic simulation setting, and apply concepts such as demand planning, inventory management, transportation optimization, and strategic decision-making. We were especially interested in experiencing how real-world supply chains respond to operational constraints, disruptions, and trade-offs under pressure. We were also eager to explore and learn more about the SCM Globe simulation platform.”

On what they gained: “The competition helped us better understand how interconnected the supply chain decisions are. We learned that even small operational decisions can significantly impact costs, customer service levels, and overall network efficiency.

Through the SCM Globe simulation, we gained hands-on experience with: 

• Inventory and replenishment planning
• Transportation and distribution strategies
• Capacity balancing
• Cost optimization
• Demand forecasting
• Data-driven decision-making
• Team collaboration under time pressure

The experience also strengthened our ability to analyze problems strategically rather than focusing solely on isolated operational tasks.”

Would they recommend it? “Yes, absolutely. We would highly recommend both the Supply Chain Cup and the SCM Globe simulation tool to students interested in supply chain management. 

The simulation provides a far more interactive and realistic learning experience than traditional case studies or classroom lectures. It helps students understand the complexity of real-world supply chains while developing analytical thinking, collaboration, and decision-making skills.

The competitive environment also adds excitement and encourages participants to think critically, adapt quickly, and continuously improve their strategies. Overall, it is an excellent way to bridge the gap between academic concepts and real-world supply chain challenges.

Based on our experience, we can confidently say that the competition is challenging, but participants will learn a lot and have fun in the process!”

Why Competitions Like This Matter

Supply chain management is one of the most dynamic and consequential fields in the global economy. Yet too often, students learn it through textbooks and case discussions alone. Competitions like Supply Chain Cup bridge that gap by putting students in real decision-making scenarios where every choice has measurable consequences.

As past SCM Globe competitions in France, Morocco, Saudi Arabia, and Indonesia have shown, simulation-based challenges don’t just teach technical skills. They build confidence, strategic thinking, and the ability to operate under time pressure, all of which are exactly what employers are looking for.

We were impressed by the quality and creativity of submissions across all participating universities. Every team that completed the competition demonstrated genuine supply chain thinking, and we are proud to have provided the platform for that learning to happen.

What’s Next

We look forward to welcoming even more universities to the next Supply Chain Cup, returning in the fall 2026 semester. If you are an instructor interested in bringing your students, or a company interested in sponsoring, reach out to us at info@scmglobe.com.

Import data from your ERP system to automatically create digital models of your supply chains. Update these models with daily data imports from your ERP and other relevant systems as business situations and markets change. With every update, run these models in simulations to see how your supply chains will perform in the coming days and weeks. Continuously probe through the fog of uncertainty; see problems before they happen, and find best ways forward as the road ahead twists and turns in unexpected ways.

Download PDF PRODUCT OVERVIEW for SCM Globe Professional and SCM Globe Enterprise/X4SIM

SCM Globe ENTERPRISE for Sales & Operations Planning

Bob Caruso shows the opportunity for companies and their supply chain partners to collaborate and plan joint supply chain operations using a cloud-based platform that displays their supply chain on a digital map updated every day with relevant information imported from ERP and other systems. SCM Globe ENTERPRISE forecasts supply chain performance, analyzes and improves existing supply chains, and designs new ones. Energize and drive your Sales & Operations Planning process; see this illustrated in our case study “Java Furniture Company“.

SCM Globe X4SIM for Military Joint Logistics Planning

Rear Admiral (Ret) Matt Ott explains why planning and managing mission logistics in the modern battlespace calls for the situational awareness provided by an easily understandable planning and real-time monitoring platform usable by everyone from unit logistics personnel to senior commanders. X4SIM was developed for joint mission logistics planning in collaboration with Air Force Special Operations Command. It supports agile application of the DoD Joint Planning Process JP 5-0 (See Chapter III – Joint Planning Process). This is demonstrated in our case study “Syria Evacuation Scenario“.

NOTE: Bob Caruso is the SCM Globe Enterprise Sales Lead; and Matt Ott is a member of the SCM Globe Board of Advisors.

“We wargame because we must. There are certain warfare problems that only gaming can illuminate.” – Robert Rubel, Professor Emeritus, Naval Warfare Studies, U.S. Naval War College.

Military organizations have been using games to train their people and predict possible outcomes of future battles since the Prussian Army began using the wargame “Kriegsspiel” some 200 years ago. This shouldn’t be surprising if we accept the notion that games are a biological adaptation in mammals to gain survival skills. Play is the activity of practicing survival skills in low-urgency situations that can then be used in high-urgency, life-and-death situations. This is exactly what the military does with wargames.

Reality vs Playability in Games

Let’s start by noting that there are two kinds of games:

• Entertainment games – games designed for having fun
• Serious games – games designed for learning real-world skills

Entertainment games are about having fun, not about learning real-world skills. And as a result, game design techniques used for entertainment games and for serious games differ in significant ways.

History is used as a theme for entertainment games, but serious games (such as wargames) seek to literally replicate and recreate history. So the data used in wargames for terrain, logistics, weapons capabilities, etc. needs to be as accurate as possible. These games must be accurate enough to help decision makers get an understanding of where and how future conflicts might develop, and help historians replicate and understand why past conflicts happened as they did.

The problem with entertainment games is that the skills learned by players are rarely transferable to the real world. For example, chess masters develop great skill in the game of chess, which allows them to perform to a higher level than novices. But these skills are not directly transferable to the real world. Studies show chess masters have superior memory and skill in chess, but chess masters have the same memory and skill capacity as chess novices in areas not related to chess.

This is why the use of realistic data and accurate models in educational simulations (serious games) is so important. It enables skills developed in those serious games to be transferable for use in the real world.

Applying Techniques from Wargames to a Supply Chain Game

SCM Globe is a serious supply chain game, and like wargames, it uses accurate data, and a map of the world as its game board. This is shown in the screenshots below. These screenshots show the model of an actual supply chain for a company that makes furniture in Indonesia and sells to customers around the world. This model was created by defining groups of four types of supply chain entities: 1) Products; 2) Facilities; 3) Vehicles; and 4) Routes. And then dragging and dropping the resulting entity icons to place them on a digital map in places where they actually are or where people want them to be.

(click on screenshots to see larger images)

SCM Globe leverages digital maps (like Google Maps, Apple Maps, Bing Maps, OpenStreetMap, etc.) to create its game board. Players are able to zoom in on the map and turn on the satellite view and place products, facilities, vehicles, and routes in exact locations on the map. The information used to define these entities accurately reflects the real world.

This placement of entity icons (products, facilities, vehicles, routes) creates a mathematically rigorous model of the supply chain, yet supply chain designers do not have to deal directly with the math or need a lot of training to quickly create accurate models. The supply chain models created by defining and placing the entities on the map are then run in simulations and people can see how well their supply chain designs work. They use simulations results to improve their designs and explore different options. The skills students learn in these simulations are directly transferable for use in the real world.

This use of models created by placing game pieces on a map, and realistic simulations that show performance of those models makes SCM Globe quite similar to wargames. Both use similar techniques to teach students real-world skills that they can use to effectively solve problems they will encounter in their jobs.

Manual Games versus Video Games

Philip Sabin is Professor Emeritus of Strategic Studies in the War Studies Department of King’s College, London UK. In his book, Simulating War, he explores using wargames as teaching tools, and he describes and shows examples of effective use of wargaming techniques.

Professor Sabin explains that “manual wargames”, games where you have to manually manipulate each piece on a game board, push students to understand the overall system that is created by all the individual pieces. They see how each piece relates to the other pieces on the board. The process of manually manipulating each piece requires a higher level of mental engagement than would be required if the pieces were automatically moved about by the game itself. This higher level of engagement is what focuses students’ minds and enables them to see the patterns and learn the skills needed to respond effectively.

Sabin explains that most video games used for entertainment hide the components that make them work because that makes for better entertainment. But this inaccesable “black box” game design doesn’t allow students to grasp the inner workings and operating logic of the game, so overall understanding is diminished compared to the depth of subject matter understanding developed by users of manual wargames.

Modeling and Simulation Enables Deliberate Practice

Like wargames, SCM Globe is composed of both modeling and simulation. The modeling part happens when players design their supply chains by creating the supply chain entities and placing them on the map. In this process players are exploring the map, defining products and demand, locating facilities, and creating vehicles and routes to move products between facilities to meet demand.

Once this is done, students click on the “Simulation” button, and the software runs the model in a simulation. It shows real-time readouts of cost and performance data for each of the facilities and vehicles. And it shows how long the supply chain will operate before a problem develops. When there is a problem, the simulation points out where the problem is and what caused it (for instance warehouse A ran out of product B) as shown below.

[ We are glad to provide free evaluation accounts to instructors, students and supply chain professionals — click here to Get Your Free Trial Demo ]

The benefit of combining modeling and simulation is that students can  easily create supply chain models by defining and locating products, facilities, vehicles and routes on a map. Then in simulations, they quickly find out how well their models work. Students can play “what if” games and test out different model designs. They change models, simulate the effect of those changes, and keep improving their models until they get the performance they want.

Design Thinking

One of the main reasons Professor Sabin and other wargame designers prefer using manual wargames instead of automated video wargames is because the ability to redesign the rules of the game encourages students to understand the details of how the game works. They see the results produced by different model designs. Whereas in automated video games students cannot rewrite the rules of the game because it would take an enormous amount of time, as well as require software skills that most students do not possess. So exploration of different operating models is restricted to only what is already programmed into the game.

SCM Globe provides the ability to change the rules and design new and unique supply chains models in the same way as manual wargames. People can start with any of the existing supply chain models from the SCM Globe library and change them by adding new entities or changing existing ones as they wish. They can also create completely new supply chain models from scratch, or model real supply chains such as their company’s supply chain or a competitor’s supply chain. Simulations then show the results of the design and operating decisions made in those models.

Because people can modify existing supply chain models and create and explore new ones, it gives them the opportunity to literally become skilled game designers, or more specifically, to become skilled supply chain designers.

NOTE: SCM Globe worked with the U.S. Air Force in 2024 and 2025 to develop an AI-assisted, multi-user, military collaboration platform called “Enterprise/X4SIM” for logistics training, supply chain design, operations planning, and real-time performance monitoring. The commercial version of this platform is now available for business use.

The folks at Fantastic organize what they call a “Massively Multiplayer Online Collaboration” to kick off their sales campaign. People attend online or in-person at Fantastic’s corporate office. There is a master of ceremonies from Fantastic who is acting as the event leader, but that mostly means facilitating a free flow of ideas and keeping people focused on the tasks at hand. If Fantastic can bring the manufacturers, distributors, and retailers it works with into a collaborative game of supply chain management then everyone in the supply chain has a chance to move a lot of product and make a lot of money.

Everyone logs onto the internet and accesses a collaboration platform called SCM Globe Enterprise. It provides a map of the world that is projected on the large screen at the front of the conference room for those present at Fantastic, and people online see it on their screens. All participants can follow along and talk to each other using voice, video and chat links. The map starts out showing the global reach of the Fantastic supply chain. Figure 1 shows a global view of Fantastic’s supply chain.

Figure 1. Global View of the Fantastic Corporation Supply Chain

The facilities of all the companies and routes between them are shown. By clicking on facilities people can see relevant information; by clicking on routes it shows the vehicles that travel on those routes and other relevant information. People use touch-screen controls to call up information. By tapping on countries or cities, they access specific market data. The map displays current sales by product category and sales trend lines over the last several years can also be shown with a further tap of the finger.

People can also make changes to the supply chain by adding or deleting products, facilities, vehicles, and delivery routes. And they can change production amounts at factories, delivery schedules for moving products between facilities, and product demand forecasts. As people make changes on their displays at Fantastic or elsewhere online, the changes are seen by everyone as they happen, and the session progresses.

Then three of the parts suppliers add in new factories their companies are building that can deliver more components for the Fantastic home entertainment system. More will be needed to support the increased manufacturing activity planned at Fantastic. Then a guy from the logistics company that supports stores on the east coast and the midwest adds in a new distribution center they are opening up and shows on the map how they could support additional store deliveries of the Fantastic product (this is illustrated in Figure 2a and 2b below).

Figure 2a. Satellite view of new Midwest Distribution Center

At that point some retailers say they are opening more stores and if they started stocking the Fantastic product then their demand forecasts would go up, so they enter higher demand numbers at a bunch of their stores. As the session progresses, this visibility and interaction makes it possible to get a good group consensus on amounts of product that can be sold and the amounts of component parts and distribution services needed to support this sales growth.

Figure 2b. New Distribution Center Supports Additional Stores

People run simulations on the supply chain configuration they have designed to see if it can handle the product volumes required to meet sales forecasts. The simulations run before everyone’s eyes and show where problems will crop up. Figure 3 shows results from one of the simulation runs. It shows inventory delivered to each of the stores, and then shows a red circle over the New York store and the Atlanta store indicating that with the existing delivery schedules and demand forecasts these stores will run out of inventory in a couple of weeks.

Figure 3. Simulation Results Showing Supply Chain Performance

As these problems come up in the simulations, people respond and make changes to the supply chain and rerun the simulations. After several iterations and some spirited discussions, a supply chain design and operating schedule is arrived at that delivers the needed performance levels at costs that are acceptable to all. Figure 4 shows some key performance indicators (KPIs) for participants.

Figure 4. Key Performance Indicators

This collaboration session harnessed several game dynamics, one of which is called “crowdsourcing”, to pool peoples’ ideas and arrive at a good supply chain design. Fantastic Company invited its supply chain partners to an open exchange of ideas and simulations to test the soundness of ideas and designs. The group arrived at a good solution and that solution also has the active support of all the relevant parties. So it is likely to be successful. Figure 5 shows a sample Profit & Loss report based on this supply chain plan.

Figure 5. Profit & Loss Report

Everyone participates in defining objectives and performance levels that need to be met, and those roles and rules for each company are set forth in their contracts with Fantastic. People at each company feel good about what they accomplished. And each party in this multiparty online game sees how they can make money, and maybe even have fun doing so.

Everything people need to continue working together is there online in the collaboration platform and information will be updated in real-time or near real-time as people start carrying out the activities they agreed to. This event would never be confused with that bane of corporate existence known as a “meeting”.

NOTE:
This event was what gamers would call a massively multiplayer online role playing game (MMORPG) – MMOG or MMO for short. They are a type of game that closely resembles business activities such as those described here. What can happen when we take game technology and its close cousin, social media, and apply these technologies to the way we do business?

What we mean by “stress‑testing”

Stress‑testing is different from classical planning or static network design. Planning assumes relatively stable (normal) conditions and seeks an optimal plan for a narrow set of constraints. Stress‑testing assumes uncertainty. We deliberately push the network (closing a supplier for three weeks, blocking a port for ten days, dropping a warehouse shift, or doubling the demand in a region) and we watch how the system behaves over time.

Instead of asking “What is the plan?”, we ask “What would break first, how fast would it break, and which counter‑measures buy us the most resilience per dollar?”.

Please note that stress-testing isn’t only about downside risk; it also exposes growth opportunities and readiness gaps. We simulate favorable shocks (tender wins, nearshoring lead-time gains, expansion, etc.), and measure how much extra volume the network can absorb before service, cost, or cash breaks. The model shows where to adjust cadence and inventory parameters to capture demand with minimal investment, and what incremental cost-to-serve to expect.

The same resilience lens that protects against downside quantifies the cheapest path to capture upside.

Explore the approach in detail in this free white paper.

Also, you can read this case study on “Managing Supply Chain Risk through Resiliency and Supplier Selection“.

How the SC Resilience Sprint works (week‑by‑week)

We start with a scoping session to agree on a limited but high‑impact perimeter: a product family, a region, a strategic customer segment, or a growth initiative you cannot afford to get wrong. Keeping the perimeter tight is what makes the two‑week cadence realistic and impactful.

During the first week, we assemble a baseline model. Using SCM Globe’s map‑based modeling, we place facilities, routes, and vehicles directly on a live map and load the minimum viable data needed to run a realistic simulation. We keep data light: basic data of only 4 entities which are products, facilities, vehicles, and routes. When data is missing, we work with ranges and document assumptions. The aim is not a perfect digital twin; it is a defensible baseline that behaves like your network does in the real world for thirty to ninety days of operations.

Next, we run the baseline and stabilize it. Many networks, when simulated from their current settings, cannot run reliably for an important period of time  without stockouts, stranded inventory, bottlenecks, or excessive cost. Before we talk disruption, we fix the basics.. This stabilization step alone often uncovers fast wins with measurable service and cost effects.

We then assemble and execute a library of disruption scenarios that reflect your actual exposure. We run each scenario for a realistic horizon, then capture how service, inventory, lead time, logistics costs, and cash behave.

The second week is about responses. For every high‑impact scenario, we test practical mitigation strategies and improvement options inside the model. Because scenarios are clones of the same baseline, we can compare options on equal footing and rank them by value, feasibility, and time to impact. By the end of the second week, we have a short list of actions that demonstrably change outcomes under stress.

Finally, we run a decision workshop. We present the few metrics that matter to executives and operators and we facilitate trade‑offs. The deliverable is a clear roadmap not just recommendations.

Why SCM Globe for this work

SCM Globe combines a simple, map-based modeler with a robust, time-based simulation engine and AI guidance. You build facilities, routes, and vehicles on a live map, clone scenarios in seconds, and the engine advances the network in time while enforcing capacities, calendars, and transport schedules. AI suggestions scan inputs and runs to spot missing or inconsistent parameters, highlight likely bottlenecks and late deliveries, and propose testable fixes such as delivery frequency changes, or order-quantity tweaks. Results merge the operational view (service, inventories, lead times, utilization) with finance and sustainability metrics (transport/facility costs and environmental KPIs). Collaboration is built‑in, so planners, logistics, and finance can iterate on the same model easily.

Just as important as the platform is the team using it. We’ve run similar projects across industrial companies and NGOs. SCM Globe tool is also used in classrooms and executive programs at top universities worldwide, and it’s been employed by the U.S. Air Force for logistics wargaming and mission planning.

Ready to start

If you have a critical flow you are worried about, a new market you are entering, or a plan you want to test before it becomes expensive to change, a resilience sprint is the fastest way to get answers you can trust. It’s very fast to run and the models start telling useful stories within days.

Start simple. Start today.

None of these make headlines, but these invisible inefficiencies compound daily, and together, they move service, cost, and cash in the right direction. A $100,000 annual saving can take just hours to implement, but a $2M system can take +18 months and may not move the needle. Let’s talk about small, real tweaks you can try in the next few weeks.

What Counts as a “Hidden Win”

A hidden win is:

• Simple to understand (you can explain it on one slide).
• Fast to trial (days or a couple of weeks, not a quarter).
• Directly measurable with a KPI you already track (OTIF, pick rate, transport cost per unit, etc.).
• Low political risk: doesn’t require restructuring or major capex.

These are simply changes that give your team confidence and free capacity for the bigger stuff. Use them as a continuous improvement engine: try, measure, keep or roll back.

The 10 Tweaks:

1) Re‑slot Fast Movers Closer to the Dock (or Pick Path)

What: Move your fastest-moving SKUs to the most accessible locations. 

Why it works: Shorter travel means fewer touches and less picker fatigue. This is one of the most repeatable warehouse wins. 

How to try: Pull last 90 days’ picks (or more), rank by lines picked, relocate the very top SKUs during a low-volume shift. Measure picks per labor hour before/after.

2) Split Safety Stock Policies by ABC Class

What: Apply different service targets and formulas to A, B, and C items instead of using a single rule.

Why: A-items drive revenue/service risk; C-items tie up cash if overstocked.

How: Classify SKUs by volume or margin; set higher service targets (or coverage targets) for A, lower for C. Pilot on one product family; monitor stockouts and inventory value.

3) Dynamic Reorder Points During Promotions or Season Peaks

What: Temporarily adjust reorder points instead of letting standard settings trigger Purchase orders (PO). 

Why: Promo/seasonal spikes and intermittent demand aren’t “normal demand”; treating them as such leads to either stockouts or bloated inventory afterward. 

How: Using historical demand data, run a simulation with fixed and dynamic reorder points, then observe the impact on inventory value and service level. If the gains are significant, work on making the reorder point calculation dynamic.

4) Consolidate LTL Shipments into Planned Milk Runs

What: Replace multiple ad hoc LTL shipments with a scheduled route hitting several customers or DCs.

Why: You pay less per unit shipped and gain schedule predictability. 

How: Map typical weekly drops, see which can ride together on a set day/route. Start with one lane. Track cost per pallet and on-time delivery.

5) SKU Rationalization Based on Margin and Velocity (Not Just Sales)

What: Review the tail of your assortment and drop/merge SKUs that drain resources. 

Why: Low-volume, low-margin items create disproportionate planning, purchasing, and handling effort.

How: Build a simple 2×2 (velocity vs. margin). Flag bottom-left quadrant. In your planning sheet, tag 2-3 candidate SKUs “watch list” and:

• simulate (or calculate) what happens if you buy only every X weeks or switch them to make-to-order.
• offer substitutes
• change the service model
• pilot in one channel/region: Apply the new rule only in a low-risk geography or e‑commerce channel. Track fill rate, backorders, and complaint tickets.
• decide with data: If complaints/backorders stay near zero and operations effort drops, retire the SKU after communicating with sales.

6) Add a “What If?” Column to S&OP Review Sheet

What: Force one line in the deck/spreadsheet where someone states a scenario and the immediate response.

Why: It institutionalizes proactive thinking without a complicated, time-consuming, risk process. 

How: Next meeting, ask: “What if demand is +20% in Q4?” Capture a one-sentence response and owner. Track if actions were taken.

7) Standardize Master Data Naming and Units Before the Next Project

What: Clean up inconsistent SKU names, units of measure, and supplier codes. 

Why: Dirty master data quietly wrecks planning runs and causes manual workarounds. 

How: Pick one data field (e.g., UOM). Define the standard, run a batch clean, and then lock the rule.

8) Cross‑Train One Extra Person at Every Critical Node

What: Ensure at least one backup operator/planner for each key role or process. 

Why: Absences or turnover cause immediate bottlenecks; cross-training smooths the load. 

How: This month, identify the “single points of human failure”. Schedule shadow days. Use a simple checklist to sign off competence.

9) Get (and Track) PO Acknowledgements

What: Require your key suppliers to confirm every PO quantity, price, and a realistic ship/delivery date with a deadline, then track two simple KPIs: Ack Rate (% of POs confirmed on time) and Ack Cycle Time (hours from send to confirm).

Why: A PO is just a request; until the supplier acknowledges it, you don’t truly have a commitment. Missed acknowledgements are a common root cause of late receipts and surprise changes. 

How: Add three columns to your PO log (Ack received? Y/N, Ack timestamp, Committed date). Follow up just after the deadline. Review the non-responsive suppliers regularly and use this data as a support for discussion with them.

10) Simulate Before Approving Any Network Change

What: Quickly clone your current network in a simulation tool (like SCM Globe), tweak one variable, compare KPIs. 

Why: You catch unintended consequences early and learn faster. 

How: Set a rule: any routing, facility, demand, or policy change over a defined threshold gets a quick simulation review. Document the delta vs. baseline.

Final Thoughts

Hidden wins are everywhere. Pick three, try them, measure, repeat. If you’ve got a favorite tweak that saved your quarter, share it, we’ll compile the best ones.

If you need a simulation tool to test supply chain improvement ideas safely, you know where to find us.