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During the last decade, a cascading series of unpredictable events—including earthquakes, volcanic eruptions, catastrophic storms, disease outbreaks and armed conflicts—has exposed deep fragilities in global supply chains. These events served as initial alarm bells for much greater challenges to come.

Intricately woven supply chains were built on concepts such as just-in-time manufacturing and designed to reduce labor and operating costs. Over the years, companies relentlessly optimized their supply chains to serve markets with relatively predictable supply and demand patterns. However, recent and unprecedented events have shown how these choices have created inflexible supply chains that are brittle under stress.

Breaking a single link in a globalized supply chain can have a ripple effect, impacting customers thousands of miles away from the point of disruption. “Supply chain issues” has become a catchphrase for economic dislocation.

“In recent years, supply chain has gone from the background, something people did not think about, to a boardroom-level topic,” says Rob Cushman, Senior Partner, IBM Supply Chain Transformation. “It’s a concept that people have had very painful personal experiences with. And that’s why thinking about supply chain is pivoting from cost to being about resilience and agility, and ultimately driving growth.”

Cost savings

By deploying a cognitive supply chain, IBM reduced supply chain costs by USD 160 million   and built in more resilience and agility

100% order fulfillment 

Even during the peak of the covid-19 pandemic, IBM maintained a 100% order fulfillment rate of its products to clients

The worldwide reach, size and complexity of its supply chain organization represented a significant challenge as IBM began exploring transformation strategies for delivering a differentiated customer experience to promote customer loyalty and growth. IBM employs supply chain staff in 40 countries and makes hundreds of thousands of customer deliveries and service calls in over 170 nations. IBM also collaborates with hundreds of suppliers across its multi-tier global network to build highly configurable and customized products to customer specifications.

Previously, the IBM supply chain ran on legacy systems spread across different organizational silos, making information sharing slow and incomplete. Employees also performed much of their work on spreadsheets, which impeded collaboration and real-time data transparency.

However, at the same time the IBM supply chain was re-thinking business processes and transforming its technology platforms, IBM was making major strides in AI, cloud, data fabric, IoT, edge computing and other tools. “We saw the advances IBM was making in all these new technologies,” says Ron Castro, Vice President of IBM Supply Chain. “So, we asked, ‘Why not leverage our own technology to move our own supply chain forward?’”

“The principle behind why we embarked on this journey was to answer the question, ‘How can we best react to disruptions to manage resiliency and our client experience?’” says Castro. “We needed to identify disruptions quickly, analyze the data, get insights and decide on the best course of action.”

IBM supply chain management set out a bold vision to build its first cognitive supply chain. The aim was to have an agile supply chain that extensively uses data and AI to lower costs, exceed customer expectations, ruthlessly eliminate or automate non-value add work and exponentially improve the experience of supply chain colleagues.

IBM Consulting® was brought in at the beginning to help develop the processes required to drive the transformation. “We consider ourselves ‘Client Zero’ for IBM Consulting,” says Debbie Powell, IBM Digital Supply Chain Transformation Leader. “We have the technology to do what we need to do. It’s the culture and the processes where change was needed. We also realized that a lot of our knowledge was tribal and often depended on one person. We needed to digitize and democratize knowledge to support decision-making throughout the organization.”

IBM Consulting helped the IBM supply chain team use Design Thinking methods to plan its digital transformation and move from sequential to continuous planning. “We put a lot of effort into agility and a cultural shift to empower people and adjust workflows in a controlled way,” says Matthias Gräfe, Director of IBM Supply Chain Transformation. “We went from a top-down approach to identifying personas from the bottom up, the people that actually make the decisions.”

“Successful digital transformation required us to challenge traditional ways of working that were held sacred for decades and win the hearts and minds of supply chain colleagues for change to stick,” says Takshay Aggarwal, Partner, IBM Supply Chain Transformation.

At a high level, the IBM supply chain digital transformation revolves around building sense-and-respond capabilities. This was accomplished by democratizing data and automating and augmenting decisions achieved by combining cognitive control tower, cognitive advisor, demand-supply planning and risk-resilience solutions. “We view the cognitive control tower as the single source of truth where you have access to all the data and it helps advise the best course of action,” says Castro. “It also helps gather insights from the information quickly across the end-to-end supply chain.”

The cognitive control tower is powered by the  IBM® Cognitive Supply Chain Advisor 360  Solution, which runs on  IBM Hybrid Cloud  and on  Red Hat® OpenShift®  (link resides outside of ibm.com) software. Cognitive Advisor 360 enables real-time, intelligent supply chain visibility and transparency. It also senses and responds to changes in demand as they happen and simplifies the automation of supplier management.

The system uses IBM Watson® technology to enable natural language queries and responses, which accelerates the speed of decision-making and offers more options to correct issues. “I can ask—in natural language—about part shortages, order impacts, risks to revenues and trade-offs,” says Cushman. “There’s a button that recommends actions to solve issues — that’s what Watson does. It’s augmented intelligence so we empower people with better information to make data-driven decisions very quickly.”

“With the cognitive supply chain, we have the benefit of bringing in all these data from legacy systems and internal and external sources, as well as unstructured data, to apply advanced analytics and different elements of AI,” says Castro. “And since the system responds to natural language, think about the power of being able to extract data and get insights and recommendations without having to be an expert in a legacy system or an ERP platform.”

The IBM cognitive supply chain technology architecture also includes  IBM Edge Application Manager ,  IBM Maximo® Visual Inspection  and  IBM Track and Trace IoT —an integrated stack of solutions that connect data end-to-end across the supply chain. “Our procurement, planning, manufacturing and logistics data are connecting in close to real time,” says Cushman. “That’s how we can share inbound information from suppliers, manufacturing status updates with our external manufacturing partners and delivery information with our customers.”

“We’ve added demand sensing, so that the solution pulses the market for changes in demand, predicting the future. We’ve also embedded a cloud-based risk management tool called Resilinc into our procurement and inbound parts management process,” says Cushman. “It essentially uses AI to crawl the web and if there is a disruption, we can take action quickly to secure a second supply source.”

On a minute-by-minute basis, one of the biggest advantages of IBM’s cognitive supply chain is that it provides employees with immediate access to the information they need to read and mitigate disruptions. “There is unbelievable power that comes from taking lots of disparate data and putting it where people can see and understand it,” says Cushman.

“The real-time, single-view of the truth increases the velocity of decisions and leverages rapid response,” says Castro. “It helps us develop ‘what-if’ scenario analysis from a planning perspective all the way through to the execution team and suppliers.”

In fast-moving, real-world situations, quick, informed decisions provide a competitive advantage. “In the past, a major disruption—such as the closing of a major airport—would take days for us to understand the immediate impacts. With our current solution, we have ‘what-if’ capability that brings this analysis down to minutes,” says Powell. “In a supply constrained environment, whoever gets the information first wins.”

Since its cognitive supply chain became operational, IBM has saved USD 160 million related to reduced inventory costs, optimized shipping costs, better decision-making and time savings. “When mitigating a part shortage, it used to take four to six hours per part number,” says Powell. “We’ve brought that down to minutes and made further improvements to seconds.”

“Where’s my stuff?” is a common question in the supply chain industry. Finding an answer can entail hours of phone calls, emails and ERP queries across different geographies. “We’ve built a solution where you can log in and enter an order and you’ll have an answer in about 17 seconds,” says Cushman. “That was an enormous pivot and a powerful change in how we do business.”

By using its cognitive supply chain platform, the IBM supply chain team is also able to create new capabilities much faster. “Years ago, when we started this journey, we needed a long, looping roadmap with one or two years required for major capability upgrades,” says Castro. “With this digital enterprise, we now have teams that complete deployments in two or three weeks. We’ve moved to much more agile development.”

Despite dislocations caused by the COVID-19 pandemic, IBM fulfilled 100% of its orders by using its cognitive supply chain to quickly re-source and re-route parts as necessary. “During the last two years, the IBM supply chain did not fall behind. We met our commitments. Everyone else was screaming supply chain issues and we’re shipping products,” says Daniel Thomas, IBM Business Optimization Manager and Chief of Staff. “We delivered on our promises during the height of the disruptive era we live in.”

“Guaranteed supply is important, but many of our clients are also looking for predictability of supply,” says Castro. “The tools we have now help us address both issues. They enable us to manage the demand side to meet the right client expectations.”

“We have a responsibility to inspire younger supply chain leaders who will keep the IBM supply chain at the cutting edge and beyond for years to come,” says Aggarwal. “People entering the work force today have different experiences than previous generations. They are digital natives and expect a consumer-grade experience when managing their work. As we embarked on our journey, we actively engaged them in designing workflows and digital capabilities. There were trials and tribulations and we had multiple failures in design and rollout. Architecting the cognitive supply chain, and learning from failures and successes, made our young leaders champions of the cognitive supply chain and constant innovators of new capabilities.”

“IBM is the only global services company with its own multibillion-dollar supply chain, and we’ve transformed it into a data-driven architecture to drive our business. There’s a richness of experience that we bring to client conversations because we’ve done this work for ourselves,” says Cushman. “It’s all about how a supply chain delivers a differentiated customer experience to enable stickiness and growth.”

“The collaboration between IBM Systems and IBM Consulting teams to transform our own business and demonstrate the power of exponential technologies in supply chain has been one of our finest moments as a company,” says Cushman. “We look forward to sharing our real-world experience and learnings with our worldwide community of customers, partners and clients.”

IBM is an information technology company based in Armonk, New York. Founded in 1911, the company offers hardware, software and services in cloud computing, AI, commerce, data and analytics, IoT, mobile and cybersecurity, as well as business resiliency, strategy and design solutions. IBM has a global workforce of more than 280,000 employees serving clients in over 175 countries through IBM Consulting, IBM Software and IBM Infrastructure.

To learn more about the IBM solutions featured in this story, please contact your IBM representative or IBM Business Partner.

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By Supplychainopz

Professionals in supply chain management use various methods to determine how to improve the performance of supply chain operations. Analysis of case study is certainly one of the most popular methods for people from business management background. In order to accelerate the learning, this article has gathered 20+ most sought-after supply chain case studies, analyzed/categorized them by industry and the findings are presented.

Boeing wants to encourage more flight frequency and direct route using a smaller capacity aircraft. Then they decide to outsource many things such as the design, testing and production of key components to key industrial partners and try to reduce number of components that go to assembly. The ultimate goal is to finish the final production process within 3 days. Airbus takes a bit different marketing approach. They want to utilize high capacity airplane to help airlines drive the operating cost down. They decide to selectively outsource the production of parts and keep the design and production of key components in-house.

Supply Chain of fashion industry involves a time based competition. Many customers have the unique product needs but a competition is very fierce because of the low barriers of entry. Many new players try to offer specialized products to customers all the time. This section features the supply chain case studies of H&M, Benetton, Zara and Adidas. –  H&M  aims to be the price leader in the fashion market.In order to materialize its vision, H&M tries to eliminate the middlemen in various stages of supply chain and consolidate the buying volumes. Product design is also the central part of its strategies. They don’t try to follow the high fashion designs but try to adopt the street trends which are easier to produce. At the end of the day, they can bring products to market within 2-3 weeks. –  Benetton , in contrast, chooses to have a full control of its production but allow its licensees to operate the stores so they can focus on production and quality control. The reason is that they would like to create the worldwide brand awareness. For fast moving products, they use the production facilities in Europe. Asian suppliers will perform production for standardized products. –  Zara  is very famous for its time based strategy. In order to launch a new product within 15 days, Zara uses a small lot production. A new product will be tested in pilot stores. If product sales is good, a larger batch will be ordered. Otherwise, remaining products will be removed from the shelves and sold as mark-down in other stores. This creates the perception among consumers that Zara’s products are unique and you have to take it while stock lasts. Vertical integration contributes to the success of Zara, they own the majority of its production facilities and stores (this is the reason why Quick Response can be effectively implemented). Its automated distribution centers are strategically located between the center of populations so products are delivered to stores quickly. Zara also works with Air France, KLM Cargo and Emirates Air in order that they can coordinate directly with the airlines to make the outbound shipments to its stores and bring back some raw materials and semi-finished materials with return legs. The last supply chain case study in the fashion retailing industry is  Adidas . In order to cope with changing customers’ demand, they decide to undertake Mass Customization strategy. The whole idea is to develop, market and deliver the product variety that most customers will find what they want. The first steps towards mass customization is to strategically offer the product choices. Too few variations will disappoint a customer but too many variations will simply postpone a buying decision. After that, Adidas asks the same key suppliers to produce custom components in order to achieve the economy of scale. In order to compensate a long waiting time, Adidas uses air freight or courier service. The reason why they can do this is that customized products are sold directly to customers so they have the higher profit margin to compensate the higher transportation cost. Supply chain strategy of the fashion retailing industry is summarized as below,

FMCG industry is typically the products sold to customers at a low cost and will be completely consumed within 1 year. The nature of this industry is the short product life cycle, low profit margin, high competition and demand fluctuation. This section will present the case studies of P&G, Unilever and Coca-Cola respectively. Forecasting and new product introduction has always been the issues for many FMCG companies,  P&G  is no exception. To cope with this, P&G conducts a merchandise testing at the pilot stores to determine the customer’s response to new product before the launch. The result is that the forecast accuracy is improved because a demand planner has an additional source data to make a better decision. Moreover, products can be shipped to stores in-time then lost sales is minimal. –  Unilever  also feels that the competition in FMCG industry has significantly increased. They have to launch the new products on regular basis but the forecasting of new product is difficult. So they create a better classification of new products (base, relaunch, repack, new) using a regression model to identify potential forecast errors for each type of new product. –  Coca-Cola  doesn’t really have many stock keep units when compared with other companies in the same industry. However, products go to over 2.4 million delivery points through over 430 distribution centers. Managing transportation at this scale is the absolute challenge. In order to streamline the delivery, Coca-Cola implemented a vehicle routing software. The reason is that is the software vendor has a very good relationship with Coca-Cola’s legacy ERP software vendor. Moreover, the vendor has a solid connection with the university who can help to develop the algorithm that fits in with the business’ needs. The result is that transportation planners at each distribution center can use the new tool to reduce travelling time/distance on daily basis.

Lean manufacturing concept has been implemented widely in the automotive industry so the case studies about lean manufacturing is very readily available. Due to the increasing competition in the automobile industry, car manufacturers have to launch a new model to the market more frequently. This section will show you how BMW manages a long term planning, how Ford applies lean concept to the new product development and how Hyundai manages the production planning and control. –  BMW  uses a 12-year planning horizon and divides it into an annual period. After that, they will make an annual sales forecast for the whole planning horizon. After the demand is obtained, they divide sales into 8 market and then select the appropriate production sites for each market, considering overall capacity constraints and total cost. As you may notice, this kind of a long range planning has to be done strategically. –  Ford  calls its product development system as “work streams” which include the body development, engine development, prototyping and launch process . The cross-functional team are the experts and their roles are to identify key processes, people, technology necessary for the development of new prototype. Each work stream team is responsible to develop timeline of each process. Detailed plan is usually presented on A3 sized paper. They clearly identifying current issues they are facing with supporting data, drawings and pictures. On weekly basis, they organize a big group meeting of all work stream team to discuss the coordination issues. –  Hyundai  deploys a centralized planning system covering both production and sales activities across the facilities and functional areas. They develop a 6-month master production plan and a weekly and a daily production schedule for each month in advance. During a short term planning (less than one month), they pay much attention to the coordination between purchasing, production and sales. Providing a long term planning data to its suppliers help to stabilize production of its part makers a lot.

Life cycle of technology products is getting shorter and shorter every day. Unlike FMCG, the launch of a new product in the hi-tech industry requires the investment in research and development quite extensively. Then, a poor planning will result in a massive loss. This section will cover JIT and outsourcing by Apple Inc, Supply Chain Risk Management by Cisco System, Technology Roadmap by Intel, Supply Chain Network Model by HP, Mass Customization by Dell and Quality Management by Sam Sung. Steve Jobs invited the Tim Cook to help to improve  Apple’s Supply Chain  in 1998. Jobs told Cook that he visited many manufacturing companies in Japan and he would like Cook to implement the JIT system for Apple. Jobs believed that Apple’ supply chain was too complex then both of them reduced the number of product availability and created 4 products segment, reduced on hand inventory and moved the assembling activities to Asia so they could focus on developing the breathtaking products that people wanted to buy. –  Cisco Systems  would like to be the brand of customer choice so they implement a very comprehensive supply chain risk management program by applying basic risk mitigation strategies, establishing appropriate metrics, monitoring potential supply chain disruptions on 24/7 basis and activate an incident management team when the level of disruption is significant. –  Intel ‘s new product development is done by the process called Technology Roadmap. Basically, it’s the shared expectations among Intel, its customers and suppliers for the future product lineup. The first step to prepare the roadmap is to identify the expectations among semiconductor companies and suppliers. Then they identify key technological requirements needed to fulfill the expectations. The final step is to propose the plan to a final meeting to discuss about the feasibility of project. Some concerning parties such as downstream firms may try to alter some aspects of the roadmap. Technology Roadmap allows Intel to share its vision to its ecosystem and to utilize new technology from its suppliers. –  HP ‘s case study is pretty unique. They face with a basic question, where to produce, localize and distribute products. Its simple supply chain network model is presented below,

From this example, only 3 possible locations result in 5 different way to design the supply chain. In reality, HP has more production facilities than the example above so there are so many scenarios to work with. How should HP decide which kind of a supply chain network configuration they should take to reduce cost and increase service to customer? The answer is that they use the multi-echelon inventory model to solve the problem. –  Dell  is one of the classic supply chain case studies of all time. Many industries try to imitate Dell’s success. The key ingredients of Dell’s supply chain are the partnership with suppliers, part modularity, vendor managed inventory program, demand management and mass customization. Also, you can find the simplified process map of Dell’s order-to-cash process as below,

–  Sam Sung  has proven to be the force to be reckoned with in the hi-tech industry. The secret behind its supply chain success is the use of Six Sigma approach. They studied how General Electric (GE), DuPont and Honeywell implemented six sigma. After that, they have created their own implementation methodology called DMAEV (define, measure, analyze, enable, verify). They use the global level KPI to ensure that each player in the same supply chain is measured the same way. Also, they utilize SCOR Model as the standard process. Any process changes will be reflected through an advance planning system (APS).

The last industry covered here is the general merchandise retailing industry. The critical success factor of this industry is to understand the drivers of consumer demand. Four case studies will be presented, namely, 7-11, Tesco, Walmart, Amazon and Zappos. –  7/11  is another popular case study in supply chain management. The integration of information technology between stores and its distribution centers play the important role. Since the size of 7/11 store is pretty small, it’s crucial that a store manager knows what kind of products should be displayed on shelves to maximize the revenue. This is achieved through the monitoring of sales data every morning. Sales data enables the company to create the right product mix and the new products on regular basis. 7/11 also uses something called combined delivery system aka cross docking. The products are categorized by the temperature (frozen, chilled, room temperature and warm foods). Each truck routes to multiple stores during off-peak time to avoid the traffic congestion and reduce the problems with loading/unloading at stores. –  Tesco  is one of the prominent retail stores  in Europe. Since UK is relatively small when compared with the United States, centralized control of distribution operations and warehouse makes it easier to manage. They use the bigger trucks (with special compartments for multi-temperature products) and make a less frequent delivery to reduce transportation cost. Definitely, they use a computerized systems and electronic data interchange to connect the stores and the central processing system. –  Wal-Mart ‘s “Every Day Low Prices” is the strategy mentioned in many textbooks. The idea is to try not to make the promotions that make the demand plunges and surges aka bullwhip effect. Wal-Mart has less than 100 distribution centers in total and each one serves a particular market. To make a decision about new DC location, Walmart uses 2 main factors, namely, the demand in the proposed DC area and the outbound logistics cost from DC to stores. Cost of inbound logistics is not taken into account. There are 3 types of the replenishment process in Wal-Mart supply chain network as below,

In contrary to general belief, Wal-mart doesn’t use cross-docking that often. About 20% of orders are direct-to-store (for example, dog food products). Another 80% of orders are handled by both warehouse and cross dock system. Wal-Mart has one of the largest private fleet in the United States. The delivery is made 50% by common carriers and 50% by private fleet. Private fleet is used to perform the backhauls (picks up cargoes from vendors to replenish DCs + sends returned products to vendors). Short-hauls (less than one working day drive) is also done by the a private fleet. For long-hauls, the common carriers will be used. There are 2 main information system deployed by Wal-Mart. “Retail Link” is the communication system developed in-house to store data, share data and help with the shipment routing assignments. Another system is called “Inforem” for the automation of a replenishment process. Inforem was originally developed by IBM and has been modified extensively by Wal-Mart. Inforem uses various factors such as POS data, current stock level and so on to suggest the order quantity many times a week. Level of collaboration between Wal-Mart and vendors is different from one vendor to the other. Some vendors can participate in VMI program but the level of information sharing is also different. VMI program at Wal-Mart is not 100% on consignment basis. –  Amazon  has a very grand business strategy to “ offer customers low prices, convenience, and a wide selection of merchandise “. Due to the lack of actual store front, the locations of warehouse facilities are strategically important to the company. Amazon makes a facility locations decision based on the distance to demand areas and tax implications. With 170 million items of physical products in the virtual stores, the back end of order processing and fulfillment is a bit complicated. Anyway, a simplified version of the order-to-cash process are illustrated as below,

Upon receipt of the orders, Amazon assign the orders to an appropriate DC with the lowest outbound logistics cost. In Amazon’s warehouse, there are 5 types of storage areas. Library Prime Storage is the area dedicated for book/magazine. Case Flow Prime Storage is for the products with a broken case and high demand. Pallet Prime Storage is for the products with a full case and high demand. Random Storage is for the smaller items with a moderate demand and Reserve Storage will be used for the low demand/irregular shaped products. Amazon uses an propitiatory warehouse management system to make the putaway decision and order picking decision. After the orders are picked and packed, Amazon ships the orders using common carriers so they can obtain the economy of scale. Orders will arrive at UPS facility near a delivery point and UPS will perform the last mile delivery to customers. Amazon is known to use Sales and Operations Planning (S&OP) to handle the sales forecast. Anyway, this must be S&OP process at product family/category level. To compete with other online retailers,  Zappos  pays much attention to the way they provide the services to customers. In stead of focusing on the call center productivity, Zappos encourages its staff to spend times over the phone with customers as long as they can so they can fully understand the customer’s requirements. They also upgrade the delivery from 3 days to 1 day delivery in order to exceed customer expectation.

All case study demonstrates that supply chain management is truly the strategic initiatives, not merely a cost cutting technique. Leading companies have a very strong customer focus because almost all of initiatives are something to fill the needs of customers. Relationship management is the unsung hero in supply chain management. It’s the prerequisite to the success of every supply chain. And at the end of the day, it comes down to the quality of supply chain people who analyze, improve and control supply chain operations. – See more at: http://www.supplychainopz.com/2014/04/supply-chain-management-case-study.html#sthash.MrnrGsyY.dpuf

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Supply Chain Management Design & Simulation Online

Supply Chain Case Studies

SCM Globe comes with a library of case studies that explore COMMERCIAL , HUMANITARIAN , and MILITARY supply chains. When you purchase an account you have access to all the case studies and their simulations.

The case studies range from relatively simple beginning cases like Cincinnati Seasonings , to quite challenging advanced cases such as Zara Clothing Company , or Nepal Earthquake Disaster Response .  Case studies are laboratories where you apply what you learn in lectures and readings to solve supply chain problems in highly realistic simulations. Each case has a " CASE STUDY CONCEPT " showing the supply chain principles and practices highlighted in that case.

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Case studies presently available in the online library are shown below. You are welcome to use any or all of them. You can also create your own case studies, or we can create them for you. Cases are shown in the three categories. As you work with these cases you will gain an intuitive understanding of supply chain dynamics, and develop the analytical skills for designing and managing real supply chains.

People new to SCM Globe should start with the  Cincinnati Seasonings case study . Work individually at first, not in groups. Each person needs their own account. Do the three challenges shown in the online introduction to Cincinnati Seasonings. That's how you'll learn to use the software, and how to use simulations to analyze and design supply chains. Then you will be ready to work in groups or work on more advanced cases.  Click on the case studies below to see a description and introduction to each case.

Commercial Supply Chain Case Studies

Collaborative Supply Chains

S&J Trading Company – Angola

Java Furniture Company – Indonesia

Cincinnati Seasonings

Supply Chains of the Roman Empire

Ancient Silk Road – First Global Supply Chain

Zara Clothing Company Supply Chain

Fantastic Corporation – Global Supply Chain

Fantastic Corporation – Unexpected Disruptions

Humanitarian supply chain case studies.

Disaster Response Supply Chains: Flooding Scenario

Nepal Earthquake Disaster Response Supply Chain

Humanitarian Supply Chains: Syria Evacuation Scenario (CIV and MIL)

Military supply chain case studies.

Burma Campaign – 1944 Invasion of India

Battle of Smolensk – 1941 Invasion of Russia

Alexander the Great Needed Great Supply Chains

New case studies.

New cases are added based on projects we do with instructors, students, and supply chain professionals. Here are the new supply chain models in the library:

• Local and Sustainable Supply Chains – Blue Ocean Cooperative
• Aerospace Manufacturing Cluster – Rockford IL
• Hyderabadi Biryani – Paramount Restaurant 
• Western Desert War – May 1941
• Russian Logistics for the Invasion of Ukraine

Interactive Supply Chain Case Studies

Every case study has a main theme or concept that it illustrates. You will be challenged to use knowledge acquired in lectures and readings as well as your own real-world experience to expand and re-design the supply chains in these case studies.

In the commercial supply chain cases you need to improve and expand the supply chains to support new stores and still keep operating costs and inventory as low as possible. In cases that deal with humanitarian or military missions you need to create supply chains to deliver the right supplies to the right locations when they are needed, and do so at a reasonable cost.

We are glad to provide a  free evaluation account  to instructors, students and supply chain professionals interested in exploring SCM Globe simulations — click here to request an account —  Get Your Free Trial Demo  

See SCM Globe pricing for Academic and Business versions of the software.

The best case to start with is Cincinnati Seasonings . After working through the three challenges presented in the online introduction to this case you will be ready to handle further challenges in this case or move on to more advanced cases. Get a quick introduction to working with case studies in “ Working with Case Studies “.

As problems are found in the simulations, you make decisions about how to fix them. Make changes to your supply chain model in the Edit screen. Then go to the Simulate screen and run a simulation to see the results of your changes. Depending on the changes you make, your supply chain simulation runs for additional days and other problems arise. As you address these problems you see about how supply chains work. Apply what you learn in readings and and lectures plus your work experience to solve the problems you encounter.

Keep improving your supply chain model until you get the simulation to run for 30+ days. Then download your simulation results and create a monthly Profit & Loss Report plus KPIs (as shown below). This provides an objective basis for evaluating the merits of different supply chain solutions.

Monthly Profit & Loss Reports identify areas for improvement. They help you improve your supply chain to keep it running for 30 days and also lower operating costs and inventory levels. You can work on lowering the carbon footprint of your supply chain too. These are the challenges you address in SCM Globe, and they are the same challenges people face when managing real supply chains. What works well in the simulations will also work well with actual supply chains. Skills you develop in working with the simulations are directly transferable to the real world.

NOTE: You can run simulations for longer than 30 – 60 days, but there is usually no reason to do so. This is because most companies do not run their supply chains unchanged for longer than 30 days at a time. They use a 30 day S&OP ( sales and operations planning ) cycle and these simulations correspond to that monthly S&OP cycle. These simulations focus on the tactical realities of operating a supply chain from one month to the next, and finding what works best.

Accessing the Online Library of Case Studies

As shown in the screenshots below, logon to your account and access the case study library from your Account Management screen. Click on the “View Library” button (arrow 1) in upper right corner of the Account Management screen. In the Library screen you see a list of available supply chain case studies; click “ Import ” to load a selected case study into your account; give the imported case a Name , and click “ My Account ” to go back to your Account Management screen.

You are welcome to import any or as many of the supply chain models in the library as you wish. Once you have a copy of a supply chain model in your own account you can make any changes you want to it.

In Account Management, you “ Create a New Supply Chain ” or work with an existing supply chain by clicking the “ Edit ” button (arrow 2) next to the existing supply chain you want to work on. You can also upload copies of supply chain models sent to you by other SCM Globe users (arrow 3) , and check your account expiration date (arrow 4) .

Use the Default Values or Enter New Data

When you load any of the case study supply chain models from the SCM Globe library, they come with default numbers already plugged in. You can either accept the defaults or do some research to find more current data. This data (like data and prices everywhere) changes all the time.

Look for data on products, facilities and vehicles that are used in your supply chain and see what their specifications and costs are. Costs can vary widely in different parts of the world. Go to websites of commercial real estate brokers in cities of interest and see what you can find out about rent costs:

• for cities in North America start with www.cityfeet.com
• and for cities in other parts of the world start with  www.knightfrank.com

Metric System of Weights and Measures

In the case studies all weights, volumes, distances and speeds are expressed using the metric system. The metric system is used around the world in every country except three: Liberia; Myanmar; and the United States. So it is good for supply chain professionals to feel comfortable with the metric system.

Register on SCM Globe for Access to all Supply Chain Simulations

Click the blue "Register" button on the app login page, and buy an account with a credit card or PayPal (unless you already have one). Then scan the "Getting Started" section, and you are ready to start. Go to the SCM Globe library and click "Import" next to the supply chain models you want.

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Creating an omnichannel supply chain: a macy’s case study.

In February 2020, Macy’s announced their Polaris plan , a three-year strategy created to stabilize profits and create growth. This plan included closing 125 underperforming stores and consolidating offices. It also included a major overhaul of their supply chain model.

But, of course, Macy’s had to close their doors less than 6 weeks later due to COVID-19. As their online presence was the only presence available, their longstanding supply chain strategy, which was already starting to cause major issues within the company, needed immediate attention.

Macy’s CEO Jeff Gennette stated in September 2020, “Everything on the digital agenda has been accelerated. We’re optimizing inventory placement to meet customer demand wherever and however they shop in our store.”

What’s so bad about Macy’s supply chain model?

Customers expect a strong omnichannel experience — one that integrates both the online and offline world of the retailer, enabling a frictionless shopping experience.

For retailers, the goal is to take the retailer’s replenishment cycle from days to hours and reduce inventory at stores. This way, retailers expand their use of stores to fulfil online orders and hold less inventory altogether, allowing them to dedicate more room for digital fulfillment.

Omnichannel shopping is the baseline expectation for customers, as companies such as Gap, Target, and many others have upped their omnichannel game.

And Macy’s is, er, behind.

Macy’s way of viewing their supply chain in the past was traditional: Move products from point A to point B and optimize costs at each stop along the way. Each delivery channel has its own transportation plan and technology stack, siloing all distribution and fulfillment centers.

This supply chain method was acceptable 10 years ago, but to stay afloat in the in-store and online retail spaces, Macy’s needed to make a change. Silos created major cost issues, not to mention slow speed and service in today’s two-day-delivery age.

The company’s supply chain model operated two separate warehouse networks, one for stores and the other for direct customer (online) orders. This system made rebalancing inventory nearly impossible, among other issues.

Macy’s supply chain also lacked a central platform for locating inventory at the SKU level across the chain, and the cost of goods were high compared to competitors since each private brand sold at May’s was sourced independently.

Creating a better supply chain

In 2019 Macy’s hired Dennis Mullahy , the first ever Chief Supply Chain Officer, to transform the supply chain into one that supports an omnichannel strategy.

Since then, Macy’s has made leaps and bounds in optimizing their supply flow, with COVID expediting the process.

The company is transitioning to a centralized warehouse model, implementing a flow and fold design, meaning a light initial allocation to stores and flexible replenishments. Multipurpose warehouses hold inventory, which can both replenish stores and fulfill e-commerce orders.

By having a centralized inventory, the retailer is better able to strengthen its margins and fulfill orders quicker and in the ways customers want.

“Our new model will leverage all of our assets much more productively and improve customer satisfaction by increasing speed of delivery as well as generate efficiencies in our operations and inventory utilization.” Dennis Mullahy wrote.

In addition, Macy’s is getting on board with using data and analytics to not only get items to customers faster, but also improve inventory forecasting and allocation and package consolidation.

The company plans to increase drop-shipping to boost margins in e-commerce, where delivery costs have been the largest drain on profits. They’ll also renew their efforts into Macy’s Backstage operations in order to compete with other off-price companies such as Nordstrom Rack and TJMaxx.

Behind the curve

And while these improvements are giving Macy’s the help it needs, they should’ve seen the warning signs sooner. Retailers of equal size have been making moves to change their supply chain for years now, and Macy’s is just catching up.

For example, Kohls has been working to integrate e-commerce and brick and mortar stores since the beginning of 2018. The company worked to change its purchase and inventory management system by starting with the smallest stores and working their way up.

Nordstrom has been working on omnichannel fulfillment for over 3 years, and brought in tech consulting firm Opex Analytics to help.

Walmart unveiled plans this month to install a high-tech automation system across 25 Walmart regional distribution centers through their partnership with Symbotic, a robotics and automation company — something they’ve been working toward since 2017. This system will digitize and modernize Walmart’s current supply chain facilities to enrich customer experience and support evolving demand.

But even though Macy’s may be a few steps behind, true omnichannel is a journey — and a difficult one at that. It requires a lot from the supply chain, especially in terms of speed, complexity, and efficiency. The global retailer is making strides in executing their Polaris plan by focusing more on the integrated fulfillment strategy and alternative fulfillment options and listening to what their customers want.  

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Engage your students with real-world case studies that provide insights into supply chain practices, challenges, and opportunities. Share each case study with your students by simply copying and pasting the activity page URL into your learning management system (LMS).

Case 1: Rising Health Care Costs And The Role Of Outsourcing And Offshoring In The U.S. Health Care Sector

In this case study, your students will identify factors that are driving the health care costs higher in the United States than in peer countries. They will also discuss advantages and disadvantages of emerging trends in supply chain management such as adopting outsourcing in health care. After reading the case, they are encouraged to create an argument in favor of or against the view that health care offshoring is a threat to the U.S. health care industry.  See case study . 

• Case 2: McDonald’s Reinvents Itself Again

In this case study, your students will identify factors that are affecting demand management in the fast food industry and evaluate the reinvention strategy that McDonald’s has used to keep their fingers firmly on the pulse of their international customer base. Students will also be asked to advice McDonald’s with regards to future trends and the changes it should consider. After reading the case, they are encouraged to research areas in which the company plans to reinvent itself in the coming years, particularly in light of the appointment of its new CEO and the COVID-19 pandemic. See case study

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An Integrated Supply Chain Management System: A Case Study in Healthcare Sector

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• Dongsoo Kim 19  

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3590))

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This research has designed and developed an integrated supply chain management (SCM) system for optimizing inventory control and reducing material handling costs of pharmaceutical products in healthcare sector. The supply chain in this work is composed of pharmaceutical companies, a wholesaler, and hospitals. At first, we have analyzed hospital’s business processes and reviewed system requirements for the efficient supply chain management. VMI (Vendor-Managed Inventory), which is one of important applications of SCM, has been adopted and implemented to improve material handling efficiency. Online procurement system is also developed for the departments that consume drugs and place orders. Besides, real time information sharing functionalities are provided for optimizing inventory control of pharmaceuticals. The developed SCM system enables hospitals to improve the procurement processes and inventory control of pharmaceutical products, which results in decreasing total inventory more than 30%. By sharing information with hospitals, the wholesaler can gather more timely and exact data about inventory status and drug usage volumes of hospitals, so it can forecast the demand more accurately, which enables needed products to be supplied timely and cost-effectively. With the SCM system, total supply chain cost of pharmaceutical products has been decreased significantly.

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Hejlsberg, A., Wiltamuth, S., Golde, P.: The C# Programming Language. Addison-Wesley Professional, Reading (2003)

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McCann, C.J.: A Supply Chain Revolution: Understanding the Players. In: Proceedings of HIMSS Annual Conference 2003 (2003)

Erickson, C.: Managing the Medical Supply Chain; Deliver Smarter, Faster and at a Lower Cost. In: Proceedings of HIMSS Annual Conference 2005 (2005)

Arbietman, D., Lirov, E., Lirov, R., Lirov, Y.: E-Commerce for Healthcare Supply Procurement. Journal of Healthcare Information Management 15(1), 61–72 (2001)

EHCR Committee: Improving Supply Chain Management for Better Healthcare (November 2001), Available at, http://www.eccc.org/ehcr/ehcr/

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Tan, G.W., Shaw, M.J., Fulkerson, B.: Web-based Supply Chain Management. Information Systems Frontiers 2(1), 41–55 (2000)

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Haux, R., Winter, A., Ammenwerth, E., Brigl, B.: Strategic Information Management in Hospitals – An Introduction to Hospital Information Systems. Springer, New York (2004)

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Raghupathi, W., Tan, J.: Strategic IT Applications in Health Care. Communications of The ACM 45(12), 56–61 (2002)

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Graduate School of Healthcare Management and Policy, The Catholic University of Korea, 505 Banpo-Dong, Seocho-Gu, Seoul, 137-701, Republic of Korea

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Kim, D. (2005). An Integrated Supply Chain Management System: A Case Study in Healthcare Sector. In: Bauknecht, K., Pröll, B., Werthner, H. (eds) E-Commerce and Web Technologies. EC-Web 2005. Lecture Notes in Computer Science, vol 3590. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11545163_22

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The evolution of Amazon’s inventory planning system

How amazon’s scientists developed a first-of-its-kind multi-echelon system for inventory buying and placement..

For every order placed on the Amazon Store, mathematical models developed by Amazon’s Supply Chain Optimization Technologies organization (SCOT) work behind the scenes to ensure that product inventories are best positioned to fulfill the order. 

Forecasting models developed by SCOT predict the demand for every product. Buying systems determine the right level of product to purchase from different suppliers, while large-scale placement systems determine the optimal location for products across the hundreds of facilities belonging to Amazon’s global fulfillment network.

“With hundreds of millions of products sold across multiple geographies, developing automated models to make inventory planning decisions at Amazon scale is one of the most challenging and rewarding parts of our work,” said Deepak Bhatia , vice president of Supply Chain Optimization Technologies at Amazon.

We made the decision to redesign Amazon’s supply chain systems from the ground up.

In the first half of the past decade, Amazon transitioned from a largely manual supply chain management system to an automated one. However, when faced with the need to evolve Amazon’s supply chain to meet customer needs, and the introduction of same day delivery services like Prime Now, the team moved to replace that system with a new one that would better help Amazon fulfill delivery promises made to customers.

“As far back as 2016, we were able to see that the automated system we had at the time wouldn’t help us meet the ever-growing expectations of our customers,” Bhatia recalled. “As a result, we made the decision to redesign Amazon’s supply chain systems from the ground up.”

A global company catering to local needs

“In 2016, Amazon’s supply chain network was designed for scenarios where inventory from any fulfillment center could be shipped to any customer to meet a two-day promise,” said Salal Humair , senior principal research scientist at Amazon who has been with the company for seven years.

This design was inadequate for the new world in which Amazon was operating; one shaped by what Humair calls the “globalization-localization imperative.” Amazon’s expansion included an increasing number of international locations — at the time, the company had 175 fulfillment centers serving customers in 185 countries around the world .

“Meeting the needs of our customer base meant that we needed to serve those customers in multiple geographies,” Humair said.

As Amazon continued to expand internationally, the company also launched one-day and same day delivery windows in local regions for services like Amazon Prime and Amazon Prime Now.

“We quickly realized that in addition to serving customers around the globe, we also had to pivot from functioning as a national network to a local one, where we could position inventory close to our customers,” Humair says.

In addition to the ‘globalization-localization imperative,’ the growing complexity of Amazon’s supply chain network further complicated matters. To meet the increased customer demand for a diverse variety of shipping speeds, Amazon’s fulfillment network was expanding to include an increasing number of building types and sizes: from fulfillment centers (for everyday products) and non-sortable fulfillment centers (for larger items), to smaller fulfillment centers catering to same-day orders, and distribution centers that supplied products to downstream fulfillment centers. The network was increasingly becoming layered, and fulfillment centers in one layer (or echelon) were acting as suppliers to other layers.

“We had to reimagine every aspect of our system to account for this increasing number of echelons,” Humair said.

The science behind multi-echelon inventory planning

The sheer scale of Amazons operations posed a significant challenge from a scientific perspective. Amazon Store orders are fulfilled through complex dynamic optimization processes — where a real-time order assignment system can choose to fulfill an order from the optimal fulfillment center that can meet the customer promise. This real-time order assignment makes inventory planning an incredibly complex problem to solve.

Other inventory-related dependencies further complicate matters: the same pool of inventory is frequently used to serve demand for orders with different shipping speeds. Consider a box of diapers: it can be used to fulfill an order for a two-day Prime delivery. It can also be used to ease the life of harried parents who have placed an order on Prime Now, and need diapers for their baby delivered in a two-hour window.

Amazon’s scientists also have to contend with a high degree of uncertainty. Customer demand for products cannot be perfectly predicted even with the most advanced machine learning models. In addition, lead times from vendors are subject to natural variation due to manufacturing capacity, transportation times, weather, etc., adding another layer of uncertainty.

This required building a custom solution, one that relies on sound scientific principles and rigor, and borrowing ideas from academic literature as building blocks, but with ground-breaking in-house invention.

Humair notes that the scale of Amazon’s operations, the complexity of the network, and the uncertainties associated with the company’s dynamic ordering system make it impossible to even write down a closed-form objective function for the optimization problem the team was trying to solve.

While multi-echelon inventory optimization is a well-researched field, the bulk of literature focused on single-product models, proposed solutions for much simpler networks, or used greatly simplified assumptions for replenishing inventory.

“There is a large body of academic literature on multi-echelon inventory management, and papers typically focus on one or two main aspects of the problem,” noted Alp Muharremoglu , a senior principal scientist in SCOT who spent 15 years as a faculty member at Columbia University and the University of Texas at Dallas. “Amazon’s scale and complexity meant no existing solution was a perfect fit. This required building a custom solution, one that relies on sound scientific principles and rigor, and borrowing ideas from academic literature as building blocks, but with ground-breaking in-house invention to push the boundaries of academic research. It is a thrill to see multi-echelon inventory theory truly in action in such a large scale and dynamic supply chain.”

As a result, the system developed by SCOT (a project whose roots stretch back to 2016) is a significant break from the past. The heart of the model is a multi-product, multi-fulfillment center, capacity-constrained model for optimizing inventory levels for multiple delivery speeds, under a dynamic fulfillment policy. The framework then uses a Lagrangian-type decomposition framework to control and optimize inventory levels across Amazon’s network in near real-time.

Broadly speaking, decomposition is a mathematical technique that breaks a large, complex problem up into smaller and simpler ones. Each of these problems is then solved in parallel or sequentially. The Lagrangian method of decomposition factors complicated constraints into the solution, while providing a ‘cost’ for violating these constraints. This cost makes the problem easier to solve by providing an upper bound to the maximization problem, which is critical when planning for inventory levels at Amazon’s scale. 

“We computed opportunity costs for storage and flows at every fulfillment center,” Humair said. “Using Lagrangean decomposition, we then used these costs to calculate the related inventory positions at these locations. Crucially, we incorporated a stochastic dynamic fulfillment policy in a scalable optimization model, allowing Amazon to calculate inventory levels not at just one location, but at every layer in our fulfillment network.”

Mobilizing the organization

While creating the new multi-echelon system was an imposing scientific challenge, it also represented a significant organizational accomplishment, one that required collaboration across multiple teams.

“Moving multi-echelon from concept to implementation was one of the most difficult organizational challenges we’ve worked through; we had many potential implementations that looked radically different in terms of model capabilities, interfaces, engineering challenges, and long-term implications for how our teams would interact with each other,” said Jeff Maurer , a SCOT vice president who has been instrumental in rolling out the automation of Amazon’s supply chain and oversaw the roll out of the multi-echelon system.

“This was also a case where there wasn’t a great way to decide between them without building and exploring one or more approaches in production. Ultimately, that’s what we did — we picked the best options we could identify, built them out, learned from them, then repeated that process. We learned things by experimenting with real production implementations that we could never have learned from simplified models or simulations alone, given the complexity of the real-world dynamics of our supply chain. But it was hard on the teams — it wasn’t always obvious that the systems the teams were iterating on were the best path, given the high directional ambiguity.”

“Sometimes, the only way to make a massive change is to realize that you have no option but to make that change,” said Yan Xia , principal applied scientist at Amazon. Humair noted that Xia played “a pivotal role” over the four years it took the company to migrate to the new multi-echelon system.

Xia recalled that teams within SCOT were keenly aware of the limitations of the existing system.  However, there was skepticism that the multi-echelon system was the right solution.

“The skepticism was understandable,” Xia said. “It’s one thing to have a big idea. But you also have to be able to present the benefits of your idea in a coherent way.”

Xia gave an example of how he helped convince members from the buying and placement teams about the benefits of the new model.

“One team decides optimal suppliers to source products from, while another team makes decisions on where these products should be placed,” Xia explained. “I was able to show them how the two functions would essentially be unified in the multi-echelon system. Sure, it would change how they worked on a day-to-day basis — but it would do so in a way that made their lives simpler.”

To help ensure that resources were made available for the development of the multi-echelon system, Xia also focused on driving alignment among leaders in SCOT. He developed a simulation based on real-world data. The results clearly demonstrated that the proposed solution for inventory forecasting, buying, and placement would result in a steep decline in shipping costs, which in turn would allow Amazon to keep prices lower for customers.

Teams involved in multi-echelon planning discussions were galvanized after seeing the results of the simulation.

“Everyone bought into the vision,” Xia said. “We began to collaborate in near real-time. If we ran into a problem, we didn’t wait around for a weekly sprint meeting. We just got together in a room, or stood next to a whiteboard and solved it.”

Xia said that this was also when things began to get more complex. 

“An awareness of the complexity of the existing setup began to dawn on us,” says Xia. “We began to realize how every component in the system had multiple dependencies. For example, the buying platforms were tightly integrated with older legacy systems – we now had to factor these dependencies into our solutions.”

Solving a multi-item, multi-echelon with stochastic demand and lead-time and aggregated capacity constraints and differentiated customer service levels. That sort of thing is just unheard of in the academia and the industry.

The team iterated on the multi-echelon solution in a sequence of three in-production experiments (or labs) that spanned 2018 to 2020. The first lab incorporated components of the new system coupled with the old platform. It was a resounding success in terms of reducing costs, even while fulfilling orders associated with higher shipping speeds. The team moved on to testing the subsequent version of the multi-echelon system in the second lab. 

“That wasn’t nearly as good,” Xia recalled. “Most things didn’t work as expected.”

However, the team was encouraged by leadership to keep going. This wasn’t SCOT’s first attempt at taking on big and ambitious projects. The organization had taken three years to deploy the first automated supply chain management system where they overcame various challenges.

“Sure, the failure of the second lab was demotivating,” Xia says. “But we knew from experience that this failure was only to be expected. It was part of the process.”

The team fixed the bugs, and moved on to testing new features in the third lab. These included critical system capabilities, such the ability to model order cut-off times for deliveries within a particular time window.

The system went live in 2020, and over the past year, the multi-echelon system has had a large and statistically significant impact in positioning products closer to customers.

“On a personal level, I am incredibly proud of our team. Having worked in the area of multi-echelon inventory optimization before I joined Amazon, I have a deep appreciation of how difficult it was,” Bhatia noted. “There is a strong sense of pride for the work the team is doing — such as solving a multi-item, multi-echelon with stochastic demand and lead-time and aggregated capacity constraints and differentiated customer service levels. That sort of thing is just unheard of in academia and industry. This is why I find it gratifying to work as a scientist and a leader at Amazon. It gives me a lot of pride, and none of this could have been achieved without the people and the culture we have.”

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• Supply Chain Optimization Technologies (SCOT)
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• Demand forecasting

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Why metrics are the building blocks for supply chain transformation

A major US health care provider had a vision to deliver quality care more efficiently, but divergent data management was clouding the horizon.

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• 2. Better answer
• 3. Better working world

How EY can help

The better the question

How can data drive your supply chain to new heights?

With operations across the US, this health care giant had to make sense of disparate figures across varying systems and dashboards.

Operating as one of the largest health systems in the US and serving millions of members nationwide, this health care company was managing highly varied patient needs across multiple states. Over 30 hospitals and dozens of medical centers needed an efficient supply chain to deliver important medical items for doctors, patients and staff. Dependability and resiliency were operational imperatives for this organization — inefficiencies and disruptions could quickly become life-threatening.

When COVID-19 struck, this health care company created a “war room” to check and double-check its inventory, which informed them when patients could be scheduled and when materials would be available to support corresponding appointments and procedures. As the crisis began to ease into a new normal, data accuracy and visibility within the organization’s supply chain had proven to be an organizational imperative.

To keep this health care organization future-focused, it wanted to undergo a digital transformation centered on data automation, simplification and standardization across the multiple states and markets it served. It wanted to identify what regions of its supply chain were underperforming and which areas and processes might be modeling organizational best practices.

Individual offices, hospitals and regions were measuring success differently using varying systems, all using conflicting definitions of success, which made it extremely difficult to compare and benchmark across the entire organization. It was obvious that this health care company needed a dashboard of streamlined metrics.

Ernst & Young LLP (EY) was called upon to deliver fast results. In less than two months, the EY team pinpointed current metrics across regions and offices and drove the dialogue needed to help plot the course toward streamlined reports and a cohesive picture of success across the network to better inform leadership decision-making, supply chain forecasting and inventory planning.

“We were excited to join this health care organization on their quest for operational excellence and knew we could deliver immediate results by making sense of disparate numbers and systems, giving them a baseline to benchmark future success against,” said Ashutosh Dekhne , EY Americas Supply Chain & Operations Practice Leader. “Common metrics and consistent data management are the building blocks they needed to keep their supply chain operating effectively.”

The better the answer

Collective dialogue helps define a new path forward

EY workshops identified the right metrics and technology needed to strengthen this health care organization’s operating model.

EY facilitated three workshops for this health care organization, designed with a future-back approach — starting with the organization’s vision and connecting it to the metrics that drive progress toward those goals. Workshop attendees represented all the regions and supply chain operations in scope across the organization.

During the sessions attendees shared over 100 ideas on how to translate the organization’s supply chain vision into tangible actions. EY guided the workshops with deep health care sector knowledge and synthesized the findings for executives. The recommendations from these sessions would shape the strategy EY created for effective data management throughout the organization.

The biggest learning achieved through these collaborative workshops was that many people had faith in their own metrics and related processes within their regions, but not in the data management processes across the organization. Resources reported following over 375 metrics (85 of which were unique), consulting 130 different dashboards and reports, and using 15 technology systems and platforms. The quality of their data and metrics was questionable because it came from many sources, at different times — some devised manually, others in a dashboard used infrequently, following varying definitions. What qualified as “on time” for one hospital was totally different from another hospital, even though they were part of the same network. Most data from the dashboards and platforms was only as reliable as the most recent manual update.

“We quickly realized through these focus groups that we had no data standardization across our organization,” this health care organization’s Chief Supply Chain Officer said. “We needed a common set of definitions, numbers, analytics and tools that flowed throughout all our hospitals and offices, and those systems needed to be regularly used and trusted by our people.”

Through more dialogue facilitated by EY, participants began narrowing down the list of metrics, dashboards and reports they used to determine what data management processes should be retained and which operations could be reduced. Participants voted on the value of specific reporting practices and provided input on the tools they found most accurate and user-friendly.

“One hundred thirty dashboards were ultimately streamlined into one cohesive console,” the Chief Supply Chain Officer said. “This new dashboard allows us to quickly track performance, see inventory and manage volume across our network’s supply chain.”

Keeping their organizational vision in mind, to serve patients quickly and effectively, participants agreed that by reducing time spent on superfluous data management activities would free up bandwidth to serve more patients, and that streamlined reporting would give them the visibility needed to ensure all patients received the same high standard of care. With the upgraded and consolidated reports now in place, this health care organization is now using a more effective data management to support a more efficient operating model.

The better the world works

Streamlined data helps create lasting change

By reducing the number of metrics and tools, EY helped this hospital system focus on what’s most important – its patients.

Executives at this health care consortium now have identified the top 25 key metrics — down from 375 — needed to assist them in making important supply chain decisions related to inventory, scheduling and volume across their network.

The 15 different technological platforms that once fed 130 operational dashboards have now been streamlined into one standardized dashboard, underpinned by one technology platform. With one visible central system to manage data across their vast network, leaders are spending less time reconciling numbers and can make faster more informed operational decisions that serve their hospitals better.

EY also programmed the single technology platform to accept data from an internal customer scorecard, helping the health care organization keep patients’ needs top of mind.

So that the new data management model would stick, EY had monthly touchpoints with the leadership team throughout the first year. In Phase 1, touchpoints validated that metrics were being leveraged appropriately and redeployed across regions effectively. Areas that needed change management and training were identified, if needed. As the first year progressed, EY helped this organization pinpoint potential new metrics and further changes in its technical architecture that could keep its supply chain future focused.

“We now have a strong loop of training, communication and measurement of our new data management system,” said the company’s Chief Operations Officer. “We are also embedding these new ways of working into our performance management process to drive lasting change within our organization.”

Results achieved:

• 30 hospitals better served through optimized data
• 375 metrics tracked reduced to top 25
• 15 tools/systems folded into one cohesive technology platform

By investing in data, this health care company is investing in people. Behind the doctors and nurses who provide care, and the patients who need medicine and service, there are numbers — metrics that may seem routine on a screen, but that underpin a health care system that millions of Americans rely on. With a more solid data management process, this organization can now optimize their supply chain and focus on providing high-quality care for patients across the country.

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Supports clients in transforming their businesses through capability building. College football fan. Professional table tennis player. Proud father of a daughter aspiring to be a medical doctor.

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Information systems in supply chain management: A comparative case study of three organisations

• School of Business Administration (Harrisburg)

Research output : Contribution to journal › Article › peer-review

Supply Chain Management (SCM) is recognised as a core competitive strategy for businesses in almost every industry. A strong supply chain provides products and services to consumers faster, cheaper, and better. The paper discusses SCM and information systems in the supply chain. Case studies of Wal-Mart, Amazon.Com and United Parcel Services (UPS) and their use of information systems in the supply chain are presented. Wal-Mart and Amazon have established critical and timely strategies in their supply chains through huge investments in Information Technology (IT). While Wal-Mart and Amazon are offering their products to consumers, UPS offers logistics solutions to clients. These companies use a variety of information technologies which include satellite systems, barcodes, web-based Electronic Data Interchange (EDI), Radio Frequency Identification (RFID), data warehousing, and e-commerce in their supply chain. The supply chain and use of these technologies in SCM are reviewed and compared for these three organisations.

All Science Journal Classification (ASJC) codes

• Management Information Systems
• Information Systems and Management
• Management of Technology and Innovation

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• 10.1504/IJBIS.2006.008955

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• Supply chain management Engineering & Materials Science 100%
• Comparative Case Study Business & Economics 97%
• Supply chains Engineering & Materials Science 78%
• Information systems Engineering & Materials Science 65%
• Supply Chain Management Business & Economics 63%
• Information Systems Business & Economics 56%
• Wal-Mart Business & Economics 51%
• Supply Chain Business & Economics 47%

T1 - Information systems in supply chain management

T2 - A comparative case study of three organisations

AU - Subramanian, Girish H.

AU - Iyigungor, Abdullah C.

N2 - Supply Chain Management (SCM) is recognised as a core competitive strategy for businesses in almost every industry. A strong supply chain provides products and services to consumers faster, cheaper, and better. The paper discusses SCM and information systems in the supply chain. Case studies of Wal-Mart, Amazon.Com and United Parcel Services (UPS) and their use of information systems in the supply chain are presented. Wal-Mart and Amazon have established critical and timely strategies in their supply chains through huge investments in Information Technology (IT). While Wal-Mart and Amazon are offering their products to consumers, UPS offers logistics solutions to clients. These companies use a variety of information technologies which include satellite systems, barcodes, web-based Electronic Data Interchange (EDI), Radio Frequency Identification (RFID), data warehousing, and e-commerce in their supply chain. The supply chain and use of these technologies in SCM are reviewed and compared for these three organisations.

AB - Supply Chain Management (SCM) is recognised as a core competitive strategy for businesses in almost every industry. A strong supply chain provides products and services to consumers faster, cheaper, and better. The paper discusses SCM and information systems in the supply chain. Case studies of Wal-Mart, Amazon.Com and United Parcel Services (UPS) and their use of information systems in the supply chain are presented. Wal-Mart and Amazon have established critical and timely strategies in their supply chains through huge investments in Information Technology (IT). While Wal-Mart and Amazon are offering their products to consumers, UPS offers logistics solutions to clients. These companies use a variety of information technologies which include satellite systems, barcodes, web-based Electronic Data Interchange (EDI), Radio Frequency Identification (RFID), data warehousing, and e-commerce in their supply chain. The supply chain and use of these technologies in SCM are reviewed and compared for these three organisations.

UR - http://www.scopus.com/inward/record.url?scp=33645014610&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33645014610&partnerID=8YFLogxK

U2 - 10.1504/IJBIS.2006.008955

DO - 10.1504/IJBIS.2006.008955

M3 - Article

AN - SCOPUS:33645014610

SN - 1746-0972

JO - International Journal of Business Information Systems

JF - International Journal of Business Information Systems

Automotive Case Study: Chery Phase 1

Established in 2023, Chery Super Factory is a cutting-edge automobile manufacturing plant with a focus on integrating advanced technologies and realizing digital transformation. With an annual production capacity of 300,000 vehicles and 200,000 KD units, the factory aims to be at the forefront of business integration, smart supply chain management, and a robust logistics ecosystem. Chery is a pioneer in the industry, being one of the first to adopt vision-based AMRs for automated material movement in the assembly workshop. In this first stage of deployment, more than 100 AMRs have been integrated with the factory's Logistics Execution Systems (LES) software to enable unmanned material movement across various assembly lines.

Please CLICK HERE to download the white paper.

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Gartner: Supply chain function may lose boardroom influence in “post-crisis” era

Chief supply chain officers should expand their focus beyond cost management, firm says..

Chief supply chain officers (CSCOs) must expand their focus beyond cost management or else accept a relegated role within the enterprise, according to the latest analysis by Gartner Inc.

In remarks at the firm’s Gartner Supply Chain Symposium/Xpo this week, experts said that to retain influence and control of their strategic objectives, CSCOs must focus on initiatives that can deliver multiple sources of value and align with their CEOs’ growth agendas. 

“Stakeholders perceive that the worst of the supply chain crisis has receded, and CSCOs now face the prospect of being allocated fewer resources with the expectation of returning to a role more confined within the enterprise,” Tom Enright, VP Analyst in Gartner’s Supply Chain practice, said in a release. “CSCOs’ own priorities centered on cost management may be contributing to a loss of influence, as their CEOs remain steadfastly focused this year on driving growth.”

So for the supply chain function to retain influence in a “post-crisis” state, CSCOs must deliver multi-value contributions where their investments create maximum impact across key priorities that include growth, resilience, sustainability, risk reduction, and other priorities, while also addressing cost, he said. 

“While the supply chain function is most often delegated cost management responsibilities, it is indispensable for delivering other important forms of value,” said Enright. “It is up to supply chain leaders to identify and prioritize those investments that will deliver simultaneous sources of value, in line with their team’s strengths and stated priorities.”

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