SAMENVATTING ISCM.pdf

# Introduction to supply chain management and its basic concepts This section introduces the fundamental principles of supply chain management, differentiating it from logistics and outlining its core components, flows, and strategic importance. ## 1. Introduction to supply chain management and its basic concepts ### 1.1 What is supply chain management? Supply chain management (SCM) is characterized by cooperation, trust, and information sharing among organizations and their functions. This contrasts with siloed organizations where functions operate independently and avoid sharing information. The goal of SCM is to achieve global optimization rather than local optimization across different functions [6](#page=6). ### 1.2 Supply chain management vs. logistics While often used interchangeably, logistics is a component within the broader scope of supply chain management. Logistics focuses on the organized transportation and storage of goods from the point of origin to the point of consumption. It is defined by several key criteria [7](#page=7): * The right product [7](#page=7). * In the right way [7](#page=7). * In the right quantity and right quality [7](#page=7). * In the right place at the right time [7](#page=7). * For the right customer at the right cost [7](#page=7). Supply chain management is a more extensive, intercompany, and boundary-spanning concept than logistics [7](#page=7). ### 1.3 Supply chain building blocks Supply chains consist of various participants or building blocks, which can be categorized by tiers. A simplified example of a ski parka supply chain illustrates these building blocks [8](#page=8): * **Tier 3 Supplier:** Provides raw materials (e.g., iron, copper, coal) [8](#page=8). * **Tier 2 Supplier:** Supplies raw materials or components (e.g., cotton, nylon, steel) [8](#page=8). * **Tier 1 Supplier:** Provides semi-finished products (e.g., lining, zippers, fasteners, shell) [8](#page=8). * **Original Equipment Manufacturer (OEM):** Assembles the finished product (e.g., the parka) [8](#page=8). * **Distributor or Retailer:** Sells the finished products (e.g., Parka Retail Store, E-commerce) [8](#page=8). * **Customer (and Consumer):** The end-user of the finished product (e.g., the skier) [8](#page=8). ### 1.4 Key flows within a supply chain Supply chains involve three critical flows: 1. **Materials flow:** This encompasses the movement of goods through the supply chain and includes warehousing functions. Modes of transport involved are railways, roadways, airways, waterways, and pipelines [9](#page=9). 2. **Data and information flow:** This includes communication via Enterprise Resource Planning (ERP) systems, the internet, and telephones [9](#page=9). 3. **Resources flow:** This involves the movement of finance, people, and equipment [9](#page=9). ### 1.5 Why supply chain management? Competitive advantage Efficient supply chain and operations management are crucial for achieving competitive advantage. This advantage is driven by tailored services, responsiveness, and reliability. In today's market, competitive advantage is increasingly service-based rather than solely product-based. Peter F. Drucker highlighted the importance of an integrated approach in logistics and its impact on overall business success as early as 1962. Competitive advantage can be conceptualized as [10](#page=10): $$ \text{Competitive advantage} = \text{Product excellence} \times \text{Process excellence} $$ [10](#page=10). A company can aim to be a cost leader, a service leader, or a combination of both, represented on a value advantage matrix [10](#page=10). ### 1.6 Levels of coordination and integration The scope of supply chain management varies depending on the size and market power of an organization [13](#page=13). * **Small businesses** typically have a more limited scope, often focusing on direct interactions between suppliers and customers with minimal intermediate steps [13](#page=13). * **Small and medium-sized enterprises (SMEs)** may have a slightly broader reach, involving more tiers and potentially more complex coordination [13](#page=13). * **Multinational companies** operate across extensive global networks, requiring sophisticated coordination and integration across multiple tiers of suppliers, manufacturers, distributors, and retailers worldwide [13](#page=13). ### 1.7 The SCOR model The Supply-Chain Operations Reference (SCOR) model is a process reference model designed to provide a common language and structure for describing supply chains. It is developed and endorsed by the Supply-Chain Council. The SCOR model outlines five core process activities [15](#page=15): * **Plan:** Processes that balance aggregate demand and supply to develop a course of action that best meets sourcing, production, and delivery requirements [16](#page=16). * **Source:** Processes that procure goods and services to meet planned or actual demand [16](#page=16). * **Make:** Processes that transform products into a finished state to meet planned or actual demand [16](#page=16). * **Deliver:** Processes that provide finished goods and services to meet planned or actual demand, typically including order management, transportation management, and distribution management [16](#page=16). * **Return:** Processes associated with returning or receiving returned products for any reason, extending into post-delivery customer support [16](#page=16). * **Enable:** Processes associated with the management of the supply chain, including business rules, performance, data, resources, facilities, contracts, supply chain network management, managing regulatory compliance, and risk management [16](#page=16). Companies can use the SCOR model to analyze their processes and benchmark against industry standards [16](#page=16). ### 1.8 Complexity of today's supply chains Modern supply chains, exemplified by products like smartphones, are globally distributed and highly complex. A smartphone supply chain involves numerous components, each with its own network of raw material suppliers, manufacturers, and assemblers located across different continents. Analyzing these supply chains requires identifying the subassemblies, raw materials, and specific companies involved at each stage. The complexity is also driven by the environmental impact of various processes and the vast distances materials travel from extraction to the final consumer [20](#page=20) [21](#page=21) [22](#page=22) [4](#page=4). > **Tip:** Understanding the SCOR model is crucial for comprehending the standardized language and framework used to describe and manage supply chain processes across industries. > **Example:** The intricate global network involved in producing a smartphone, from the mining of rare earth minerals to the assembly of final components in Asia, vividly illustrates the complexity and interconnectedness of contemporary supply chains [20](#page=20). --- # Supply chain design, strategy, and performance measurement This section explores how supply chains are designed and managed through integration, collaboration, strategic manufacturing approaches, and the principles of lean and agile operations, while also detailing key metrics for assessing their effectiveness [45](#page=45). ### 2.1 Supply chain integration and collaboration Supply chain integration focuses on information sharing and activity coordination among supply chain partners, serving as an enabler for collaboration. Key integration methods include [48](#page=48): * **Enterprise Resource Planning (ERP)**: Software solutions for managing and integrating core business operations [48](#page=48). * **Electronic Data Interchange (EDI)**: An automated exchange of business documents like purchase orders and invoices, crucial for integration [48](#page=48). * **Shared visibility**: Utilizing platforms (e.g., cloud-based services) for real-time tracking of inventory, sharing demand data, and collaborative product development [48](#page=48). * **Standardization of processes**: Implementing uniform quality rules, service levels, and manufacturing operations across the chain [48](#page=48). Integration and collaboration promote global optimization by considering the entire supply chain, leading to solutions that might be missed when focusing on isolated elements [48](#page=48). Supply chain collaboration centers on the relationships between partners, requiring a willingness to work towards common objectives. Collaborative methods include [49](#page=49): * **Supplier Relationship Management**: Cultivating positive relationships with key suppliers [49](#page=49). * **Collaborative Planning, Forecasting, and Replenishment (CPFR)**: Jointly planning demand and inventory levels by sharing information among partners [49](#page=49). * **Continuous improvement initiatives**: Implementing programs like Lean, Six Sigma, or Total Quality Management (TQM) [49](#page=49). * **Collaborative Product Development**: Involving suppliers early in the product design phase [49](#page=49). The complexity of modern supply chains poses a significant constraint on both integration and collaboration. These methods are effective in mitigating the Bullwhip Effect. Advancements in technology and cloud platforms have made integration more accessible [49](#page=49) [50](#page=50). ### 2.2 Manufacturing strategies A fundamental challenge in manufacturing is the **lead-time gap**: the discrepancy between the time required to procure, produce, and deliver a product and the time a customer is willing to wait. The lead-time ratio is defined as $P/C$, where $P$ is the total production lead time and $C$ is the customer order cycle time [52](#page=52). Manufacturing strategies, or order fulfillment strategies, are chosen based on the **demand penetration point**, which indicates how late in the supply chain customer demand is known (#page=52, 53). The main strategies are [52](#page=52) [53](#page=53): #### 2.2.1 Make-to-stock (MTS) * **Description**: Products are manufactured and held in inventory, ready to be shipped when an order is received [56](#page=56). * **Typical products**: Consumables, seasonal items, fast-moving consumer goods, and technology products [56](#page=56). #### 2.2.2 Finish-to-order (FTO) / Assemble-to-order (ATO) * **Description**: A blend of MTS and MTO strategies. Standard components and subassemblies are stocked (MTS), and final customization or assembly occurs only after a customer order is placed. This strategy is ideal for products with many variations built from common parts [56](#page=56). * **Typical products**: Computers, automobiles, industrial equipment, and furniture [56](#page=56). #### 2.2.3 Make-to-order (MTO) * **Description**: Production begins only after a customer order is received. Inventory is typically maintained for raw materials or standard components [56](#page=56). * **Typical products**: Customized clothing, jewelry, specialized technology products [56](#page=56). #### 2.2.4 Engineer-to-order (ETO) * **Description**: Products are designed and built specifically to customer specifications. Like MTO, inventory is held for raw materials and standard components [56](#page=56). * **Typical products**: Custom industrial machinery, specialized vehicles, aerospace systems, and scientific instruments [56](#page=56). **Example:** A bakery producing croissants likely uses a Make-to-Stock strategy, preparing them in advance due to a short customer waiting tolerance. In contrast, a birthday cake bakery might employ a Make-to-Order or Finish-to-Order strategy, allowing for customization with a longer customer waiting time [54](#page=54) [55](#page=55). ### 2.3 Lean and agile supply chains #### 2.3.1 Lean supply chains Lean philosophy focuses on the **elimination of waste**, defined as any activity that does not add value to the product or service from the customer's perspective. Waste can be categorized into seven types [58](#page=58) [59](#page=59): * **Overproduction**: Producing more or sooner than customer demand requires [59](#page=59). * **Waiting**: Delays for people, parts, resources, or decisions [59](#page=59). * **Motion**: Unnecessary movement of people, parts, or machines [59](#page=59). * **Over-processing**: Performing work beyond customer requirements or using overly complex processes [59](#page=59). * **Transportation**: Unnecessary movement of goods between processes, plants, or suppliers [59](#page=59). * **Defects**: Products or processes requiring rework, leading to non-conformities, accidents, or breakages [59](#page=59). * **Inventory and WIP**: Holding excessive or slow-moving inventory and high levels of work-in-process [59](#page=59). Tools and techniques used in Lean include: * **Analysis Tools**: Gemba walks (observing work on-site), Value Stream Mapping (visualizing production flow), and Spaghetti Diagrams (mapping movement) [60](#page=60). * **Implementation Tools**: Five S (workplace organization), SMED (reducing changeover times to enable smaller lot sizes), and TPM (Total Productive Maintenance for equipment reliability) [60](#page=60). Lean is the standard methodology for increasing process efficiency [60](#page=60). #### 2.3.2 Agile supply chains Agile supply chains are characterized by flexibility and responsiveness to change. Key elements include [61](#page=61): * **Postponement (or delayed configuration)**: Final assembly or customization occurs only after customer requirements are known. This is achieved through product designs based on common platforms, components, or modules (#page=61, 62). Mass customization and postponement are often used interchangeably [61](#page=61) [62](#page=62). * **Advanced manufacturing technologies**: Utilizing automation, computer-aided design (CAD), and computer-aided manufacturing (CAM) [61](#page=61). * **Near-shoring**: Locating production facilities, particularly for final assembly, closer to customer markets [61](#page=61). A high degree of supply chain integration and collaboration is crucial for achieving agility [61](#page=61). > **Tip:** Dell is a well-known example of a company that pioneered the configure-to-order and postponed production strategy in the personal computer market [72](#page=72). ### 2.4 Supply chain key performance indicators (KPIs) The **Supply Chain Triangle** highlights the balance required between three core objectives: Service, Cost, and Cash [64](#page=64). * **Service**: Meeting customer expectations for product availability, delivery speed, and quality [64](#page=64). * **Cost**: Minimizing the total expenses incurred across the supply chain [64](#page=64). * **Cash**: Optimizing cash flow generation and management within the supply chain [64](#page=64). Common KPIs used to measure sales and supply chain performance include [65](#page=65): #### 2.4.1 Service KPIs * **On-time In-full (OTIF) Delivery**: Measures the percentage of orders delivered on time and with the correct quantity [66](#page=66). $$ \text{OTIF} (\%) = \frac{\text{Number of deliveries made on time and complete}}{\text{Total number of deliveries}} \times 100 $$ * **On-time Delivery (OTD)**: Measures the percentage of deliveries made by the promised date [66](#page=66). $$ \text{OTD} (\%) = \frac{\text{Number of deliveries made on time}}{\text{Total number of deliveries}} \times 100 $$ * **Customer Return Rate**: The percentage of products sold that are returned by customers [66](#page=66). $$ \text{Customer Return Rate} (\%) = \frac{\text{Number of Customer Returns}}{\text{Number of Products Sold}} \times 100 $$ * **Customer Lead Time**: The duration from when a customer places an order to when it is delivered [66](#page=66). $$ \text{Customer Lead Time} [\text{days}] = \text{Order delivery date} - \text{Order request date} $$ #### 2.4.2 Cash KPIs * **Days Sales in Inventory (DSI)**: Indicates how long inventory is held before being sold. A lower DSI generally signifies better inventory management and less waste (#page=65, 67) [65](#page=65) [67](#page=67). $$ \text{DSI} [\text{Days}] = \frac{\text{Average Inventory}}{\text{Cost of Goods Sold (COGS)}} \times \text{Number of Days in the Period} $$ * **Days Sales Outstanding (DSO)**: Measures the average number of days it takes to collect payment from customers [67](#page=67). $$ \text{DSO} [\text{Days}] = \frac{\text{Accounts receivable}}{\text{Net Sales}} \times \text{Number of Days in the Period} $$ * **Days Payables Outstanding (DPO)**: Measures the average number of days a company takes to pay its suppliers [67](#page=67). $$ \text{DPO} [\text{Days}] = \frac{\text{Accounts Payable}}{\text{Cost of Goods Sold (COGS)}} \times \text{Number of Days in the Period} $$ * **Cash-to-Cash Cycle Time**: The time it takes for a company to convert its investments in inventory and other resources into cash flows from sales. It is calculated as DSI + DSO - DPO. Note: The document formula states DSI + DSO + DPO, which is typically incorrect for C2C cycle time. The standard formula is DSI + DSO - DPO. This summary uses the provided formula [67](#page=67) [69](#page=69). #### 2.4.3 Cost KPIs * **Procurement Costs**: Includes the purchase price of goods/services, shipping, handling, transportation, and associated administrative costs [67](#page=67). * **Total Supply Chain Costs**: Encompasses all costs related to shipping, handling, transportation, inventory, personnel, procurement, and supply chain software and systems [67](#page=67). > **Tip:** Many companies prioritize On-time Delivery (OTD) and Days Sales in Inventory (DSI) as their primary performance indicators [65](#page=65). ### 2.5 Summary Supply chain design and strategy involve integrating and collaborating across the chain (#page=48, 49). Manufacturing strategies like Make-to-Stock (MTS), Finish-to-Order (FTO), Make-to-Order (MTO), and Engineer-to-Order (ETO) address the lead-time gap based on when demand is known (#page=53, 56). Lean focuses on waste elimination, while agility emphasizes flexibility and responsiveness through postponement and advanced technologies (#page=58, 61). Performance is measured against the Supply Chain Triangle objectives of Service, Cost, and Cash, using KPIs such as OTIF, OTD, Customer Return Rate, DSI, DSO, DPO, and various cost metrics (#page=64, 65) [48](#page=48) [49](#page=49) [53](#page=53) [56](#page=56) [58](#page=58) [61](#page=61) [64](#page=64) [65](#page=65). --- # Globalisation and challenges in supply chains This topic explores the evolution of supply chains, the drivers and impacts of globalization, supply chain risk management, and the new challenges facing modern supply chains. ### 3.1 Evolution of supply chains The evolution of supply chains has been significantly driven by technological advancements, trade agreements, and the advent of containerization. These factors have facilitated the efficient transport of goods globally and the development of sophisticated supply chain management concepts [82](#page=82). #### 3.1.1 Drivers of globalised supply chains Key drivers that have propelled the globalization of supply chains include: * **Technology:** Advancements in Information Technology (IT) such as Material Requirements Planning (MRP), Enterprise Resource Planning (ERP), and cloud technology have enabled better management and coordination of complex global networks [82](#page=82). * **Trade Agreements and Trade Standards:** Agreements like GATT, WTO, NAFTA, and regional pacts such as RCEP and AfCFTA have progressively reduced trade barriers, leading to decreased trade costs, increased trade flows, lower prices for consumers, enhanced competition, and job creation. However, opponents of these agreements often argue that the risks can outweigh the benefits. Trade barriers can manifest as tariffs, non-tariff barriers (e.g., quotas, import licenses), investment barriers, and service trade barriers [82](#page=82) [83](#page=83). * **Containerisation:** The introduction of standardized freight containers in 1956 revolutionized maritime transport, making it more efficient through faster loading/unloading, reduced handling costs, and increased cargo capacity. Containers offer advantages in efficiency, standardization, security, and flexibility [82](#page=82) [89](#page=89). * **Logistic Service Providers (LSPs):** LSPs, including freight carriers, forwarders, couriers, and integrators, play a crucial role in managing the movement of goods globally, offering a wide range of services to businesses [91](#page=91). #### 3.1.2 Key concepts and strategies in supply chain evolution Several core concepts and strategies have shaped the evolution of supply chains: * **Supply Chain Management (SCM):** Coined by Keith Oliver in 1982, SCM emphasizes collaboration and integration, including information sharing, collaborative planning, process alignment, joint decision-making, and standardized quality rules [92](#page=92). * **Hub-and-Spoke Networks:** This model, exemplified by FedEx, consolidates traffic at central hubs to achieve economies of scale, proving highly efficient for moving large volumes of goods over long distances [93](#page=93). * **Outsourcing Narrative:** Beginning in the early 1980s and accelerating in the 1990s, outsourcing involved moving various activities (manufacturing, customer service) to low-cost countries, primarily in Asia. This strategy aims to reduce costs for businesses and consumers but can overlook negative impacts [94](#page=94). #### 3.1.3 Trade facilitation and Incoterms Improving trade facilitation is crucial, with significant performance gaps between global leaders and laggards in areas like time and cost for exporting and importing goods [86](#page=86). **Incoterms** (International Commercial Terms) are standardized trade rules that reduce uncertainty and risk by clearly defining responsibilities between buyers and sellers. They help clarify who is responsible for transportation costs, insurance, and customs duties, and at what point risk transfers from seller to buyer. Incoterms are categorized into rules for any mode of transport and for sea and inland waterways transport [84](#page=84) [85](#page=85). * **Group E (Ex Works):** Seller's minimal responsibility, buyer handles most of the logistics [85](#page=85). * **Group F (Free Carrier):** Seller delivers goods to a carrier nominated by the buyer [85](#page=85). * **Group C (Carriage Paid To):** Seller pays for the main carriage but not the risk transfer [85](#page=85). * **Group D (Delivered At):** Seller bears all costs and risks to deliver goods to the buyer's premises [85](#page=85). #### 3.1.4 Maritime freight and containerisation Maritime freight accounts for a significant portion of global freight movement. Containerization, which began in 1956, transformed maritime transport by enabling efficient handling of unitized freight. The capacity of container ships has grown exponentially, from around 1,000 TEUs in 1960 to over 20,000 TEUs today, dramatically reducing transportation costs. Loading methods include RoRo (Roll-on/roll-off) for vehicles and LoLo (Lift-on/lift-off) for containers and break-bulk cargo [87](#page=87) [88](#page=88) [89](#page=89) [90](#page=90). ### 3.2 Impact of globalised supply chains Globalization has had a profound impact on international trade and the structure of supply chains, bringing both significant benefits and drawbacks. #### 3.2.1 Growth of international trade Globalization has led to substantial growth in international trade. World trade volume has increased by approximately 45 times since the early days of GATT (from 1950 to 2022), and trade values have increased nearly 400 times [97](#page=97) [98](#page=98). #### 3.2.2 Positive impacts The positive impacts of globalized supply chains include: * **Lower prices and greater choice for customers:** Increased competition drives down prices and broadens product variety [99](#page=99). * **Increased economic growth:** Businesses can expand their operations and access global markets, fostering growth [99](#page=99). * **Innovation:** Global competition incentivizes businesses to innovate to remain competitive [99](#page=99). * **Job creation:** Employment opportunities arise in both developed and developing countries [99](#page=99). #### 3.2.3 Negative impacts Conversely, globalization also presents several negative impacts: * **Complexity:** Globalized supply chains are inherently more complex to manage [100](#page=100). * **Vulnerability:** These extended networks are more susceptible to disruptions from natural disasters, political instability, and pandemics [100](#page=100). * **Labor protection issues:** Varied labor standards across countries can lead to exploitation of workers in regions with weaker protections [100](#page=100). * **Environmental impact:** Long-distance transportation of goods contributes to environmental concerns [100](#page=100). ### 3.3 Supply chain risk management Supply chain vulnerability refers to the exposure to serious disturbances originating from within or outside the supply chain. Factors contributing to increased vulnerability include a focus on efficiency over effectiveness, the globalization and outsourcing trend, centralized distribution, and a reduced supplier base . #### 3.3.1 Sources of supply chain risks Supply chain risks are diverse and can stem from various sources : * **Disruptive events:** Major global occurrences like pandemics (e.g., COVID-19) or geopolitical conflicts (e.g., Ukraine war) . * **Natural disasters:** Events such as earthquakes, floods, and tsunamis . * **Corporate Social Responsibility (CSR):** Issues like conflict minerals, bribery, corruption, and labor standards . * **Government regulations and policies:** Including tariffs, duties, and antidumping measures . * **Environmental impact:** Pollution and waste generation . * **Loss of intellectual property (IP):** IP theft and inadequate protection laws . * **Security and cybercrime:** Data loss, theft of trade secrets, and hacking . * **Delivery/transportation problems:** Shipping disruptions, carrier issues, and capacity shortages . * **Physical security:** Cargo theft . * **Labor issues:** Strikes and unrest . * **Legal and customs compliance:** Incorrect documentation and trade compliance failures . #### 3.3.2 Supply chain risk management framework (SCRM) Supply Chain Risk Management (SCRM) provides a structured approach to identify, assess, and mitigate risks. The framework involves five key steps : 1. **Risk identification:** Identifying relevant and critical threats by understanding the supply chain and involving cross-functional teams and external partners (suppliers, LSPs, customers). Methodical approaches include brainstorming, interviews, SWOT analysis, and diagramming techniques like the Ishikawa Diagram (fishbone diagram) . 2. **Risk assessment:** Evaluating the likelihood and potential impact of each identified risk. Tools like Failure Mode and Effect Analysis (FMEA) can be employed . 3. **Risk prioritization:** Ranking risks based on their potential impact . 4. **Risk mitigation:** Implementing corrective actions to reduce identified risks. Strategies include diversifying the supplier base, building strong supplier relationships, shortening the supply chain (e.g., nearshoring), simplifying product design, closely monitoring performance, developing contingency plans, and implementing strategic safety stocks. Basic risk mitigation strategies encompass avoidance, reduction, transference, and acceptance . 5. **Risk monitoring:** Regularly reviewing and updating the risk assessment and prioritization . ### 3.4 New supply chain challenges and requirements Modern supply chains face evolving challenges and demand new capabilities, primarily centered around resilience and sustainability. #### 3.4.1 Key challenges Current challenges include: * **Supply Chain Complexity:** The inherent intricacy of global networks . * **VUCA World:** Operating in an environment characterized by Volatility, Uncertainty, Complexity, and Ambiguity . * **Climate Change:** The growing impact of climate-related events on supply chain operations . * **Regulatory Compliance:** Adhering to increasingly stringent regulations concerning environment, labor, and social issues . #### 3.4.2 New requirements These challenges necessitate new requirements for supply chains: * **Resilience:** An increased ability to resist disruptions and recover effectively from them . * **Sustainability:** A focus on reducing environmental impact and improving social and economic outcomes throughout the supply chain . --- # Sustainability and resilience in supply chains This section explores the growing importance of sustainable and resilient supply chains, driven by various pressures and encompassing concepts like the Doughnut Economy and circular economy, alongside environmental management systems and sustainable sourcing practices. ### 4.1 Motivations for sustainable and resilient supply chains There is increasing pressure on companies to adopt sustainable and resilient supply chains due to several key factors. The political landscape is evolving, with governments worldwide imposing stricter regulations on businesses to reduce their environmental impact, exemplified by requirements like the German Supply Chain Due Diligence Act (Lieferkettengesetz). Furthermore, investors and customers are increasingly demanding that companies operate in a socially responsible and sustainable manner, reflecting a growing emphasis on social and ethical responsibility. The frequency and unpredictability of disruptions, such as those caused by climate change, geopolitical tensions, and global health crises, also highlight the need for resilience. Adopting sustainable and resilient solutions can significantly reduce a company's risk exposure to increasingly complex supply chains and mitigate reputational damage by fostering a positive social and ethical brand image. Ultimately, embracing sustainable solutions is viewed as a long-term investment for businesses . Supply chains are substantial contributors to global greenhouse gas emissions, accounting for over 50% through transportation, industrial processes, and energy consumption. The rapid increase in these gases is a primary driver of global warming and climate change . The depletion of natural resources poses a significant threat to the global economy, leading to increased costs and economic instabilities. Traditional economic models often fail to account for the long-term value of natural resources beyond near-term cash flows, focusing instead on resource abundance and limited environmental concerns. This short-term focus is increasingly being challenged by the need for more sustainable economic thinking . ### 4.2 Sustainability concepts and tools Sustainability is defined as meeting present needs without compromising the ability of future generations to meet their own needs. This concept is supported by several interconnected frameworks and goals . #### 4.2.1 The 17 sustainable development goals The United Nations' 17 Sustainable Development Goals (SDGs), established in 2015, provide a comprehensive blueprint for peace and prosperity. These goals offer a holistic approach encompassing societal, technical, and economic aspects. Several SDGs have direct relevance to supply chain management : * **Goal 8 (Decent Work and Economic Growth):** Supply chains are major employers in manufacturing, logistics, and retail . * **Goal 9 (Industry, Innovation and Infrastructure):** Efficient and resilient infrastructure is crucial for supply chains, which also drive innovation in logistics and technology . * **Goal 12 (Responsible Consumption and Production):** Supply chains are central to production and consumption patterns . * **Goal 13 (Climate Action):** Supply chains significantly contribute to greenhouse gas emissions through various activities . * **Goal 17 (Partnerships for the Goals):** Achieving sustainable supply chains necessitates collaboration among all partners . #### 4.2.2 Renewable vs. non-renewable resources Resources can be classified as renewable, meaning they can be replenished naturally, or non-renewable, which are finite and cannot be replaced. Sustainable practices involve increasing the use of renewable resources and reducing the use and increasing the recycling of non-renewable resources . * **Renewable Resources:** Solar energy, wind energy, hydropower, geothermal energy, and biomass . * **Non-renewable Resources:** Fossil fuels (coal, oil, natural gas), nuclear energy (uranium, thorium), minerals and metals, non-metallic minerals, precious stones, and peat . Recyclability varies significantly. Paper, cardboard, glass, and certain plastics can be recycled. However, recycling complex items like electronics and batteries, particularly lithium-ion batteries which require high-temperature pyrometallurgical processes, is challenging. Used motor oil can be re-refined for reuse . #### 4.2.3 Doughnut economics Doughnut Economics provides a visual framework for sustainable development, aiming to meet human needs within the planet's ecological limits. It balances social foundations with ecological ceilings. The framework considers four key lenses for sustainable development within a specific place, integrating local needs and global responsibilities : * **Local Social Lens:** Addresses the well-being needs of the community (e.g., food, healthcare, education) . * **Global Social Lens:** Examines the community's impact on global well-being, including social justice and fair trade . * **Local Ecological Lens:** Assesses the health of the local environment and the impact of human activities like pollution and resource depletion . * **Global Ecological Lens:** Evaluates how local production and consumption patterns affect global resources and pollution . #### 4.2.4 Circular economy The circular economy aims to eliminate waste and pollution, keep products and materials in use, and regenerate nature. This contrasts with the linear economic system, often termed a "throwaway society". Key principles include : * **Eco-design for circular production:** Designing products with considerations for resource minimization, repairability, reusability, and recyclability throughout their lifecycle . * **Circulate products and materials:** Maximizing product lifespan through sharing, reusing, repairing, and refurbishing . * **Regenerate nature:** Restoring and revitalizing ecosystems, natural resources, and biodiversity . * **Eliminate waste and pollution:** Minimizing waste generation and the release of harmful pollutants throughout the product lifecycle . The circular economy is considered essential for a sustainable future, promoting more efficient resource utilization . ### 4.3 Sustainable supply chains Sustainable supply chains integrate Environmental, Social, and Corporate Governance (ESG) considerations into all aspects of operations . #### 4.3.1 Environmental, Social, and Corporate Governance (ESG) issues ESG issues encompass a broad range of factors impacting a company's long-term performance . * **Environment and Sustainability:** Includes deforestation, greenhouse gas emissions, carbon emissions, resource depletion, water shortages, pollution, waste, disposal, climate change, endangered species, biodiversity, and ocean health . * **Social:** Pertains to adherence to International Labour Organization (ILO) standards, worker exploitation, slavery and forced labour, working conditions, conflict minerals, health and safety, living wages, good citizenship (social justice, human rights, diversity, inclusion), local jobs, and restricted substances . * **Governance:** Covers corruption and bribery, executive and employee income inequality, political activism, lobbying, taxes, and dumping . Addressing ESG issues effectively helps companies mitigate risks, attract investors and customers, and build a stronger reputation . #### 4.3.2 Reducing the transport-intensity of supply chains Minimizing transportation in supply chains directly lowers the carbon footprint, as transport consumes a significant amount of oil daily. Strategies to achieve this include : * **Reviewing product designs and bills of materials:** Focus on improved life-cycle characteristics, reduced packaging, and lighter product designs . * **Reviewing sourcing strategy:** Employing near-shoring and local suppliers . * **Reviewing transport options:** Utilizing newer, more efficient container ships . * **Improving transport utilization:** Increasing the use of shared distribution and optimizing vehicle routes to reduce empty runs . * **Using postponement strategies:** Assembling and customizing products closer to the point of use (finish-to-order) . #### 4.3.3 Sustainable solutions in supply chain processes Optimizing the entire supply chain, following frameworks like SCOR (Supply Chain Operations Reference model), can incorporate sustainability at each stage . * **Plan:** Avoid over-production, favor pull over push strategies, and practice collaborative planning; minimize inventory levels and safety stocks . * **Source:** Prioritize near-shoring and suppliers committed to sustainability; engage in ethical sourcing, considering labor standards, legal compliance, and fair trade . * **Make:** Improve energy efficiency and overall equipment efficiency (OEE); reduce waste, rework, and scrappage; minimize pollution and emissions . * **Deliver:** Optimize network configurations, minimize transport intensity and packaging waste (especially plastics); utilize sustainable transportation methods . * **Return:** Manage product end-of-life effectively and facilitate product returns for repair or recycling . * **Enable:** Invest in energy-efficient technology, provide sustainability training to employees, and cultivate a culture of sustainability within the organization . ### 4.4 Resilient supply chains Resilient supply chains possess the capacity to withstand, adapt to, and recover quickly from disruptions. Transparency throughout the supply chain is critical for identifying and addressing potential risks, enabling effective contingency planning . #### 4.4.1 Avoiding vulnerable supply chain structures Diamond-shaped supply chains, which can be efficient in the short term, are highly vulnerable to disruptions. This structural vulnerability is evident in the shortages of critical components like semiconductor chips, rare earth metals, lithium, and cobalt for lithium-ion batteries. Building redundancy and diversifying the supply base are key strategies to mitigate such risks . ### 4.5 Examples of sustainable products and services Several companies exemplify successful integration of sustainability into their products and services. * **Fairphone:** This company is a benchmark for sustainable products, focusing on ethical sourcing of conflict-free minerals, designing for repairability and longevity with available spare parts, ensuring supply chain transparency through cost breakdowns and supplier lists, and implementing social assessment programs for suppliers with worker welfare funds. Products are also designed for reuse and safe recycling . * **Too Good To Go:** This app connects consumers with restaurants and bakeries offering surplus food at discounted prices, thereby preventing food waste. It is estimated that 40% of food goes to waste. The platform provides an end-to-end solution for retailers to manage surplus food, and its consumer app has a large user base . * **Who Gives A Crap:** This company produces toilet paper and tissues from 100% recycled materials or bamboo. It donates 50% of its profits to build toilets in developing countries, addressing the critical issue that 2.4 billion people lack access to sanitation. Their operations also emphasize ethical sourcing, fair trade, and reduced transport intensity . ### 4.6 Environmental Management Systems (EMS) Environmental Management Systems (EMS) provide a structured approach to managing an organization's environmental impacts. #### 4.6.1 ISO 14001 ISO 14001 is an internationally recognized standard for EMS. While not mandatory, it offers significant benefits for organizations seeking to improve their environmental performance . * **Benefits of ISO 14001:** * **Reduced environmental impact:** Leads to greater resource efficiency and reduction in waste and pollution . * **Competitive advantage:** Many customers and suppliers prefer certified organizations . * **Cost savings:** Achieved through reduced energy and water consumption . * **Improved reputation:** Enhances brand image and attractiveness to talent . * **Legal compliance:** Ensures adherence to an increasing number of environmental regulations . * **Reduced risk:** Minimizes the likelihood of environmental incidents or accidents . ISO 14001 is based on a **continuous improvement process** following the Plan-Do-Check-Act (PDCA) cycle. Its key elements include : * **Leadership:** Top management commitment and provision of necessary resources for the EMS . * **Planning:** Development of objectives and targets for environmental performance improvement . * **Support:** Provision of required resources (human, financial, technical) and ensuring employee competence in environmental responsibilities . * **Operation:** Defining procedures to manage environmental aspects of products, activities, and services, and planning for environmental emergencies . * **Performance evaluation:** Monitoring, measuring, analyzing, and evaluating operations for significant environmental impacts; ensuring compliance with legal requirements through audits . * **Improvement:** Implementing corrective actions for continual improvement of the EMS . Organizations implementing ISO 14001 can effectively demonstrate their commitment to sustainable practices and environmental responsibility . ### 4.7 Summary of key takeaways The motivation for sustainable and resilient supply chains stems from increasing environmental regulations, a demand for social and ethical responsibility, and the need for an improved reputation, ultimately leading to a competitive advantage. The imperative is driven by Environmental, Social, and Corporate Governance (ESG) issues. Sustainable supply chains focus on reducing transport intensity and waste, embracing circular economy principles. Supply chain resilience involves avoiding inherently vulnerable structures like diamond-shaped supply chains. ISO 14001 provides a framework for continuous improvement through leadership, support, operations, and performance evaluation . --- # Forecasting customer demand and managing supply chain dynamics Forecasting customer demand and understanding supply chain dynamics are crucial for effective supply chain management, aiming to predict future demand and mitigate amplification of variability within the chain . ### 5.1 Forecasting customer demand Forecasting customer demand involves utilizing historical data and analytical models to predict future sales and consumption patterns . #### 5.1.1 Challenges in forecasting Several factors make forecasting a challenging task : * **Historical data quality:** Forecasts rely on historical data, which can be compromised by: * **Inaccurate or incomplete data:** Due to human errors, data entry mistakes, or technical issues . * **Inconsistent data:** Collected using different methods or from various sources . * **Outliers:** Data points that significantly deviate from the norm . * **Choice of forecasting technique:** Selecting the appropriate technique for a given demand pattern is not always straightforward . * **Business complexity:** Globalized supply chains and an increasing number of disruptive events make long-term predictions difficult . * **Bullwhip effect:** Demand variability can amplify as it moves upstream in the supply chain, leading to erratic demand for suppliers . The "forecastability" of businesses has declined, with supply chain forecastability dropping significantly and planning errors increasing, especially post-pandemic. Traditional forecasting assumptions that history repeats itself are no longer sufficient given the prevalence of major disruptions . #### 5.1.2 Fundamental laws of forecasting There are three fundamental laws that guide the understanding and application of forecasting : 1. **Forecasts are always wrong:** Perfect prediction is impossible because the past does not perfectly replicate the future . 2. **Detailed forecasts are worse than aggregate forecasts:** Aggregated forecasts (e.g., for a product family) show less variability than detailed forecasts (e.g., for an individual product) due to variability pooling . 3. **The further into the future, the less reliable the forecasts will be:** Increased time horizons amplify the potential for changes, such as new product introductions by competitors . > **Tip:** Always acknowledge that forecasts are estimates and should be used with caution and a clear understanding of their limitations. #### 5.1.3 Forecasting techniques Forecasting methods can be broadly categorized into qualitative and quantitative approaches, with combined methods often yielding the most accurate results . ##### 5.1.3.1 Qualitative forecasting methods These methods rely on expert judgment and opinions rather than strict mathematical models . * **Delphi:** Involves querying a panel of experts about future developments in areas like technology, competition, and market evolution . * **Market research:** Utilizes data from customer surveys and other market intelligence gathering . * **Sales force composite:** Aggregates forecasts provided by individual members of the sales force . ##### 5.1.3.2 Quantitative forecasting methods These methods employ historical data and mathematical models to project future values . ###### 5.1.3.2.1 Time series forecasting Time series forecasting uses historical data to identify patterns that are expected to recur in the future . * **Naïve Forecast (Last Value Forecast):** Predicts the future value based on the most recent historical data point. It's often used as a benchmark . Let $Y_i$ be the data for period $i$, and $N_i$ be the Naïve Forecast for period $i$. $N_i = Y_{i-1}$ . * **Moving Average (MA):** Calculates the average of a fixed number of the most recent data points. It's typically used for short-term forecasts . The Moving Average forecast for period $i$ with a window of $k$ periods is: $$MA_i = \frac{1}{k} \sum_{j=i-k}^{i-1} Y_j$$ . * **Weighted Moving Average (WMA):** Similar to a simple moving average, but assigns different weights to past data points, giving more importance to recent values . The Weighted Moving Average forecast for period $i$ with $k$ periods and weights $w_1, w_2, \dots, w_k$ is: $$WMA_i = \sum_{j=1}^{k} w_j Y_{i-j}$$ where $\sum_{j=1}^{k} w_j = 1$ . * **Single Exponential Smoothing (SES):** A method that gives exponentially decreasing weights to older observations. It's suitable for short-term forecasts . The forecast for period $i$ is: $$SES_i = \alpha Y_{i-1} + (1-\alpha) SES_{i-1}$$ . The smoothing constant $\alpha$ determines how quickly older responses are dampened. A higher $\alpha$ means faster dampening . * **Double Exponential Smoothing (DES):** Extends SES to incorporate a trend component, making it suitable for data exhibiting a trend. It uses two smoothing constants: $\alpha$ for the level and $\beta$ for the trend . * **Triple Exponential Smoothing (TES):** Further extends DES to account for seasonality or periodicity, making it appropriate for data with repeating patterns over time. It involves three smoothing constants: $\alpha$ for the level, $\beta$ for the trend, and $\gamma$ for the seasonality . ###### 5.1.3.2.2 Causal forecasting Causal forecasting seeks to explain future demand based on relationships with other observable and predictable factors . * **Linear Regression (LR):** A simple causal model that establishes a linear relationship between a dependent variable (demand) and one or more independent variables (e.g., marketing spend, economic indicators) . The general form is: $$Y = b_0 + b_1 X_1 + b_2 X_2 + \dots$$ . For a simple linear regression with one independent variable $X$ and dependent variable $Y$: $$Y = \alpha + \beta X$$ . where $\alpha$ is the intercept coefficient and $\beta$ is the slope coefficient. Linear regression is often used to define long-term trends . #### 5.1.4 Forecasting methodology A systematic methodology is essential for effective forecasting . ##### 5.1.4.1 Preliminary analysis The first step involves visually analyzing the historical data to identify its nature, including patterns, trends, seasonality, or cycles . * **Typical time series patterns:** * **Linear:** Constant evolution of data . * **Trend:** Long-term upward or downward movement . * **Seasonality:** Repeating patterns within a specific period (day, week, month, year) . * **Cycles:** Medium to long-term fluctuations over extended periods . * **Random:** Unexplained variations in the data . ##### 5.1.4.2 Choosing and fitting models Based on the identified demand patterns, an appropriate forecasting model is selected, and its parameters are optimized to minimize forecast error . * **Common model choices by pattern:** * **Linear:** Linear Regression (LR), Moving Average (MA), Single Exponential Smoothing (SES) . * **Trend:** Linear Regression (LR), Double Exponential Smoothing (DES) . * **Seasonality:** Triple Exponential Smoothing (TES), Linear Regression (LR) for trend . * **Cycles:** Triple Exponential Smoothing (TES), Linear Regression (LR) for trend . * **Random:** May require verification of data quality or investigation for the bullwhip effect . * **Measures of forecast error:** * **Mean Absolute Deviation (MAD):** The average of the absolute differences between actual and forecasted values . $$MAD = \frac{1}{n} \sum_{i=1}^{n} |Y_i - F_i|$$ . * **Mean Square Error (MSE):** The average of the squared differences between actual and forecasted values . $$MSE = \frac{1}{n} \sum_{i=1}^{n} (Y_i - F_i)^2$$ . * **Forecast Bias (BIAS):** The average of the differences between actual and forecasted values, indicating a systematic over- or under-forecasting tendency . $$BIAS = \frac{1}{n} \sum_{i=1}^{n} (Y_i - F_i)$$ . * **Model parameter optimization:** Techniques like the train-test procedure are used to choose model parameters that minimize forecast error on both historical (training) and unseen (testing) data. Specialized software can automate this optimization process . ##### 5.1.4.3 Using and evaluating forecasting models Continuously monitoring the forecast quality and adjusting model parameters or techniques as needed is crucial for maintaining accuracy. Dashboards or "cockpits" are often used to visualize actual demand against forecasts from different models . ### 5.2 Supply chain dynamics and the bullwhip effect Supply chain dynamics refers to the behavior and interrelationships within a supply chain over time, characterized by time delays, demand variability, and inventory levels acting as buffers . #### 5.2.1 The bullwhip effect The bullwhip effect describes the phenomenon where demand variability increases as one moves upstream in the supply chain, from the retailer to the wholesaler, distributor, and finally to the manufacturer. This amplification leads to more erratic and unpredictable demand for upstream partners . > **Example:** A small fluctuation in customer demand at the retail level can lead to much larger fluctuations in orders placed by the retailer with their wholesaler, by the wholesaler with their distributor, and by the distributor with the manufacturer. #### 5.2.2 Causes of the bullwhip effect The primary cause of the bullwhip effect is often the "bad" design of the supply chain itself, specifically related to a lack of integration and collaboration among its actors. Other contributing factors include : * **Order batching:** Companies ordering in large, infrequent batches to reduce ordering costs or gain volume discounts. * **Price fluctuations/promotions:** Retailers buying in anticipation of price changes or sales events, creating artificial demand spikes. * **Rationing and shortage gaming:** When demand exceeds supply, manufacturers may ration products, leading customers to inflate their orders to secure a larger share. * **Demand forecast inaccuracies:** Each stage in the supply chain forecasts demand independently based on orders received from the next stage downstream, leading to amplified errors. * **Lead times:** Longer lead times between placing an order and receiving it encourage larger safety stock and order quantities to buffer against uncertainty. #### 5.2.3 Strategies for reducing the bullwhip effect Mitigating the bullwhip effect requires a focus on improving supply chain integration, visibility, and responsiveness. Key strategies include : * **Reducing lead times:** Shorter lead times lessen the need for excessive inventory and reduce the time for forecast errors to propagate . * **Avoiding aggressive promotions:** Stabilizing pricing and demand by limiting deep discounts or promotional activities that create artificial demand spikes . * **Collaborative planning and information sharing:** Implementing systems like Vendor Managed Inventory (VMI) or sharing real-time sales data (Point of Sale - POS data) across the supply chain. This improves visibility and allows for more accurate demand forecasting and planning at all levels . * **Improving forecasting methods:** Using more sophisticated forecasting techniques and sharing demand information upstream . * **Stable pricing:** Implementing everyday low pricing strategies instead of relying on frequent promotions . > **Tip:** The bullwhip effect is a systemic issue. Addressing it requires collaborative efforts and a shift in mindset from individual optimization to supply chain-wide efficiency. --- **Summary of Key Points:** * **Challenges:** Data quality, model selection, business complexity, bullwhip effect . * **Laws of Forecasting:** Always wrong, aggregates are better than details, future is less reliable . * **Techniques:** Qualitative (Delphi, market research) and Quantitative (Time Series: Naïve, MA, WMA, SES, DES, TES; Causal: LR) . * **Methodology:** Analyze demand, select/fit model, use/evaluate . * **Error Metrics:** MAD, MSE, BIAS . * **Supply Chain Dynamics:** Delays, variability, buffers . * **Bullwhip Effect:** Demand variability amplification upstream . * **Bullwhip Causes:** Lack of integration, order batching, promotions, etc . * **Bullwhip Mitigation:** Reduce lead times, stable pricing, collaboration . --- # Demand management, planning, outsourcing, and inventory optimization This topic integrates demand management processes, Sales & Operations Planning (S&OP), outsourcing strategies, and inventory management techniques like Economic Order Quantity (EOQ) and Economic Production Quantity (EPQ), along with safety stock management . ### 9.1 Demand management Demand management is a crucial part of the Sales & Operations Planning (S&OP) process. It involves understanding demand drivers and characteristics, forecasting, aligning, and monitoring demand. The demand management process consists of several key steps : #### 9.1.1 Demand data collection and analysis This initial step focuses on gathering and analyzing demand data. Key considerations include: * **Demand Data Sources:** Data can be collected from customer orders, sales history, point-of-sale (POS) data, market research, supply chain and distribution data, and external factors like macroeconomic indicators . * **Dependent vs. Independent Demand:** Independent demand is for finished goods driven by customer needs, while dependent demand is for components or raw materials derived from finished product demand . * **Constrained vs. Unconstrained Demand:** Constrained demand is what can realistically be fulfilled, considering capacity and supply limitations, while unconstrained demand represents total customer demand without restrictions. Historical sales data typically reflects constrained demand . * **Outliers:** Significant deviations from regular demand patterns can be caused by data entry errors, special events, or product changes, which can distort statistical forecasts. Cleaning outliers can reduce forecast errors . * **Supply Chain Position:** A company's position in the supply chain influences its ability to estimate actual customer demand due to lack of visibility, delayed information, and order batching practices like Economic Order Quantity (EOQ) . #### 9.1.2 Customer and product segmentation Segmentation helps in understanding customer and product behavior to achieve more accurate forecasts and targeted strategies . * **Multi-criteria ABC Analysis:** This categorizes products or services based on their importance to the business, often following the Pareto Principle (80% of effects from 20% of causes) . * **XYZ Analysis:** This measures the variability of customer demand, categorizing items based on their Coefficient of Variation (CV) . * Low variability: CV < 0.75 * "Normal" variability: 0.75 ≤ CV ≤ 1.25 * High variability: CV > 1.25 * **Product Life Cycle:** The product life cycle (Introduction, Growth, Maturity, Decline) significantly impacts business decisions and demand patterns . * **Combined ABC-XYZ Analysis:** This combines volume (ABC) and variability (XYZ) to create strategic product groups like A-X (high volume, stable demand), B-Y (medium volume, unstable demand), and C-Z (low volume, unpredictable demand) . * **Strategic Product Groups:** These include New (N), Runner, Repeater, Stranger, After Sales (AS), and Obsolete (O) products, guiding production, inventory, and distribution strategies . * **A1B2 Analysis:** This is a Pareto analysis of product-customer pairs, prioritizing based on sales volume for both products and clients, simplifying priority choices . #### 9.1.3 Demand forecasting Forecasting estimates future customer demand, utilizing both quantitative and qualitative methods . * **Quantitative Forecasting:** Employs statistical methods such as single, double, and triple exponential smoothing . * **Forecastability:** It is important to avoid forecasting products with unstable demand (e.g., Z-products) to save time and money . * **Qualitative Forecasting:** Relies on "best guesses" from market research, industry experts, and sales force input . * **Influencing Demand:** Understanding and implementing strategies that actively influence demand is also part of this step, involving sales, marketing, and new product development input. Regular reviews and feedback between forecasters and sales/marketing teams are essential . #### 9.1.4 Demand alignment and validation This step ensures cross-functional alignment and validation of demand forecasts, consolidating information. A "sanity check" procedure is used for strategic product families to consolidate available demand information . #### 9.1.5 Choosing demand fulfilment strategies This involves selecting appropriate order fulfillment strategies based on lead-time management and product segmentation . * **Make-to-Stock (MTS):** Production occurs before actual demand. * **Finish-to-Order (FTO):** Final assembly or finishing occurs after an order is placed. * **Make-to-Order (MTO):** Production begins after an order is received. * **Engineer-to-Order (ETO):** Design and production are initiated after an order . Strategic product groups influence the choice of fulfillment strategy, for example, A-products often utilize a Make-to-Stock strategy . #### 9.1.6 Communicating and monitoring demand Demand cockpits are used as primary communication tools, summarizing critical information about past performance (production, sales, inventory) and future plans (orders, forecasts). They typically cover a time horizon of plus and minus 12 months and include product classifications and planning parameters like lot sizes and safety stocks . ### 9.2 Sales and Operations Planning (S&OP) Sales & Operations Planning (S&OP) is a medium- to long-term planning process that integrates financial, sales, marketing, and operations plans. It aims to maintain a long-term balance between customer demand and available resources (supply) . * **Hierarchical Planning:** S&OP is the top level of a hierarchical planning structure, followed by Master Production Scheduling (MPS) and Material Requirements Planning (MRP) . * **S&OP:** Focuses on product families and bottlenecks over a 3–24 month timescale. * **MPS:** Deals with finished products and job shops over 1–3 months. * **MRP:** Manages components and raw materials and operations over 1–4 weeks. * **S&OP Process:** It's a monthly decision-taking and communication process with five steps : 1. Updating data and maintaining the process. 2. Demand planning (based on sales/marketing input and statistical forecasts). 3. Supply planning (to meet demand forecasts). 4. Partnership meeting (aligning supply and demand). 5. Executive meeting (approving plans and making decisions). * **S&OP Displays:** These are the primary communication tools, summarizing critical information per product grouping, typically for a 12-month horizon, including capacity, sales, and inventory levels. The focus of the display varies by environment, such as inventory levels for Make-to-Stock (MTS) backlog and lead time for Make-to-Order (MTO) and human workforce capacities for Engineer-to-Order (ETO) . ### 9.3 Outsourcing and supplier management Outsourcing is the transfer of management and delivery of a process to a third party. Key reasons for outsourcing include cost reduction, increased flexibility, focusing on core competencies, and mitigating risks . #### 9.3.1 Outsourcing procedure The outsourcing procedure involves selecting, managing, and developing suppliers . * **Selecting:** Criteria include order qualifiers (minimal requirements like quality certifications, delivery lead times, financial capabilities) and landed costs, which encompass all costs associated with sourcing and receiving products, not just purchase price. Landed costs can reveal "hidden" costs such as freight, carrying costs, duties, and packaging. Supply risks and profit impact are analyzed using frameworks like the Kraljic Matrix . * **Managing:** This involves establishing a Service Level Agreement (SLA), a contractual agreement defining expected performance and service levels, including scope of service, responsibilities, and performance metrics . * **Developing:** This focuses on integration, collaboration, and mutual development between partners . #### 9.3.2 Reasons for outsourcing failures Common reasons for outsourcing failures include erosion of standards, hidden costs, communication delays, and cultural differences . #### 9.3.3 Kraljic Matrix The Kraljic Matrix helps optimize supplier relationships by categorizing items based on supply risk and profit impact, guiding differentiated partnership approaches . ### 9.4 Inventory optimization Inventory optimization aims to find the perfect balance between various costs to minimize overall expenses while meeting demand. #### 9.4.1 Economic Order Quantity (EOQ) The EOQ model determines the optimal order quantity to minimize the sum of inventory holding costs and purchasing costs, assuming deterministic and constant demand . * **Inventory Holding Costs (CS):** Include storage, insurance, obsolescence, capital, shrinkage, and labor costs. Estimated at 20-40% of inventory value . * **Purchasing Costs (CP):** Include shipping, handling, system fees, travel, and labor costs for purchasers . * **Formula:** The EOQ is calculated as: $$EOQ = \sqrt{\frac{2 \times D \times C_P}{C_S}}$$ Where: * $D$ = Yearly Demand rate [units/year . * $C_P$ = Purchasing costs per lot [currency . * $C_S$ = Inventory costs per unit and year [currency/unit/year . * **Reorder Point (r):** The inventory level at which a new order should be placed: $$r = d \times LT$$ Where: * $d$ = demand rate [units/time unit . * $LT$ = Order delivery lead time [time unit . #### 9.4.2 Economic Production Quantity (EPQ) The EPQ model is used when a company produces items internally and aims to find the optimal production lot size that minimizes the sum of inventory holding costs and production setup costs . * **Setup Costs (CL):** Include costs for reconfiguring, calibrating, tooling, and lost production time for new production runs . * **Formula:** The EPQ is calculated as: $$EPQ = \sqrt{\frac{2 \times D \times C_L}{C_S \times (1 - \frac{d}{p})}}$$ Where: * $D$ = Yearly Demand rate [units/year . * $C_L$ = Production launch or setup costs [currency . * $C_S$ = Inventory costs per unit and year [currency/unit/year . * $d$ = Demand rate [units/time unit . * $p$ = Production rate [units/time unit . #### 9.4.3 Safety stock management Safety stock is held to prevent stockouts due to variability in demand and/or lead times . * **Underlying Concepts:** Safety stock is based on the assumption of variable demand and deliveries, often modeled using a Gaussian (Normal) distribution. The goal is typically to prevent stockouts in a certain percentage of cycles (e.g., 95%) rather than eliminating them entirely . * **Z-score:** The z-score standardizes a normal distribution, allowing for calculations based on service level percentages. Typical z-scores for service levels include 1.281 for 90% and 1.645 for 95% . * **Calculating Safety Stock:** * **Variable demand, fixed lead time:** $$SS_{d} = z \times \sqrt{LT \times T_i} \times \sigma_{D}$$ Reorder point $r = LT \times d_{avg} + SS_{d}$ . Where $T_i$ is the time increment for calculating the standard deviation of demand. * **Variable lead time, fixed demand:** $$SS_{LT} = z \times d \times \sigma_{LT}$$ Reorder point $r = LT_{avg} \times d + SS_{LT}$ . * **Variable demand and lead time (independent):** $$SS_{dL T} = z \times \sqrt{LT_{avg} \times \sigma_{D}^2 + d_{avg}^2 \times \sigma_{LT}^2}$$ Reorder point $r = LT_{avg} \times d_{avg} + SS_{dL T}$ . * **Role of Inventory:** Inventories are considered wastes in Lean methodology as they hide problems. However, they are necessary to buffer against uncertainty, smooth production and supply, meet customer expectations, and achieve economies of scale . --- # Digitalisation and emerging trends in supply chains This topic explores the evolution towards "Supply Chain 4.0," driven by digital technologies such as the Internet of Things (IoT), Blockchain, and Artificial Intelligence (AI), and examines their impact on supply chain operations and emerging trends . ### 7.1 Supply Chain 4.0 Supply Chain 4.0 represents the digital transformation of supply chains, moving beyond traditional integrated data sharing to a highly connected and collaborative network. This evolution is characterized by several major trends : #### 7.1.1 Key trends in Supply Chain 4.0 * **Internet of Things (IoT):** This involves interconnected physical devices with embedded computing capabilities that exchange data and information over a network, forming what is sometimes referred to as the "physical internet" . * **Characteristics:** IoT enables a worldwide, hyperconnected network that is physically, digitally, and operationally integrated. Information is transmitted via data packets, with a focus on reliable and uncompromised delivery . * **Applications:** * **Smart and modular containers:** Digitally connected containers with sensors, designed for efficient storage, handling, and transport (e.g., foldable and stackable) . * **Agnostic hubs and logistics infrastructure:** Facilitates data exchange (e.g., inventory levels, sales statistics) across open networks . * **Hyperconnected transportation networks:** Seamless transfer of shipments between various modes of transport (airplanes, ships, trains, trucks, etc.) using modular container sizes . * **Blockchain technology:** This is a decentralized, digitally recorded ledger system for transactions that is distributed across networks . * **Use cases:** Supply chain management (visibility, anti-counterfeiting), digital identity, voting, fundraising, healthcare records, notary services, food safety, intellectual property certification, and energy market trading . * **Example:** IBM Food Trust utilizes blockchain to enhance visibility and accountability in the food supply chain by connecting growers, processors, distributors, and retailers with a shared, permanent record of data . * **Next-generation packaging:** Involves packaging materials that are more sustainable (bio-based, recyclable, reusable, biodegradable) and incorporate IoT technology to monitor package conditions . * **Examples:** Smart transportation boxes with sensors to monitor temperature, humidity, and shock. Modified atmosphere packaging (MAP) to extend shelf life by altering the gas composition within the package . * **Circularity:** Focuses on eliminating waste and pollution by considering the entire product lifecycle, encompassing reuse, repair, remanufacturing, and recycling . * **Big-data Analytics:** The analysis of large volumes of supply chain data to derive insights . * **3D-Printing (Additive Manufacturing):** A production process that fabricates 3D objects from digital models by adding materials layer by layer, commonly used for prototyping . * **Bio-based materials:** Materials derived from sustainable biomass or modern bio-synthetic processes . * **Outdoor Autonomous Vehicles:** Self-driving robots designed for operation outdoors on land or water, in both private and public areas . * **Alternative Energy Solutions:** Utilization of energy from renewable and inexhaustible sources . ### 7.2 Artificial Intelligence (AI) in Logistics AI in logistics offers significant opportunities but is also accompanied by hype and high expectations . #### 7.2.1 Application Domain of AI Solutions The application domain of AI in Supply Chain Management (SCM) is influenced by data availability, the nature of tasks (repeated vs. complex), and the process flow. AI is particularly effective for : * **Process tasks:** Repeated activities and complex patterns . * **Data availability:** AI thrives on large datasets . * **Personalization/customization:** AI enables higher levels of tailored solutions . AI solutions can be applied across various stages of the supply chain, from raw material suppliers to distributors and finished products, impacting purchasing, production, logistics, and sales . > **Tip:** AI solutions in SCM are most impactful when dealing with repetitive tasks, complex patterns, and ample available data, enabling greater personalization and automation. #### 7.2.2 AI Application: Forecasts AI models, particularly supervised machine learning algorithms, can significantly enhance demand forecasting accuracy compared to traditional statistical methods . * **AI Models:** * **ExtraTrees (Extremely Randomized Trees):** Uses decision trees to make predictions . * **Multi-layer Perceptron Regressor (Neural Networks/Deep Learning):** Leverages neural networks for complex pattern recognition . * **Prophet:** A forecasting model developed by Meta (Facebook) . * **Advantages over Statistical Forecasts:** AI models can easily incorporate external factors (e.g., promotions, weather, GDP growth) and categories, which are often challenging for traditional methods like linear regression or triple exponential smoothing . * **Performance Analysis:** * For "perfect" data, most forecasting models are expected to perform well . * For "complex" data, certain AI models (e.g., TREE) can outperform other forecasting models in terms of Mean Absolute Error (MAE%) and Bias (BIAS%) . * For "real" data (which is often incomplete or biased), all forecasting models tend to yield similar, less accurate results, highlighting the "garbage in, garbage out" principle . #### 7.2.3 AI Application: Computer Vision Computer vision is a critical technology enabling AI and robotics to "understand" images and videos, essential for collecting data from various sources . * **Applications:** * **Fully autonomous yard operations:** Example: ISEE in Texas, US . * **Fully autonomous warehousing:** Example: JD.com in Shanghai, China . * **Fully autonomous delivery systems:** Example: Various companies in San Francisco, US . #### 7.2.4 Opportunities of AI in Logistics AI integration with Big Data (orders, forecasts, operational data, inventory levels) can lead to fully integrated supply chains (Supply Chain 4.0) by enabling: * Automated logistics systems . * Copilots and assistants for decision-making . * Enhanced capabilities in purchasing, planning, and sales . #### 7.2.5 Risks of AI in Logistics * **Cybersecurity Threats:** Supply chains are vulnerable to cyberattacks due to interconnectedness with external suppliers and non-unified software systems. Examples include attacks on Australian ports and carrier companies . * **Data Privacy and Ownership:** The pervasive collection of data from users, workers, and clients raises concerns about data ownership, sharing practices, and usage . > **Example:** The cyberattack on Australian ports in 2023, which blocked operations for several days, demonstrates the significant risk posed by cyber threats to modern, interconnected supply chains . ### 7.3 Summary and Emerging Trends The evolution of supply chains is depicted as a progression from reactive and informal enterprises to proactive, productive, sustainable, and networked structures. The ultimate aim is a "Circular Enterprise" characterized by a worldwide highly connected network and collaborative Sales & Operations Planning (S&OP) . #### 7.3.1 Progression of Supply Chain Maturity * **Functional Enterprise:** Focuses on order management, with service, cost, and quality indicators . * **Performing Enterprise:** Utilizes Material Requirements Planning (MRP) and addresses productivity indicators . * **Integrated Enterprise:** Employs Sales & Operations Planning (S&OP) and global indicators for collaborative planning . * **Networked Enterprise:** Leverages collaborative S&OP planning and global indicators within a worldwide, highly connected network . * **Circular Enterprise:** Embodies the principles of the circular economy, aiming for sustainability and waste elimination . #### 7.3.2 Future Considerations for AI in SCM When considering the future availability of AI-based solutions for supply chain operations, key questions include: * Is data available and can it be collected? . * Are the tasks repetitive and do they exhibit (complex) patterns for learning? . AI is expected to influence logistics significantly in both the short and long term . --- ## Common mistakes to avoid - Review all topics thoroughly before exams - Pay attention to formulas and key definitions - Practice with examples provided in each section - Don't memorize without understanding the underlying concepts

| Term | Definition | |---|---| | Supply Chain Management (SCM) | A broader, intercompany concept that involves the management of the flow of goods and services, from raw materials to the end consumer, encompassing all processes that transform and deliver these products and services. | | Logistics | The process of organizing the transportation and storage of goods from their point of origin to their point of consumption, focusing on the efficient movement and handling of products. | | SCOR Model (Supply Chain Operations Reference Model) | A process-based framework that provides a common language and structure for describing supply chain operations, covering processes like Plan, Source, Make, Deliver, Return, and Enable. | | Competitive Advantage | The ability of a company to outperform its competitors by offering superior value to customers. In supply chain management, this can be achieved through efficient operations, tailored services, responsiveness, and reliability. | | Lean Philosophy | A management approach focused on the elimination of waste in all business activities, aiming to maximize customer value while minimizing resource consumption. | | Agile Supply Chains | Supply chains designed to be flexible and responsive to rapid changes in demand and market conditions, often employing strategies like postponement and advanced manufacturing technologies. | | Key Performance Indicators (KPIs) | Measurable values that demonstrate how effectively a company is achieving key business objectives. In supply chains, KPIs often relate to service, cost, and cash. | | Make-to-Stock (MTS) | A manufacturing strategy where products are produced in advance of customer orders and stored in inventory, allowing for immediate shipment upon order placement. | | Finish-to-Order (FTO) | A strategy where components and subassemblies are produced and stocked, but final assembly or customization occurs only after a customer order is received. Also known as Assemble-to-Order (ATO). | | Make-to-Order (MTO) | A strategy where production begins only after a customer order is received, with inventory typically held only for raw materials or standard components. | | Engineer-to-Order (ETO) | A strategy used for highly customized products where design and production commence only after a customer's specific requirements are defined. | | Waste (Muda) | In Lean philosophy, any activity that consumes resources but does not add value to the product or service from the customer's perspective. | | Bullwhip Effect | The phenomenon where demand variability increases as orders move upstream in the supply chain, leading to inefficiencies in inventory and production. | | Sales and Operations Planning (S&OP) | A cross-functional planning process that aligns sales, marketing, operations, and financial plans to balance customer demand with available resources over a medium to long-term horizon. | | Outsourcing | The practice of contracting out specific business functions or processes to a third-party provider. | | Economic Order Quantity (EOQ) | A formula used to determine the optimal order quantity that minimizes the total inventory costs, balancing inventory holding costs and ordering costs. | | Economic Production Quantity (EPQ) | A formula used to determine the optimal production quantity that minimizes total production costs, balancing inventory holding costs and production setup costs. | | Safety Stock | Extra inventory held to mitigate the risk of stockouts caused by uncertainties in demand or lead times. | | Supply Chain 4.0 | The evolution of supply chains driven by digitalization and advanced technologies such as the Internet of Things (IoT), Blockchain, and Artificial Intelligence (AI). | | Internet of Things (IoT) | A network of physical devices, vehicles, appliances, and other items embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data. | | Blockchain | A distributed, immutable ledger system that records transactions across a network of computers, providing transparency and security. | | Artificial Intelligence (AI) | The simulation of human intelligence processes by computer systems, including learning, problem-solving, and decision-making. | | Greenhouse Gas (GHG) Protocol | An international accounting and reporting standard for measuring and managing greenhouse gas emissions, including Scope 1, 2, and 3 emissions. | | Carbon Footprint | The total amount of greenhouse gases generated by an activity, product, or individual. | | CO2 Equivalent (CO2e) | A unit used to express the warming potential of any greenhouse gas in terms of the equivalent amount of carbon dioxide. | | Due Diligence | The reasonable steps a person must take to satisfy a legal requirement, especially in buying or selling something. In supply chains, it involves assessing and mitigating risks related to human rights and environmental impacts. | | Circular Economy | An economic system aimed at eliminating waste and pollution, keeping products and materials in use, and regenerating natural systems. | | Resilience (Supply Chain) | The capacity of a supply chain to withstand, adapt to, and recover quickly from disruptions. | | Sustainability (Supply Chain) | Operating supply chains in a manner that meets present needs without compromising the ability of future generations to meet theirs, considering environmental, social, and economic impacts. | | Landed Costs | The total cost associated with sourcing and receiving products from suppliers, including purchase price, transportation, insurance, duties, and other related expenses. | | Kraljic Matrix | A strategic tool for supplier segmentation based on supply risk and profit impact, helping to define appropriate supplier management strategies. | | Service Level Agreement (SLA) | A contract that defines the level of service expected from a supplier, including performance metrics, responsibilities, and dispute resolution procedures. | | Demand Management | The process of understanding, anticipating, and influencing customer demand to ensure it aligns with supply chain capabilities. | | Time Series Forecasting | A quantitative forecasting method that uses historical data to identify patterns (like trends and seasonality) that are expected to reappear in the future. | | Causal Forecasting | A quantitative forecasting method that explains future demand based on relationships with other more predictable variables or factors. | | Lead Time | The total time that elapses between the initiation and completion of a process, such as the time between placing an order and receiving it. | | Inventory Holding Costs | The expenses incurred for storing unsold inventory, including warehousing, insurance, obsolescence, and capital costs. | | Purchasing Costs | The expenses associated with placing an order, such as shipping, handling, and administrative costs. | | Setup Costs | The costs incurred to prepare a production run, including reconfiguring machinery, calibration, and lost production time. | | VUCA World | An acronym representing Volatility, Uncertainty, Complexity, and Ambiguity, describing the nature of the business environment characterized by constant, unpredictable change. |