Supply Chain Analytics Course Summary by Time Segment 0:00 - 5:38 Topic: Introduction to Supply Chain Analytics Key Points: Supply chain management is crucial in today's business environment. Analytics can help address challenges in supply chain management. Different philosophies govern supply chain management, including the cyclic view. 5:38 - 10:43 Topic: Push vs Pull Processes Key Points: Supply chain processes can be categorized as push or pull. Push processes: Products are anticipated and produced before customer orders (e.g., grocery stores). Pull processes: Products are produced based on customer orders (e.g., restaurants). Push processes are more proactive (anticipate demand). Pull processes are more reactive (respond to demand). Inventory levels are typically higher with push processes. 10:43 - 14:37 Topic: Push vs Pull Processes (Continued) & Risk Key Points: Risk is higher in push processes due to anticipation of demand. Manufacturer typically holds the most risk in the supply chain. Some exceptions exist (e.g., industrial product manufacturers with pull processes). The appropriate push/pull boundary depends on factors like product value and unit cost. Data analytics can help determine the optimal push/pull boundary. Inappropriate boundaries can lead to excessive inventory or stockouts. 14:37 - 19:00 Topic: Competitive Strategy & Supply Chain Strategy Key Points: Supply chain strategy should support the competitive strategy of a company. Competitive strategy defines how a firm fulfills customer needs compared to competitors. Examples of competitive strategies: Everyday low prices (Walmart). Supply chain strategy determines how materials are procured, transported, etc. to achieve the competitive strategy. Previously, companies operated in silos with limited communication between departments. Modern businesses require strong integration across all functional strategies. 19:00 - 21:21 Topic: Strategic Fit & Customer Priorities Key Points: Strategic fit is achieved when customer priorities, supply chain capabilities, and competitive strategy are aligned. Data analytics helps identify changing customer priorities. Customer priorities are not constant and can be influenced by factors like exposure, purchasing power, and technology. Companies need to adapt their competitive strategy based on evolving customer priorities. 21:21 - 33:48 Topic: Strategic Fit (Continued) & Competitive Advantage Key Points: Supply chain capabilities should match the competitive strategy. (e.g., Market dominance strategy requires many retail outlets). Data helps monitor competitive priorities for strategic fit. Overall business goals and supply chain goals should be aligned. Strategic fit ensures resources and processes support the desired strategy. Data analytics helps understand customer priorities for strategic decision-making. (e.g., Petroleum companies using data to expand gas stations based on rising demand). Strategic fit is a 3-step process: Understand customer and supply chain uncertainties (data analytics helps manage these). Understand your own supply chain capabilities. Link capabilities with customer and supply chain uncertainties to achieve strategic fit.
