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Coursera

Supply Chain Planning

S.P. Jain Institute of Management and Research via Coursera

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Overview

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Supply Chain Planning (SCP) provides a structured and analytical exploration of how organizations align demand, capacity, inventory, and resources to support efficient, responsive, and resilient supply chain operations. The course integrates three core domains—demand planning and forecasting, aggregate planning and S&OP, and inventory management and control—to explain how planning decisions influence cost, service levels, resource utilization, and operational performance. Learners study qualitative and quantitative forecasting techniques, time-series methods, aggregate planning strategies, linear programming, supply and demand balancing, inventory classification, replenishment systems, safety stock, service levels, EOQ, reorder points, and single- and multi-period inventory models. Through conceptual explanations, business examples, spreadsheet-based demonstrations, and applied calculations, the course develops the ability to select, evaluate, and apply planning methods under different demand, capacity, inventory, and supply-chain conditions.

Syllabus

  • Demand Planning & Forecasting
    • Demand planning and forecasting provide the analytical foundation for aligning supply with anticipated customer demand. This module introduces the purpose and managerial significance of forecasting, showing how demand estimates influence decisions across operations, supply chain, finance, marketing, capacity, inventory, and facility planning. Learners examine the relationship between forecasting choices and the product life cycle, distinguish qualitative from quantitative approaches, and determine how forecast horizon, demand predictability, data availability, and managerial judgment affect technique selection. The module then develops practical time-series capability by examining level, trend, seasonality, cyclicity, and random variation, followed by numerical methods for stationary and trending demand, including averages, moving averages, weighted moving averages, simple exponential smoothing, and Holt's trend-adjusted method. Through conceptual explanations, business examples, and spreadsheet-based demonstrations, the module equips learners to select, apply, and interpret forecasting methods for a range of demand conditions.
  • Aggregate Planning and S&OP
    • Aggregate planning translates expected demand into medium-term decisions about production, capacity, workforce, inventory, and service levels. This module explains how organizations balance supply and demand across industries with fluctuating requirements, and how coordinated planning supports cost control, resource utilization, customer service, and operational resilience. Learners examine the role of aggregate planning in manufacturing, fashion, technology, and perishable-product settings; compare chase, level, and hybrid planning strategies; and evaluate the trade-offs associated with workforce flexibility, inventory carrying cost, stockout risk, production stability, and implementation complexity. The module also introduces linear programming as a structured optimization approach for determining production, workforce, and inventory decisions subject to demand, capacity, and resource constraints. A complementary lesson on supply-chain network planning broadens the planning perspective by examining facility location, inventory positioning, resource allocation, transportation efficiency, customer responsiveness, and risk mitigation. Together, the lessons provide a practical foundation for coordinated planning decisions that connect demand, capacity, resources, and the supply-chain network.
  • Inventory Management and Control
    • Inventory management balances product availability, working capital, cost, and service — making it a core supply chain capability. This module examines how excess stock, stockouts, and poor channel allocation affect profitability, liquidity, and competitive advantage. Learners classify inventory by stage, purpose, ownership, and strategic role; evaluate performance using financial statements and measures like inventory turnover and days inventory outstanding; and trace the replenishment cycle from lead time and reorder point through safety stock, ordering, and receipt. The module then builds a decision framework for inventory policy — distinguishing single-period from multi-period models, and deterministic from stochastic demand. Learners model demand uncertainty using probability distributions and service levels; apply the newsvendor model for single-period decisions; calculate EOQ and reorder points under deterministic demand; and compare continuous-review and periodic-review systems. Through applied examples and calculations, learners develop the ability to select and justify inventory policies that balance ordering, holding, shortage, and service-level trade-offs.

Taught by

Prof. Debmallya Chatterjee and Prof. Sheila Roy

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