Introduction to Operations and Supply Chain; Supply Chain strategy; Descriptive analytics; Diagnostic analytics; Predictive analytics; Prescriptive analytics; Operations performance; Capability trade-offs; Capacity planning; Technology adoption; Inventory management; Supply network structure; Project management; Demand forecasting; Layout; MRP/ERP; Quality management; Make-buy.
Practical insights and methodologies on AI for Forecasting planning in operations & supply chain; Demand variability and uncertainty in planning; Forecasting accuracy; Forecast bias and error diagnosis; Time-series forecasting with statistical methods; AI & machine learning for forecasting; Explainable forecasting AI models; Capacity planning under constraints; Production, inventory, and materials planning logic; AI-based forecasting for uncertain demand; Capacity and resource planning under constraints; Sales and operations planning (S&OP); Integrated AI-based planning.
Role of enterprise systems in operational coordination; ERP concepts and core transactional processes; Master data and operational data management; Performance monitoring using dashboards and KPIs; Execution visibility and exception management; Analytics embedded in enterprise systems; Data-driven decision workflows; Cross-organizational information integration; Governance, controls, and system accountability; Managing change and system adoption.
The strategic role of procurement within organizations and supply chains, sourcing strategy, supplier selection, contract management, and performance evaluation, procurement governance, supplier relationships, negotiation, and category management, spreadsheet-based cost modeling and decision analysis, experiential components such as negotiation exercises and simulation are also incorporated.
Introduction to decision analysis and prescriptive analytics for supply chain and operations decisions. Decision challenges, foundations of decision analysis, decision quality and process design, decision framing using influence diagrams, stakeholder objectives and value measures, and alternative development. Deterministic modeling using spreadsheet tools, including net present value, scenario, and sensitivity analysis. Probability foundations, uncertainty quantification, Monte Carlo simulation, decision trees, risk attitude, value of information, constrained optimization, portfolio resource allocation, and communication and implementation of analytical decisions.
A 16-week full-time professional internship in an operations or supply chain function within an organization. Students gain hands-on experience in strategic planning, demand forecasting, procurement, logistics, inventory management, process improvement, and supply chain digitization. Internship experience is supervised by both a company supervisor and a faculty advisor. Students conduct independent analysis and submit comprehensive reports on their internship experience and contributions.
The aim of this summer training is to provide students with direct on-the-job experience working with professionals in the field. This training provides an opportunity to expose students to the reality of professional practice. Students are required to submit a report and make a presentation on their summer training experience and the knowledge gained.
Performance excellence in operations and supply chains, Performance measurement systems and KPIs, Process variation and performance risk, Root-cause analysis and diagnostic analytics, Predictive analytics for performance improvement, Prescriptive analytics for improvement prioritization, Lean principles supported by data, Six Sigma concepts and DMAIC framework, Statistical process control fundamentals, Benchmarking and continuous improvement programs.
The first phase of the team-based project sequence for OSC majors. Students form teams and develop comprehensive project proposals addressing real-world operations and supply chain challenges. Working with faculty advisors and industry partners, students define scope, conduct preliminary analysis, and establish project management plans. This course emphasizes team dynamics, stakeholder engagement, and integration of knowledge from the entire OSC curriculum.
This is the second phase of team-based project course in the OSC major. Students execute comprehensive projects addressing real-world operations and supply chain challenges sponsored by industry partners or internal organizational needs. Through iterative analysis, modeling, prototyping, and stakeholder engagement, teams develop evidence-based recommendations and implementation strategies. The course emphasizes integration of analytical methods, technology application, ethical reasoning, and professional communication. Culminates in a formal report and executive presentation.
Introduction to sustainability principles into operations and supply chain management. Sustainability frameworks, operations strategy, sustainability performance measurement, carbon accounting and emissions analysis, sustainable process design, and life cycle assessment. Circular economy systems, sustainable supply chain, inventory and transportation decisions, quality improvement methodologies, digital transformation, and project management for sustainability. Emphasis on carbon footprint evaluation, analytical tools and managerial decision-making.
Integrative case-based analysis of contemporary operations and supply chain management issues, supply chain strategy and design, process management and technology enablement, production planning and demand management, warehouse and inventory management, distribution network design, disruption and risk management, supply chain digitization, and sustainability and circularity. Case-analysis, articles, and simulations to practice structured problem diagnosis, evidence-based recommendation development, managerial communication, and ethical decision-making in complex real-world settings.