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Inventory Management

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Free Online Course: Inventory Management provided by Coursera is a comprehensive online course, which lasts for 4 weeks long, 5-6 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Coursera. Inventory Management is taught by Paul Jan.

University of California, Irvine via Coursera
4 weeks long, 5-6 hours worth of material
In progress
Overview

  • Inventory is a strategic asset for organizations. The effective management of inventory can minimize a company’s spending while dramatically increasing its profit. In this course, we will explore how to use data science to manage inventory in uncertain environments, how to set inventory levels based on customer service requirements, and how to calculate inventory for products that have short sales cycles.

Syllabus

    • Steady-State Demand: No Demand Variability
      • Welcome to Module 1, ​​Steady-State Demand: No Demand Variability. In this module, we will begin by discussing demand behavior, specifically steady-state demand. Next, we will explore lead time and gather lead time information from multiple stakeholders. The module will close with a demonstration of how to calculate a reorder point within Excel.
    • Inventory Management with Demand Variability
      • Welcome to Module 2. After discussing steady-state demand in Module 1, we will explore the more common situation of demand variability. Specifically, we will focus on sources of variability, strategies for countering variability, and lead time calculations to maintain a safety stock.
    • Inventory as a Strategic Tool to Meet Customer Service Level
      • Welcome to Module 3. In this module, we will discuss customer service level, its relationship to inventory, and how to calculate safety stock to maintain a desired customer service level.
    • Newsvendor Model (One-Period Decision Model)
      • Welcome to Module 4. In this module, we will cover the newsvendor model, examples of single-period products, and calculating the order quantity to mitigate product underages or overages.

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