Inventory Planning - How to Optimize Inventory Policies

Apply, Simulate, and Optimize Inventory Policies

What you'll learn
How to apply, simulate, optimize, and select the best inventory policies
How to optimize inventory policies to minimize costs
How to optimize policies to find the perfect trade-off between inventory and service levels
How to assess service level
How to select an inventory policy based on historical demand patterns and forecast errors

Requirements
Excel Intermediate
Forecasting KPIs (see my other course for example)

Description
What will you learn?In this course, using Excel templates, you will learn how to Apply inventory policiesSimulate them using historical demand and forecast dataOptimize policies based on cost or service/inventory trade-offs As a bonus, we will also cover all simulations and optimizations of these policies using Python.These Excel templates and Python scripts can then be easily tweaked for your own products and data.How is this course different?I have been teaching inventory optimization to master students at the university (in Brussels, Belgium, and then Paris, France) and to professionals since 2015. Most inventory optimization courses focus on solving equations, such as the Economic Order Quantity (EOQ), safety stocks, and newsvendor models. Not this one.Over the years, I have drastically changed how I taught inventory optimization and utilize inventory policies because my experience delivering models to my clients taught me that,Being able to solve a formula doesn't mean that you know how to apply it in practice.Even if you can properly apply a formula, the underlying theory doesn't apply in practice.Other models - that don't rely on specific theoretical foundations - usually deliver more value.So I changed The content of my course: from theory-driven to simulation-driven, How I taught it: from a focus on equations to a focus on 'how do you apply this in practice using real-life data'My objective is that by the end of this course, you will be able to, Simulate different policies using your own dataOptimize themSelect the one that best fits your objective (cost, service level) based on your own data (historical demand and forecast)What deliverables do you get?Excel templates that you can use with your own dataPython scripts to simulate and optimize your inventory policiesCorrected templates for all exercises and simulationsAll the slidesWhat's not covered in this course?EOQ modelNewsvendor modelVariable lead timesPre-requisitesExcel intermediate level - The course includes a brief introduction to the Excel SolverHow to compute the RMSE (see my other course) - The course includes a brief reminder on how to compute RMSE. Not Mandatory - Python beginner level - Python scripts are an add-on to this course, so if you don't know Python, you won't lose any insight/content. How much content is in this course?2h15 of videos (including theory, discussions, and corrections)Depending on your Excel proficiency, approximately 4 to 8 hours of personal work (including mostly simulations in Excel and a bit of theory) 30 minutes of videos related to Python scriptsDepending on your Python proficiency, it'll take approximately 1 to 2 hours of personal work to go through the scripts

Who this course is for:
Demand planners, Supply planners, Purchasers, Supply chain data scientists, Supply chain analysts