Inventory Planning - How to 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 policies
Simulate them using historical demand and forecast data
Optimize policies based on cost or service/inventory trade-offs
These templates 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 data
Optimize them
Select 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 data
Corrected templates for all exercises and simulations
All the slides
What's not covered in this course?
EOQ model
Newsvendor model
Pre-requisites
Excel intermediate level - The course includes a brief introduction to the Excel Solver
How to compute the RMSE (see my other course) - The course includes a brief reminder on how to compute RMSE.
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)
Who this course is for:
- Demand planners
- Supply planners
- Purchasers
- Supply chain data scientists
- Supply chain analysts
Instructor
Nicolas Vandeput helps supply chain leaders achieve demand and supply planning excellence.
He founded his consultancy company, SupChains, in 2016; and SKU Science, an online platform for supply chain forecasting, in 2018. Passionate about education, Nicolas is both an avid learner and a teacher.
Since 2020, he has been teaching demand forecasting and inventory optimization to master students in CentraleSupelec, Paris, France. He also teaches demand forecasting at Albert School, Paris, France, and guest teaching in various universities worldwide.
He published three books: Data Science for Supply Chain Forecasting in 2018 (second edition in 2021), Inventory Optimization: Models and Simulations in 2020, and Demand Forecasting Best Practices in 2023.