edX Supply Chain fundamentals course by MIT

Not long ago, platforms like Coursera (https://www.coursera.org/) or edX (https://www.edx.org/) started offering the possibility to enroll free courses, ranging from Law to Arts, Management, Sports and many more.

 

Since then thousands of people have had the opportunity to develop their skills, I’m among those thousands, and currently I’m working through passing the first of three courses offered by edX and focused on Supply Chain Management.

This first Course (CTL.SC1x Supply Chain and Logistics Fundamentals) runs for eleven weeks and covers all the basics of Supply Chain focusing on three main areas Demand Forecasting, Inventory Management, and Transportation Planning.

If you have the time and interest, this first course developed by the MIT presents each of the above topics in a clear and very structured way, including examples and assignments that will help you get the foundation you need to accomplish the following two courses.

Below you can see the Course schedule, taken from the edX website should you are interested in starting the course.

•   Overview of SCM

An overview of supply chain management perspectives, core concepts, and basic approaches. It is a chance to get familiar with the edX platform, the discussion forum, and the course materials.

•   Forecasting I: Introduction  

We introduce demand management and focus specifically on demand forecasting. We will develop and use basic time series models.

• Forecasting II: Exponential Smoothing

We will expand the use of time series models to include Exponential Smoothing. We will develop and test different model forms for stationary, trend, and seasonality patterns.

• Forecasting IV: Causal Analysis & Special Cases

We introduce ordinary least squares regression that can be used for causal analysis. We finish the Forecasting section by discussing two special cases: intermittent demand and new product forecasting.

• Inventory I: Overview & Deterministic Demand

The inventory section opens up with the simplest inventory model: the Economic Order Quantity (EOQ)

• Inventory II: Stock Outs & Single Period Models

We now expand from our initial assumptions of deterministic and constant demand to allow for stochastic or random demand. In this module we restrict the time frame to a single period and develop what is called the Newsvendor Model.

• Inventory III: Probabilistic Demand Models

This week is spent developing and using the most common inventory policies in practice for both continuous and periodic review situations. We will spend a lot of time developing models that either minimize costs or meet a specified level of service.

• Inventory IV: Special Cases

We will show some methods for applying these inventory models for multiple items and multiple locations at the same time. We will wrap up the inventory section by discussing some real world implications and concerns.

•  Transportation I: Fundamentals

The transportation section focuses on understanding the fundamentals of freight transportation from a global perspective. We will show how to make routing decisions with multiple legs and demonstrate how this also applies to any mode selection. We also show how to handle uncertainty in lead-times and demonstrate how this relates back to inventory policies.

• Transportation II: One To Many distribution

In this final transportation lesson, we introduce an approximation method for determining transportation costs. We demonstrate this approach on a common one-to-many distribution situation that most firms face. We finish this week – and the entire course – with a wrap up of the major concepts and some suggestions on using them in practice.

• Final Exam

The final exam covers all of the material in this course.

So here you go, if you feel like you want to give it a go, just register and look for the below course!

“CTL.SC1x Supply Chain and Logistics Fundamentals”

Enjoy!

The Beer Game

Not long ago I had the opportunity to play what is one of the most famous games in the Supply Chain sphere; The Beer Game.

The Beer Game was developed in the late 1950s professor Jay Forrester. Initially it was played with pen, paper, printed plastic tablecloths, and poker chips, but nowadays there are on-line versions as well as board games. 

The Beer Game simulates the supply chain of the beer industry.The object of the game is to meet customer demand for cases of beer through the distribution side of a multi-stage supply chain with minimal expenditure on back orders and inventory. There are four units, retailer, wholesaler, distributor, and manufacturer, with a two week communication gap of orders toward the upstream and a two week supply chain delay of product towards the downstream

The goal is to keep operating costs as low as possible, teams will be penalized for having too much inventory (0.5 units per case of beer per week) or unfilled back orders (1 unit per case per week). Each link in the supply chain keeps track of its own costs, but a team’s score is the sum of these tallies. In the end, the lower the score, the better.

Usually 50 rounds (which represent weeks) are played, and to simulate the incomplete information we deal with in real life, players cannot communicate across stations. Each retailer draws a card indicating consumer demand for cases of beer; at the same time, all the units send their orders up the supply chain. In response, cases of beer, represented by poker chips, move in the opposite direction, from manufacturer to retailer. A small number of chips are already at every station when we start.

In the next video there is a detailed explanation of the game (min. 8:23) after a brief introduction on Supply Chain Management.

  

The principal effect shown by the Beer Game is the so called bullwhip effect. It refers to the effect that the amount of periodical orders amplifies as one move upstream in the supply chain towards the production end.

As a consequence of the bullwhip effect a range of inefficiencies occur throughout the supply chain:

• high safety stock levels
• poor customer service levels
• poor capacity utilisation
• inaccurate demand forecasting
• high cost

The main causes of the Bullwhip effect are

• The lack of information

In the Beer Game no information except for the order amount is shared up the supply chain, hence, most information about customer demand is quickly lost.

The game simulates supply chains with low levels of trust, where only little information is being shared between the parties and where all forecasting has to rely solely on the incoming orders at each supply chain stage. 

•   The structure of the supply chain

The supply chain structure itself contributes to the bullwhip effect. The longer it takes for an order to travel upstream and the subsequent delivery to travel downstream, the more aggravated the bullwhip effect will be.

The next video contains an example that explains the impact of the Bullwhip effect in the stock levelsas well as shows the obstacles the Supply Chain needs to overcome to  ensure a steady flow of stock up and downstream the Supply Chain. 

Finally, if you want to experience first-hand how it feels to play the Beer Game, in thelink below there is an online version where you can test yourself!

http://www.masystem.com/o.o.i.s/1365