While the effect is not new, it is still a timely and pressing problem in contemporary supply chains. Skip to content. Very managing that inventory. Four for the distributor and for for the factory?
Larry Navarre: Zero. Everybody gets a vacation. Larry Navarre: Zero, good. Okay, very good. Larry Navarre: Ten, okay, Larry Navarre: It takes time to get beer. One week to order, one week to deliver, and you have to have a source of supply. Is this a problem? Larry Navarre: Eight? You got some back-orders here. You might want to take care of that. People will wait for their beer? Larry Navarre: Okay, Hey, alright.
Just a little couching there, a little management education. Larry Navarre: Eight. Okay, retail? Larry Navarre: Oh, Tom, this here advanced to one week. Click it back one week. Just click it down one week. After we enter in week 23, then we update. Larry Navarre: Two. Two whole pallets, two whole pallets. Now click, there we go.
Okay, thank you, Tom. Larry Navarre: What do you call that? And Thomas, thank you so much. Were you truly trying to game the system? You started out trying to manage your inventory. You were — and then what happened? Katie: Well, it says on the instructions that you can choose to add more variations to the game. So I decided to take that risk. Larry Navarre: Oh, okay. So you chose to add — and they really pumped it in there. Some try to game the system and some try to optimize the system.
The reality is that in weeks one, two and three, it was four pallets a week. Actual demand. And they are the only ones that see actual demand. And this is typical of the traditional way of doing supply chains. And in week four, it jumps up to eight pallets per week and then it stays there the rest of the game. Eight pallets per week. This is called a step change.
And it provides a disruption to the dynamics of the system, which everybody tries to compensate for throughout the remainder of the game. No, this is great, you did a super job. Well done! Okay, this is an exercise to illustrate system dynamics. It was created by MIT. Our beer game is an acceleration of the whole process. Normally, if you look at this — this is actually Brandeis University — and they use this exercise as an MBA weekend orientation introduction to explain the complexities of business.
Participants typically crack the whip. And the idea is that a little change over here by the consumer translates into big changes up the supply chain. The game starts with steady demand, and increase in demand is generated just once.
And this induces variation in the system. Participants try to compensate but errors are amplified. Then we can use the principles of supply chain management to explain what is going on.
The most important in supply chain dynamics is variation reduction. Reducing variation is a primary objective of a supply chain manager. The sources of variation in a supply chain are not obvious in this dynamic supply chain system. And the bullwhip effect is a phenomenon that occurs when, acting in isolation, with limited information, supply chain managers make decisions that are magnified upstream. And it results in stock-outs and over-stocking throughout the supply chain.
So that is the principle that is utilized in supply chain management. Here are the factors that contribute to the bullwhip. It takes, in the game, one week to order and one week to receive product. So that two week lag causes a delay in the system, which is difficult to monitor. That batching introduces more problems to the system.
There are also magnifying effects of inflated orders. We have to have the material there to sell to the customer or provide for production.
And traditionally, that was the case in the supply chain. People simply reacted to what they were seeing in the next participant in the supply chain. And finally, information and decision isolation. Nobody talked to each other. I have never, ever said that in the beer game, and nobody ever talks to each other. We make our own decisions.
Believe it or not, this is fifty years old. This phenomenon was known in distributions in the thirties and the forties but Professor J. Forrester of MIT created a mathematical model to simulate the effects. And you can see the swings. And I say this in my industry. Our articles. Divide your inventories by 2 while decreasing shortages. What a bold statement we claim! This article aims at explaining how it is possible to achieve such outcomes with numerical simulations and simple cases.
We will explain below with simulations the two main differentiators of Flowlity : dynamic safety stock and extended Supply Chain synchronization. For this part we consider the following seasonal demand pattern. The graph below shows the demand pattern for the period week 27 to week 23 With this example, we want to see the impact of a seasonal peak on inventory levels depending on two different inventory policies.
Traditionally, companies define a static safety stock approach that would consist of setting a fixed min and max reevaluated quarterly or yearly :. Flowlity, instead, dynamically adjusts safety stocks based on computed uncertainties.
This inventory policy takes into account the different levels of risk through time and places the right inventory at the right time. As you can see in the graph below, we first made a forecast of future consumption that is different from the actual one that materializes. You can find the settings for the simulation in the appendix. The results highlight the benefit of a dynamic inventory policy in this case.
In the following graph we can see the actual inventory evolution when planning according to a traditional inventory policy and when planning with dynamic safety stocks:.
Graphically we can notice that the blue line inventory level when planning according to a dynamic inventory policy is almost always below the brown one inventory level when planning according to a traditional inventory policy. And all within a safe simulation. There are four players — the beer retailer, the wholesaler, the distributor and the manufacturer. It lasts an hour at most and simulates up to a year in the beer-distribution supply chain. If any players are missing, AI bots can play their roles.
You can even take part as a single player. Each week, the retailer places a beer order with the wholesaler.
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