Supply Chain Management - Beer Game Report
He Yi 5100309186
Experiment Report: Beer Game
Class F1003017 贺艺 5100309186
Introduction

The purposes
1. Through the analysis of the beer game, learn the bullwhip effect in supply
chain management;
2. Learn that the structure of the system made by humenbeing is intricate and
delicate;
3. Learn that effective originality usually comes from the new way of thinking.

Principle
The Beer Game is one of a number of management flight simulators
developed at MIT's Sloan School of Management. The game was developed by
Sloan's System Dynamics Group in the early 1960s as part of Jay Forrester's
research on industrial dynamics. It has been played all over the world by
thousands of people ranging from high school students to chief executive
officers and government officials.
Of course, there is no beer in the beer game, and the game does not
promote drinking. Originally the 'production-distribution game', most students
are more excited about producing beer than widgets or toasters. When played in,
say, high schools, it easily becomes the apple juice game.
Equiment and experimental setup
1. Fig.1 is the preface of the software “Beer Game”.
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Supply Chain Management - Beer Game Report
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Fig.1 preface of beer game
2. Fig.2 is the tool bar of this software. You can set the parameters here.
Fig.2 tool bar
1) File
File—Reset: to re-run the game and all data will be lost
File—Exit: to exit the game
2) Options
Options —Player: to choose which role you want to play and the computer will
control the other roles.
Fig.3 player
Options—Policy: to set the replenishment strategy of the roles.
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Fig.4 policy
*If you want to know the details of these policies, please click on “help”.
Options -Short Lead Time: to reduce the transportation delay and production delay.
Fig.5 short lead time mode
Options-Centralized: to turn the whole system into a centralized system(sharing the
information of each warehouse`s inventory, the quantity of goods in delay and each
role`s total cost).
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Supply Chain Management - Beer Game Report
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Fig.6 centralized mode
Options - Global Information: to make the information of each role visible.
Fig.7 global information mode
Options-Demand: to set the type of demand.
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Supply Chain Management - Beer Game Report
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Fig.8 demand
3) Play
Play-Start: to start the game.
Play-Next Round: to begin the next round after starting the game.
Procedures
1. Start the game, and then the first round begins.
2．The retailer places an order to the wholesaler based on the customer`s demand
and historical data.
The wholesaler places an order to the distributer based on the retailer`s demand
and historical data.
The distributer places an order to the factory based on the wholesaler`s demand
and historical data.
The factory decides the quantity of goods to produce based on the distributer`s
demand and historical data.
3．The first round ends and the next round begins. Repeat the operation until the
game ends (about 15-30 rounds).
4．After the game, get the corresponding data and graphs.
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5．Conduct the game again by short lead time and analyze the result.
6．Conduct the game for the third time by centralized system and analyze the result.
7．Analyze the costs and other information of the game under three different
conditions.
Result Analysis
1. Choose the distributor as the role, choose the rensent order based on the order
datas. Play 20 rounds, the results shows like this.
Fig. 9 default setting preface
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Fig. 10
default setting graph
Fig. 11
Default setting report
Result analysis:
From the result above we can see the bullwhip effect clearly, which is the
increase in variability as we travel up in the supply chain. While customer demand for
specific products does not very much, inventory and back-order levels fluctuate
considerably across their supply chain.
From the graph, when the demand from the retailer varies not very much, the
demand of the wholesaler varies clearly more, the demand of the distributor
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Supply Chain Management - Beer Game Report
He Yi 5100309186
changes more than wholesaler’s, while the demand of the factory varies the most
and shows the great fluctuation.
From the report, we can see that the mean of the retailer demand is the least,
wholesaler has a larger mean, distributor’s mean even larger, and the mean of the
factory is the largest. The standard deviation (SD) has the same rank, so as the cost.
Which means across the supply chain, the mean of the order would become more
because of the larger order fluctuation (Which can be seen from the larger SD), and
this can cause a larger total cost.
2. Choose Short lead time mode then run the game for 20 rounds, the result shows
as follows:
Fig .12
short lead time preface
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Supply Chain Management - Beer Game Report
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Fig. 13
short lead time graph
Fig. 14
short lead time report
Result analysis:
After choosing the short lead time mode, we can see the result above. We can
also see the bullwhip effect in the result.
However, compare with the result in normal pattern, we can find that in the
report, the variation of the mean is smaller, which is, as standard deviation grows
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Supply Chain Management - Beer Game Report
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across the supply chain, it grows less with the short lead time.
This shows that lead time reduction can significantly reduce the bullwhip effect
throughout a supply chain.
3. Choose Centralized pattern in operations. In this case, we can only be the factory.
Play the game for 21 rounds, the results show as below.
Fig .15
Fig. 16
centralized preface
centralized graph
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Supply Chain Management - Beer Game Report
Fig. 17
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centralized report
Result analysis:
From the result above, we can still see the bullwhip effect. However in this
pattern, the total cost variation across supply chain is less than normal.
This shows that by centralizing demand information, the bullwhip effect can be
reduced.
Discussion
1. Conducting the Beer Game by Software has the advantage of various modes,
please list the factors that can affect the volatility of the supply chain data
(bullwhip effect).
Here are some reasons for Barilla going through bullwhip effect:
1.
Transportation discount. This could make the retailers decrease the order
frequency but increase the amount of one order;
2.
Trade promotions. This cause the fluctuating demand;
3.
Lead time. The average lead time was 10 days;
4.
Many types of the products make it harder to forecast the demand;
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Supply Chain Management - Beer Game Report
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5.
The information is transferred not enough between supply chain partners;
6.
The process of the decision is sequential, which means there is lack of
cooperation.
2. Compare the changes of the bullwhip effect under different modes.
From the results of all the three modes, we can see bullwhip effect clearly.
However, when we change the mode, we can see differences.
In the short lead time mode, the variation of the mean is smaller compare with
the result of the normal mode, which is, as standard deviation grows across the
supply chain, it grows less with the short lead time than normal. This shows that lead
time reduction can significantly reduce the bullwhip effect throughout a supply
chain.
In the centralized mode, from the report we can see that the total cost variation
across supply chain is less than normal. This shows that by centralizing demand
information, the bullwhip effect can be reduced.
3. Make a comprehensive analysis for different modes and provide some
suggestions for the case of Barilla SPA(A) in the text.
From the results above we can see the bullwhip effect clearly, which is the
increase in variability as we travel up in the supply chain. While customer demand for
specific products does not very much, inventory and back-order levels fluctuate
considerably across their supply chain.
From the graph, when the demand from the retailer varies not very much, the
demand of the wholesaler varies clearly more, the demand of the distributor
changes more than wholesaler’s, while the demand of the factory varies the most
and shows the great fluctuation.
From the report, we can see that the mean of the retailer demand is the least,
wholesaler has a larger mean, distributor’s mean even larger, and the mean of the
factory is the largest. The standard deviation (SD) has the same rank, so as the cost.
Which means across the supply chain, the mean of the order would become more
because of the larger order fluctuation (Which can be seen from the larger SD), and
this can cause a larger total cost. In the short lead time mode, the variation of the
mean is smaller compare with the result of the normal mode, and in the centralized
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Supply Chain Management - Beer Game Report
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mode, from the report we can see that the total cost variation across supply chain is
less than normal.
Considering the case of Barilla SpA, the company can try to short the lead time
or use centralized pattern to reduce bullwhip effect.
Conclusion
The Beer Game is one of a number of management flight simulators developed
at MIT's Sloan School of Management. By playing the game we can see bullwhip
effect clearly.
From the result of the experiment, we can see that
for the situation that
customer demand for specific products does not very much, inventory and
back-order levels fluctuate considerably across their supply chain. However, by using
short lead time as well as centralized system method, the bullwhip effect can be
reduced.
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