Beer game

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Bill Harris
Member
Posts: 31
Joined: Fri Mar 29, 2002 3:39 am

Beer game

Post by Bill Harris »

Jim Hines wrote:

>(Are there any other test inputs that have this character?

While I havent tried it in a classroom presentation, you could also pick a
constant (i.e., no step) input at a level that doesnt match the initial
conditions in all of the intermediate levels (that is, have a constant
order level of 8 throughout the simulation). That should prang the
system, too, and should generate similar dynamics. (Admittedly, I havent
tried this one, but Ive tried a computer simulation of a similar system
with similiar initial conditions, and it worked.) The disadvantage for
inexperienced users would be that the dynamics start early, so it is harder
to run the 4 weeks of practice effectively. It might work quite well for
experienced users, as the game board looks the same, and the inputs look
deceptively easy. You certainly couldnt blame the systems dynamics on
the customer inputs then!

Id try that in a game before putting it in a course.

Bill


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saeed@ait.ac.th (Professor Khali
Junior Member
Posts: 9
Joined: Fri Mar 29, 2002 3:39 am

Beer game

Post by saeed@ait.ac.th (Professor Khali »

I have used two sets of orders for groups in the same class, a step (4 to
8) and random noise (with mean 4 and std dev 1). The behavior is similar in
the two cases, and it generates a good discussion about internal trends vs
external disturbance.

Khalid

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jsterman@MIT.EDU (John Sterman)
Senior Member
Posts: 54
Joined: Fri Mar 29, 2002 3:39 am

Beer game

Post by jsterman@MIT.EDU (John Sterman) »

Octavio Carranza want to know what demand pattern can be used with
people who have already played the beer game once.

We have had excellent experiences using an order deck with the pattern
4,4,4,4,8,12,12,12.....12

This is a step input just as in the base case, but the step height is
larger. Most people wo have played the game before dont learn a robust
ordering rule, but instead remember that demand stayed constant at 8 and
that they shouldnt over-react. Often they immediately jump their
orders to 8 throughout the supply chain without even waiting for an
increase from their customer. When they find their forecast of 8 proves
to be wrong, they try to hold the line on orders, resulting in a huge
backlog. Eventually, they crack under the strain and then order a lot.
Usually one observes that by the end of the game these folks are
generating a cycle that is largely indistinguishable from the cycle
generated by first time players. The large backlogs lead to high costs,
so these experienced teams almost never win. The experience is a good
lesson in the need to focus on underlying structure and the development
of improved decision rules for managing a system rather than focusing on
trying to improve your forecasting - inevitably, the forecast will be
wrong, and what then?

John Sterman
jsterman@MIT.EDU
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