The bullwhip effect
28/09/2011
Tiphaine Ribetto – st
Perrine Trullemans – st112855
Background: "Beer Game" is a simple simulation of a Make-to-Stock Supply chain. The goal of this game is to minimize cost of capital employed in stock while avoiding out-of-stock situations. The issue here is how to forecast demand accurately. Tiphaine and I assume the roles of beer factory in the production department. As our work does not involve any decision in the order flow, our discussion will focus on our experience as manufacturer.
Results analysis:
* What happened to the order quantity as we move backwards, up the supply chain from retailer to manufacturer? And why?
What happened during the first rounds (weeks 1-10) is that our team places small orders in an attempt to get rid of some of the inventory. As the incoming orders size were getting lower and lower, we interpret this reduction as a signal of declining demand. Our production batches were consequently reduced and sometimes equal to 0 (weeks 5 – 6 -7). Our supply chain was adjusted to a low demand scenario. When a pic in demand occurred in week 10, we were not ready to fulfill the total order. Thanks to a ‘safety stock’, we achieved to limiting the number of backlogs. Nevertheless, this jump in demand entailed consecutively an increase in our orders. Up-streamed participants ordered extra in an attempt to fill the pipeline – forgetting that orders served two rounds before would be eventually filled. This leaded us to produce even more than the demand in the market (round 11 -17: order size oscillated from 8 to 14). In the end, we lose track of what we ordered to answer of the real incoming orders and ordered way too much. Such a behavior shows that any part of the supply chain tends to overreact in front of periods of rising/ falling demand. One overreaction in the up streamed part is enough to break the perfect equilibrium and make downstream participants ever more