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r not a product is out of stock.
The Event-Based Simulators were also taken from another probability of distribution about special promotions - if the product is regularly priced, in which case a consumer will buy one, or if it is promotionally priced, in which case he might buy two or three. BiosGroup also added more probabilities about buying a competitor's product if the P&G shampoo was out of stock, and so on, capturing the complex nature of supply and demand.
With real world volatility embedded in this model, BiosGroup was then able to measure the behavior of how the whole system would behave if P&G modified various parts of the supply chain. The BiosGroup project team performed thousands of simulations, in hopes of revealing to P&G what improvements the consumer product company should make to become more efficient and cut inventory costs in half.
Challenging convention. One major focus area in the project was P&G's practice of offering price breaks to retail partners if they bought in full-truckload quantities. The pricing policy was based on the very simple problem of how to optimize transportation costs. The rule is derived from an obvious condition: filling a truck completely will ultimately require the least number of trucks possible to move the goods. Thus, to keep costs down, trucks should be loaded to 100 percent capacity, and customers should be encouraged through price incentives to buy full-truckload quantities.
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