Global Supply Chain Simulator

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Simulator

Based on Global Supply Chain Simulator (see the email from Harvard Publishing), each student develops a comprehensive plan to choose suppliers and production quantities. Use the following data for Year 1 of the simulation.

Table 1: Data for Product Design

Table 2: Data for Demand

If no feature is added, the forecasted demands are the following (measured in thousand units).

The above data may not match with the real data in the simulator. But you use this ex ante forecast to plan your decisions.

If you choose any feature, then the forecasted demand in each month changes according to the “Mean” column in the Product Design table. For instance, if you choose “Stylish”, then subtract all the monthly demands by 1000 units. See the following table as a reference.

All features will have an additive effect on the monthly demand. (Hint: Use binary variables to control the demands due to product design.)

Table 3: Cost Data

Assume no feature is added.

If a feature is added, the impacts on selling price and cost follow the last two columns of Product Design table. For instance, if you choose both Stylish and Storage Capacity, the selling price will be $215 for Model A and $255 for Model B; the production cost will be $145 for Model A and $165 for Model B.

Table 4: Supplier Data

Note: The incremental unit cost is added to the production cost with feature. For instance, if you choose both Stylish and Storage Capacity, the production cost of the first two suppliers (long lead time) will be $145 for Model A and $165 for Model B. In contrast, the production cost of the last two suppliers (with zero lead time) will be $155 for Model A and $175 for Model B.

A) Build an EXCEL model to optimize various decisions (i.e., supplier selection and production quantities) subject to the constraint that no order change is ever requested. Interpret your results so that anyone who participate the simulation can act upon your plan.

B) Assume that the order change cost is zero. Solve your Excel model again to determine the optimized profit by freely issuing order changes.

C) Based on your results in Part A) and B), explain whether requesting an order change is worthy.

D) Implement your plan in the simulation again. Record the profit of Year 1. Cut and paste the screen shot as the evidence (although the coordinator can find it from the Administrator’s interface).

E) Discuss how you choose between level and chase strategies in this simulator.  

Hints

If you wish to extend your Excel model for the remaining years, you need to be aware that data in Tables 1-3 may change from year to year.

To make the model “linear”, you need to fix the decisions on “features”. Iterate the possible combinations of features. As required by Part 1), there are four choices on features. It is, hence, not difficult to conduct a full search. (The binary decision variables of features impact the selling price and cost and hence make the model nonlinear. If you fix the feature decisions in any given iteration, the model can be linearized again.) When extending to the later years of the simulation, it is up to you to choose whether you want to do a full search (i.e., 16 combinations).

In the hypothetical “chase” scenario with zero cost of order change, you construct a plan so that the total arrival equals to the demand for that month (i.e., some form of constraints as the lecture note discussed). Allocate the production quantities to the chosen suppliers by excluding the cost of order changes. You may have multiple solutions that produce identical profits. This is a special case of linear programming, where the objective function is parallel to a border of the feasible region.

The leftover incurs the monthly holding cost in every month except in December when the markdown occurs. For example, if you keep 1000 units of leftover in every month, then the total holding cost is 7000 multiplied by the holding cost rate. (Demand arises in 8 months of the year and hence 8-1=7).  The 1000 units of leftover in December generates the markdown revenue without incurring the holding cost.