The Impact of Possible Cost Scenarios

When decisions are made regarding long-term capacity and network structure, it may be useful to consider possible future changes in the demand or cost scenarios when making choices. Assuming that once capacity is eliminated, it cannot be recovered easily (except after a long lead time), the reduced capacity levels may prevent access to the benefits that could accrue from having the flexibility to adapt product flows to match cost or demand levels at a future point in time. 

To illustrate this idea, consider an alternative to the problem described earlier a new transport company decreases costs from P2 to Wl to l/unit from Wl to Cl, C2 and C3 decrease to l/unit, 0.5/unit and 0.5/unit respectively. Such a cost decrease may occur because of an arrangement with a trucking company that does extensive backhaul along these routes. Note that if we had closed Pi and Wl based on costs in the previous section, then we would operate only with P2 and W2, and our costs would have continued to be 1,020,000. 

However, if all plants and warehouse capacities remain, then the model can be optimized with the new cost parameters. The new optimal solution is to operate only PI and Wl and thus have a cost of 895,000. If there was an 80% chance of such a cost change, then the expected cost with all plants open would be (0.2 X 1,370,000) + (0.8 X 895,000) = 990,000. Thus, the slack capacity offers the flexibility to respond to such cost-reducing opportunities and decreases expected cost. 

This example suggests that excess capacity in a network can provide the flexibility to react to changing cost or demand conditions. As we shall see later, when demands and costs are generated by scenarios and thus lack certainty, building in slack capacity throughout the network may preserve the flexibility to deal with parameter changes. 

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