Ski Jacket Production
Ski Jacket Production
Executive Summary
The problem is to determine the optimal production level of the Egress new designed jacket given the uncertainty in the forecasted demand. As oppose to determining a single profit value in the deterministic approach, the probabilistic method will incorporate the uncertainty in estimated demand and provide insights of the range of profit outcomes and its associated risk (deviation from mean). The key issue is to understand impact of demand uncertainty and production level to the profit range and its distribution. In this case, we will determine the optimal decision variables (jacket production quantity) that will maximize our objective (average profit).
The given information from management is the variable production cost, the selling price, and the salvage value per unit. There is also the fixed production cost regardless of production level. Production can all be sold if it is not greater than the demand level. However, if the production quantity is greater than the demand, it will be sold to discounters at the salvage value price.
When dealing with uncertainty, the simulation model is useful to explicitly incorporate uncertainty into the input variables. This random input variable and the resulting output variables of interest are keep recorded. Hence, we are able to analyze how the outputs vary as of function of the varying inputs. In this case, the demand distribution was assumed normally distributed with the mean and standard deviation from 12 discrete forecasts from Egress employees. The optimal production level of Egress’ new designed is around 10,174 jackets with the average profit of $61,849 and standard deviation of $94,136.
Model * Decision: Production quantity of ski jacket * Objective: Maximize the profit * Assumption: * The decision variable (production quantity)) are non-negative * Variable production cost = $80/jacket * Selling price = $100/jacket
Executive Summary
The problem is to determine the optimal production level of the Egress new designed jacket given the uncertainty in the forecasted demand. As oppose to determining a single profit value in the deterministic approach, the probabilistic method will incorporate the uncertainty in estimated demand and provide insights of the range of profit outcomes and its associated risk (deviation from mean). The key issue is to understand impact of demand uncertainty and production level to the profit range and its distribution. In this case, we will determine the optimal decision variables (jacket production quantity) that will maximize our objective (average profit).
The given information from management is the variable production cost, the selling price, and the salvage value per unit. There is also the fixed production cost regardless of production level. Production can all be sold if it is not greater than the demand level. However, if the production quantity is greater than the demand, it will be sold to discounters at the salvage value price.
When dealing with uncertainty, the simulation model is useful to explicitly incorporate uncertainty into the input variables. This random input variable and the resulting output variables of interest are keep recorded. Hence, we are able to analyze how the outputs vary as of function of the varying inputs. In this case, the demand distribution was assumed normally distributed with the mean and standard deviation from 12 discrete forecasts from Egress employees. The optimal production level of Egress’ new designed is around 10,174 jackets with the average profit of $61,849 and standard deviation of $94,136.
Model * Decision: Production quantity of ski jacket * Objective: Maximize the profit * Assumption: * The decision variable (production quantity)) are non-negative * Variable production cost = $80/jacket * Selling price = $100/jacket