Hi,
I'm doing a project for a car company for my final year studying Industrial Engineering.
The company forecast demand 4 months ahead but, according to history data, the company rarely meets the forecast demand.
The Supply Chain Department asked me to develop a model that would, with the help of actual historic demand, assign a risk factor or probability that the forecast demand will be met. The SPD wil use this to challenge the Volume Control Department's plan.
My question is which methods/techniques would you suggest to solve this problem with the best accuracy. I thought of Monte Carlo simulation. Is this sufficient or is there better ways. Please help me!!
I'm doing a project for a car company for my final year studying Industrial Engineering.
The company forecast demand 4 months ahead but, according to history data, the company rarely meets the forecast demand.
The Supply Chain Department asked me to develop a model that would, with the help of actual historic demand, assign a risk factor or probability that the forecast demand will be met. The SPD wil use this to challenge the Volume Control Department's plan.
My question is which methods/techniques would you suggest to solve this problem with the best accuracy. I thought of Monte Carlo simulation. Is this sufficient or is there better ways. Please help me!!