Monte Carlo Simulation Application (return to DSS home)
(click here to go to Monte Carlo Simulation Concepts)
In Project 2, we developed a Model to forecast Firm’s Demand.
Details concerning the variables of the Model ® Variables.
An interactive Simulation of the Model® Simulation.
Based on the Model in Project 2 and inputs/outputs, an actual simulation was run (1000 Iterations) using @Risk.
Simulation Results - Market Share
Summary Measures Upon Running Simulation
|
Name |
Market Share |
|
Description |
Output |
|
Cell |
F6 |
|
Minimum = |
4.38E-02 |
|
Maximum = |
0.2325275 |
|
Mean = |
0.1228274 |
|
Std Deviation = |
2.81E-02 |
|
Variance = |
7.90E-04 |
|
Skewness = |
-4.97E-02 |
|
Kurtosis = |
3.028416 |
Simulation Results - Firm Demand
|
Name |
Firm Demand |
|
Description |
Output |
|
Cell |
F7 |
|
Minimum = |
1219.689 |
|
Maximum = |
3539.851 |
|
Mean = |
2605.607 |
|
Std Deviation = |
332.7022 |
|
Variance = |
110690.8 |
|
Skewness = |
-0.6742423 |
|
Kurtosis = |
4.328664 |
Conclusions
From the distributions for market share as well as firm demand, the following conclusions can be drawn:
- The market share of the firm is most likely to fall in the range between 9% and 15%
- The Firm Demand is likely to be in the range 2250 and 3100 units
Forecasting variables is a non- trivial problem, but the Monte Carlo Simulation can help overcome some uncertainty. From the above information, the firm can now schedule production levels, budget for advertising expenditures, implement marketing campaigns and ultimately determine revenue and create value for the firm and its shareholders.