4-1 exel
Global Location Decision Model
| Instructions: | |||||||||
| Global Location Decision Model | 1) Decide on at least 4 factors to will significantly influence your decision. | ||||||||
| 2) Based on relative importance, decide on weights for each factor -- must sum to 100% | Factor 1 | Factor 2 | Factor 3 | Factor 4 | SUM | 0 | 0 | 0 | |
| 3) Show just 3 options for Country locations in the column headings -- a full analysis may have 5-20 options! | 10% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |
| 4) Score each factor for Options 1, 2 and 3. 10 is best, 0 is worst. You don't have real data, just estimate each score. | 20% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |
| 5) Compute the Weighted Score for each Option. (Consider using the =SUMPRODUCT function.) | 30% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |
| 6) Select the best option! (..or if scores are close, performance additional analyses.) | 40% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |
| Options | 50% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |
| Factors | Weight | 60% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! |
| Factor 1 | (Scores = 0 to 10) | 70% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! |
| Factor 2 | 80% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |
| Factor 3 | 90% | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |
| Factor 4 | |||||||||
| Total | 0% | ||||||||
| Weighted Score --> |
Sensitivity of Factor 1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0 0 0 0 0 0 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0 0 0 0 0 0 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0 0 0 0 0 0 0 0
Factor 1 Weight
Total Score (0-10)