The prioritization matrix (table 2-7) can be used to develop numeric rankings to aid in comparing a large number of sites. Start by assigning a number to each factor based on the priority rating (e.g., high priority=3, moderate priority=2, low priority=1, not applicable=0). If you want to weight some factors more than others, multiply the priority rating by a weight factor. For example, a weight factor of 2 doubles the importance of a factor; weighted scores will range from 0 to 6 (table 2-8).
Simply adding the unweighted or weighted ranks for each category gives more weight to categories that have more factors (e.g., resources values). To correct for this, first determine the maximum score possible for each category, then divide the site's category score by the maximum score for that category. This will be a decimal number that can be expressed as the percentage of the maximum score. If you use weighted ratings, sum the weighted scores to determine the maximum for each category.
The final step involves combining the four category scores to obtain an overall priority score. Averaging the four scores is the simplest method. Alternatively, the four scores (expressed as decimals) can be multiplied. This latter method yields a wider spread of values, which may be useful if many sites have similar ratings. Either method yields values that can be expressed as percentages of the maximum possible rating (table 2-9).
When you convert your observations and evaluations to numbers, you typically lose some information. Numeric priority rankings can readily separate the most and least promising sites, but more detailed review of candidate sites may be needed to rank sites with similar numeric ratings.
Table 2-8—Example showing use of prioritization matrix to create numeric priority rankings
|
|
|
Priority rating |
Weighted rating |
Maximum weighted score |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Factor |
Subfactor |
Weight |
Site 1 |
Site 2 |
Site 1 |
Site 2 |
||||||
Management opportunities: |
||||||||||||
Ease of access for treatment |
Slope conditions |
2 |
2 |
3 |
4 |
6 |
6 |
|||||
Adjacent to roads |
2 |
3 |
3 |
6 |
6 |
6 |
||||||
Position of treatment area |
|
1 |
2 |
3 |
2 |
3 |
3 |
|||||
Relative cost of treatment |
|
1 |
2 |
2 |
2 |
2 |
3 |
|||||
Overall likelihood of success |
|
1 |
3 |
3 |
3 |
3 |
3 |
|||||
Existing SOD incidence |
|
1 |
3 |
3 |
3 |
3 |
3 |
|||||
California bay presence/density/size classes |
Bay mostly understory saplings and small trees |
2 |
3 |
3 |
6 |
6 |
6 |
|||||
Bays sparse |
2 |
3 |
3 |
6 |
6 |
6 |
||||||
Note: Scoring for part of the Management opportunities category is shown for two example sites.
Table 2-9—Category totals and overall scores calculated using the averaging method for this example
Unweighted ratings |
Weighted ratings |
Maximum weighted score |
% of maximum |
||||
|
Site 1 |
Site 2 |
Site 1 |
Site 2 |
Site 1 |
Site 2 |
|
Management opportunities |
21 |
23 |
32 |
35 |
36 |
89% |
97% |
Disease risk (detail table not shown) |
10 |
10 |
10 |
10 |
12 |
83% |
83% |
Resource benefits risk (detail table not shown) |
7 |
23 |
7 |
29 |
42.5 |
23% |
58% |
Liabilities |
6 |
8 |
8.5 |
10 |
25.5 |
33% |
40% |
| Totals / Average % of maximum | 44 |
64 |
57.5 |
84 |
116 |
50% |
72% |
Note: Total scores using the multiplication method would be 6% for site 1 and 19% for site 2. In this example, site 2 has a higher overall priority due to higher ratings in the management opportunity, resource benefits, and liabilities categories.