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How "SMART Scores" are Calculated: Restaurant Example

Below is a numerical example simply to illustrate how the overall SMART Score of the Japanese Lotus restaurant was calculated. This is from the How Optsee® Works example where a restaurant is being selected for dinner is used to illustrate the concepts.

Figure 1 shows the values assigned to the attributes for the Japanese Lotus restaurant in the Project form.

Figure 1: Japanese Lotus Attribute Assignments

1. The Japanese Lotus value for the attribute "Atmosphere" is "Very Good". We can see from the Category assignements in the Attribute form (Figure 2) that the score for "Very Good" is 80.

Figure 2: Atmosphere Category Assignments

2. The Japanese Lotus value for the attribute "Food Quality" is "Excellent". We can see from the Category assignements in the Attribute form (Figure 3) that the score for "Excellent" is 100.

Figure 3: Food Quality Category Assignments

3. The Japanese Lotus value for the attribute "Cost($)" is "$50". We can see from the SMART Score Curve in the Attribute form (Figure 4) that the score for "$50" is 73.

Figure 4: SMART Score versus Cost Attribute Value Curve

4. The Japanese Lotus value for the attribute "Travel Time" is "20 minutes". We can see from the SMART Score Curve in the Attribute form (Figure 5) that the score for "20 minutes" is also 73.

Figure 5: SMART Score versus Attribute Travel Time Value Curve

Note that for both "Cost($)" and "Travel Time" lower attribute values are better than higher, hence, the line slopes down from left to right.

Table 1: Individual Attribute and Raw SMART Scores

Note that for the Category-Type attributes, the SMART Scores are normalized based on the highest and lowest project values for those attributes in the portfolio (NOT the highest and lowest Attribute Category Values). The equation used is:

((Actual - Lowest) / (Highest - Lowest)) X 100 = Unweighted SMART Score

So, for example, the "Atmosphere" Attribute for Japanese Lotus is calculated as follows:

((80 - 40) / (100 - 40)) X 100 = 66.7

2. The assigned weight and corresponding normalized weight for each attribute are shown in Table 2. These normalized weights are used to adjust the individual SMART Scores in the next step. Notice that even though the normalized weights are different than the assigned weights, the relative importance of each attribute is the same. For example, the normalized weight for Atmosphere is still twice as much as the normalized weight for Cost (0.417÷0.208=2.005) and more than three times as important as Travel Time (0.417÷0.125=3.336).

Table 2: Normalized Weighting Factors

The normalized weights are calculated by dividing each individual weight by the sum of all the weights.

3. Each individual unweighted SMART Score is then multiplied by its corresponding normalized weighting factor to get the individual weighted SMART Score (Table 3).

Table 3: Individual Weighted SMART Scores

4. The individual weighted SMART Scores are then summed to yield the overall project SMART Score:

27.28 + 25 + 15.15 + 8.93 = 76.86

Figure 6 shows how it appears in the row after the [Calc.] button is clicked in the Portfolio form.

Figure 6: Calculated Values Row Displayed

Clicking the [Actual] button restores the actual attribute values in the Portfolio form (Figure 7).

Figure 7: Actual Values Row Displayed

Note that the projects with the lowest values in each column have weighted SMART Scores of 0.