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SharePoint 2010 PerformancePoint Services : Understanding and Working with Scoring (part 2)

3/28/2011 9:36:49 AM

Examining How a Score Is Calculated

This section discusses the steps involved in calculating the score that is ultimately used in the final scorecard.

Step 1: Calculate the Band by Value

The Band by Value number is calculated through the scoring mechanism called out in the scoring pattern selection screen. The available options are described next.

Band by Normalized Value

This option “normalizes” the score so that the thresholds can be dynamically compared. This is especially useful if both the target and actual values vary based on values coming from the data source. The formula varies depending on how the target value is to be used.

  • Increasing Is Better: This scoring pattern is used when there is no upper bound on what is good, and when larger numbers are generally considered better than smaller numbers. One example of this is profits, where there is no such thing as having too much money.


  • Decreasing Is Better: This scoring pattern is used when there is no lower bound on what is considered good, and when smaller numbers are generally considered better than larger ones. One example of this is expenses where saving more money is usually better.


  • Closer to Target Is Better: Headcount is an example where you might use this scoring pattern. When tracking headcount for a department or a project, it is possible to have too many or too few people. This means it is preferable to keep the actual count as close as possible to the target value.


Band by Numeric Value of Actual

This option enables you to enter exact values for thresholds. This is the intended scoring pattern to use if there are static and absolute values that divide the indicator levels.

In The Green Orange business scenario, having a target number of commercials per episode is an example when this option might apply. It is not difficult to come up with worst and target values for number of commercials per episode. These values do not change across episodes, which means you can set the values once in Dashboard Designer and keep the values constant for future episodes.

This is also the easiest scoring pattern to understand since there is less math and calculations involved. Its simplicity makes it a good scoring pattern with which to begin.

Band by Stated Score

The Banding by Stated Score method enables you to bypass the calculation part of the score and directly select a Band by Value. It is possible to select a filtered data value directly from the data source or to author a custom MDX tuple expression.

This feature is tricky to use and is most applicable when dealing with Excel data sources where it is possible to do calculations in a data column and manually generate the Band by Value if you want more control over how the score is set.

The selection of the stated score query is only accessible through the Set Scoring Pattern and Indicator Wizard.

Step 2: Identify the In Band Value

When the Band by Value is calculated, the PPS scoring engine maps the Band by Value to a range defined by the Threshold settings, as shown in Figure 6.

Figure 6. Define threshold settings here.

Step 3: Normalize the Score

When the appropriate threshold is identified, the true normalized score is calculated. This calculation varies based on the band in which the score was placed. The following points provide a high-level overview of this process:

  • The bands are distributed evenly between zero, which is the worst score and one, which is the best score. All bands are given equal weight. This means that if there is a band that has a smaller percentage range, it is equivalent to a band that has a larger range.

  • The relative range of the band that the Band by Value score falls in is determined.

  • Final score is determined based on where that score falls within that range.

The technique used to accomplish this feat varies based on the scoring pattern and the banding method chosen. After the normalization takes place, this value can be compared side by side with other values.

Mathematically, the formula is a base adjustment for the band the value falls into, combined with the In Band Value, which is the relative position of that value within the specified thresholds. For example, if the value falls into the top band of a two-level indicator, the position will always be relative between the 50 percent and 100 percent marks, no matter how wide the range is for those values.

The formula to calculate the In Band Value is as follows:


The formula to calculate the offset for the Increasing Is Better scoring pattern is shown here. This result is added to the In Band Value to get the final score:


The formula to calculate the offset is similar for the Decreasing Is Better scoring pattern. It is flipped and when the calculation is done for the final score the In Band Value is subtracted from this:


For the Closer to Target scoring pattern only, if the score is below the target value, it is subtracted from 1. If it is above the target, it is left alone. The value is then multiplied by 2. This is done to compensate as the range of possible values is doubled because conceptually this pattern is treated as two independent patterns, one above and one below the target.

Tip

If you want to understand more about how the score is calculated in PPS, it is helpful to experiment with fixed value KPIs while using an Excel spreadsheet with the calculations included that verify the outcome.

It is also helpful to show the score on a scorecard. To do this, right-click the target metric on the scorecard, select Metric Settings, and then set either the primary or the secondary value displayed to the score.


Examining a Scoring Walkthrough

The following example demonstrates Increasing Is Better scoring with normalized banding. This example walks you step by step through the scores that are applicable to the Increasing Is Better scoring type. You can use the same formulas and procedure with your own numbers to understand why PPS is giving you whatever scores it does.

The calculations relevant for this scoring pattern are the following:


Consider the following thresholds as defined in Figure 7.

Figure 7. Thresholds for the Increasing Is Better scoring pattern example.

In this example, the worst value is 0, the actual value is .8, and the target value is 1.

The Band by Value would be (0.8 − 0) / (1 − 0), which is .8. This falls between Threshold 1 and Threshold 2. This means the indicator is yellow, which puts this score in the second band.

The In Band Value is calculated at (0.8 − 0.2) / (3*(0.9 − 0.2)), which gives a value of 0.285.

Adding in the band offset adds 1/3 to this value, which results in a normalized score of 0.619.

Decreasing Is Better Scoring with Numeric Value Banding Example

Because the Band by Value when using Numeric Values for banding is the actual, the calculation is only one step less:


Consider the following thresholds on a 10-level indicator as defined in Figure 8.

Figure 8. Thresholds for the Decreasing Is Better scoring pattern example.

In this example, the worst value is 1,000, the actual value is 170, and the target value is 0.

The Band by Value is the Actual (170), which is .8. This falls between Threshold 1 and Threshold 2, which means the indicator is yellow putting this score in the second band.

Normalizing the score with the previous formula gives you the following:


This results in a normalized score of 0.83.

Closer to Target Is Better Scoring with Normalized Banding Example

Listed here are the two calculations relevant for this scoring pattern:


Consider the thresholds shown in Figure 9.

Figure 9. Thresholds for the Closer to Target Is Better scoring pattern example.

In this example, the worst value is 5, the actual value is 7, and the target value is 10.

The Band by Value would be (7 − 5) / (10 − 5), which is 0.133. This falls between the Worst value and Threshold 1, which means the indicator is red putting this score in the bottom band.

As previously specified, because you are doing a Closer to Target Is Better scoring pattern, you need to multiply the In Band Value by 2 to compensate for the two halves to the scoring pattern. The In Band Value will be 2*(0.1333 − .0) / (4*(.5 − 0)), which is 0.133.

Because it is in the bottom band, the band offset will be 0 / 2, resulting in a normalized score of 0.133, or 13.3%.

Examining Rollup Scoring

After the final scores have been calculated at a particular tree level in a scorecard, if there is an objective KPI above these scores, the score is “rolled up” to produce the value for the parent KPI.

Some scores can be weighted more than others, which means they have larger influence over the rolled-up value. Weighting is a scorecard-level setting that can be done through the KPI settings dialog box. Note that weighting is used only if the default calculation is used on the parent KPI.

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