PPI Repository

Expected Successful outcome Unit Count

\mathit{e}\mathit{SUC}\mathit{^{\times}}(g)

\mathit{\times} \in \{\mathit{sgl}, \mathit{sum}\}

Dimension:

Quality

Granularity:

Group of cases

Description

Expected outcome units associated with all activity instances in a case belonging to a group of cases, after deducting those that were unsuccessfully completed.

Potential use

Process where the outcome of activity instances, as well as whether they are successful or not, can be measured.

Assumptions

Maximizing the number of successful outcome units is desirable.

Desired Value:

MAXIMIZE

Required attributes

actinst
case
type
uns
unt

Equations

Formula for practitioners

$\frac{\mathit{SUC}(g)}{\mathit{C}(g)}$

$\mathit{SUC}(g)$ returns the total successful outcome unit count for group $g$ .
$\mathit{C}(g)$ returns the number of cases in group $g$ .

Formal Definition

$\frac{\mathit{SUC}\mathit{^{\times}}(g)}{\mathit{C}(g)}$
The $\mathit{\times}$ indicates that the PPI can take multiple forms, in this case, $\mathit{\times} \in \{\mathit{sgl}, \mathit{sum}\}$ . If $\mathit{\times} = \mathit{sgl}$ , then the function considers single events of activity instances for outcome unit calculations, i.e., it uses $\mathit{SUC}\mathit{^{sgl}}$ ; if $\mathit{\times} = \mathit{sum}$ , then the function considers the sum of all events of activity instances for outcome unit calculations, i.e., it uses $\mathit{SUC}\mathit{^{sum}}$ .

Python implementation

This indicator is implemented in the process_performance_indicators Python library.

process_performance_indicators.indicators.quality.groups.expected_successful_outcome_unit_count

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