Expected Optionality

View in library docs
eOpt(g)\mathit{e}\mathit{Opt}(g)
Dimension:
Flexibility
Granularity:
Group of cases

Description

Ratio between the expected number of optional activities that are instantiated in a case belonging to a group of cases, and the expected number of activities that occur in a case belonging to a group of cases. \newline An activity is considered optional if there is at least one case in the event log where it does not occur.

Potential use

Process with multiple activities that are not instantiated in every case.

Assumptions

A greater number of optional activities is desired, as it implies a greater capability to address unexpected situations.

Desired Value:

MAXIMIZE

Required attributes

act
case

Equations

Formula for practitioners

cgOptA(c)cgA(c)\frac{\sum _{c \in g} \mathit{OptA}(c)}{\sum _{c \in g} \mathit{A}(c)}

OptA(c)\mathit{OptA}(c) returns the optional activity count for case cc.
A(c)\mathit{A}(c) returns the number of unique activities in case cc.

Formal Definition

cgOptA(c)cgA(c)\frac{\sum _{c \in g} \mathit{OptA}(c)}{\sum _{c \in g} \mathit{A}(c)}

Tags

act
case

Python implementation

This indicator is implemented in the process_performance_indicators Python library.

process_performance_indicators.indicators.flexibility.groups.expected_optionality