Stochastic model of business process decomposition

TL;DR

This paper models business process decomposition as a Galton Watson stochastic process, enabling estimation of decomposition complexity and labor input, thus improving process modeling accuracy.

Contribution

It introduces a stochastic model for business process decomposition, providing a quantitative framework for estimating decomposition depth and size.

Findings

Decomposition can be represented as a Galton Watson branching process.

The model estimates the depth and total elements of decomposition trees.

Results support empirical limits on business function decomposition.

Abstract

Decomposition is the basis of works dedicated to business process modelling at the stage of information and management systems analysis and design. The article shows that the business process decomposition can be represented as a Galton Watson branching stochastic process. This representation allows estimating the decomposition tree depth and the total amount of its elements, as well as explaining the empirical requirement for the business function decomposition (not more than 7 elements). The problem is deemed relevant as the obtained results allow objectively estimating the labor input in business process modelling.