Google matrix of business process management

TL;DR

This paper applies Google matrix and PageRank-based methods to analyze business process models represented as directed graphs, providing new insights into the influence and communication of units within firms.

Contribution

It introduces a novel application of Google matrix analysis to business process models, offering a new tool for strategic decision-making in dynamic markets.

Findings

Two-dimensional ranking reveals influence and communication properties of business units.

PageRank, CheiRank, and 2DRank provide significant insights into process dynamics.

The method offers an efficient way to support company decisions in a competitive environment.

Abstract

Development of efficient business process models and determination of their characteristic properties are subject of intense interdisciplinary research. Here, we consider a business process model as a directed graph. Its nodes correspond to the units identified by the modeler and the link direction indicates the causal dependencies between units. It is of primary interest to obtain the stationary flow on such a directed graph, which corresponds to the steady-state of a firm during the business process. Following the ideas developed recently for the World Wide Web, we construct the Google matrix for our business process model and analyze its spectral properties. The importance of nodes is characterized by Page-Rank and recently proposed CheiRank and 2DRank, respectively. The results show that this two-dimensional ranking gives a significant information about the influence and communication properties of business model units. We argue that the Google matrix method, described here, provides a new efficient tool helping companies to make their decisions on how to evolve in the exceedingly dynamic global market.