Recognition of resource patterns in human-centric processes : a case study

Abstract

Business experts need to improve business processes by increasing process efficiency and reducing process costs. To achieve this, a common method is to capture a series of repeatedly conducted process activities and their structure, i.e. the business logic of the process, and then enact process execution based on it. However, there exist informal processes, which are human-centric processes that are highly dynamic. Since this approach assumes the existence of predictable business logic of the process, it does not apply for management of informal processes. The Informal Process Essentials (IPE) model is a modeling approach for informal processes. This model depicts informal processes by documenting resources used in these process. Through this approach, we are able to retain best practice and knowledge accumulated in the processes. Based on this approach, there is also the InProXec method to enable the application of the IPE approach in organizations. In this thesis work, we want to validate the concepts introduced in the InProXec method using a case study on the jclouds project. To achieve this aim, we introduce the concept of a generic mapping mechanism and an evolving correlation coefficient function. Based on these concepts, we present the Informal Process Discoverer (IPD) service. The IPD service is an implementation of the discovery of IPE models. The test results of the IPD service have shown that the service is successful in discovering the IPE model and giving process recommendations. For example, using an informal process model with includes 7 human resources and 2 GitHub repositories as input, we are able to discover 74 other resources that participate in the process including 65 human resources and 9 Git repositories.