Experimental Verification on Human-Centric Network-Based Resource Allocation Approaches for Process-Aware Information Systems

Abstract

Efficient allocating human resource obtains significant advantages to business operations in enterprises. Manipulating the available human resources of a business optimizes the expense of developing products and services, improves work productivity, and brings more value to the business. In the process of creating products and benefits in the enterprise, a network of working relationships is formed among employees in the organization. In this paper, we propose an approach to support decision-making on human resource allocation in an organization based on the human-centric network discovered from the event logs. To be more precise, the knowledge derived from human-centric networks formed through the operation phases of the information systems is used to make resource allocation strategies in the organizations. Using the appropriateness probabilities and social network metrics for allocating human resources, we clarify efficiently allocating resources based on different metrics. The system architecture and the scenarios are also described for planning human resources allocation based on these networks. Furthermore, we use real-life data set for getting experimental verification and proving the proposal. This approach will be a promising solution to support businesses effectively allocating resources in their organizations.

Keywords

• Human-centric network
• human resources allocation
• business process management
• process mining
• process-aware information system