From the stone age to the cloud: A case study of risk-focused process improvement

Danny Ting Yi Ho, Michael zur Muehlen

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations

Abstract

Organizations strive to continually improve organizational performance while maintaining compliance to increasingly complex rules and regulations. Several methods and techniques for the identification and management of operational risks in business processes have been proposed in the academic literature, yet there are few examples of practical applications. This paper addresses this gap through a case study of a process improvement project that employed some of the proposed risk and compliance management techniques. We describe a business process reengineering project within the purchasing and accounts payable operations of a university United States. The project focused on improving service quality by improving the transparency and predictability of operations through the introduction of a workflow management system. We outline the stepwise transformation of manual process operations through technology, and discuss the risk and compliance objectives identified throughout the project and their impact on process design. This case study illustrates how process re-engineering techniques can improve process designs while balancing performance and compliance objectives. It provides guidance for the selection of an appropriate level of abstraction during process analysis and demonstrates how process objectives and technology capabilities shape the design of to-be processes.

Original languageEnglish
Pages1024-1033
Number of pages10
StatePublished - 2009
Event20th Australasian Conference on Information Systems, ACIS 2009 - Melbourne, VIC, Australia
Duration: 2 Dec 20094 Dec 2009

Conference

Conference20th Australasian Conference on Information Systems, ACIS 2009
Country/TerritoryAustralia
CityMelbourne, VIC
Period2/12/094/12/09

Keywords

  • Process improvement
  • Regulatory compliance
  • Risk management
  • Value-focused modeling

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