Business processes fragments to promote information quality

Charlie Silva Lopes, Denis Silva da Silveira, João Araujo

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: The primary concern of quality improvement in processes is not the input–output conversion but the information that enables and controls process. This paper presents process fragments for dimensions of information quality (IQ). Design/methodology/approach: Research is based on the design science paradigm to create four fragments of reusable processes, that contemplate the following dimensions of IQ: accessibility, completeness, accuracy and consistency. Findings: There is a theoretical discussion of the concept of IQ in process models, in which the fragments presented provide designers with a reduction in modeling time through reuse. Therefore, the designer has the flexibility to improve the IQ according to the context of each process. Practical implications: The discussion is relevant for both researchers and business designers because it shows that IQ is essential to guarantee the efficient execution of processes. Social implications: Processes modeling can be a challenge for inexperienced designers as they always try to solve a problem from the start, without worrying about the IQ dimensions in process models. Fragments here presented can be (re)used to guide these designers in processes modeling with more IQ. Originality/value: Process modeling approaches provide expressive techniques but do not guarantee IQ in the models. However, these approaches present process fragments that can be easily used to contemplate IQ in process models. In this context, process fragments reuse stands out as an innovative solution to mitigate the shortcomings of process models related to IQ.

Original languageEnglish
Pages (from-to)1880-1901
Number of pages22
JournalInternational Journal Of Quality And Reliability Management
Volume38
Issue number9
DOIs
Publication statusPublished - 26 Oct 2021

Keywords

  • Configurable process modeling
  • Information quality
  • Model fragment
  • Process modeling

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