Abstract
Purpose – This paper reviews empirical studies on process mining in order to understand its use by organizations. The aim is further to outline future research opportunities.
Design/methodology/approach – We propose a classification model that combines core conceptual elements of process mining with prior models from technology classification from the enterprise resource planning (ERP) and business intelligence field. Our model incorporates an organizational usage, a system-orientation and service nature, adding a focus on physical services. Our application is based on a systematic literature review of 144 research papers.
Findings – The results show that, thus far, the literature has been chiefly concerned with realization of single business process management systems in single organizations. We conclude that cross-system or cross-organizational process mining is underrepresented in the ISR, as is the analysis of physical services.
Practical implications – Process mining researchers have paid little attention to utilising complex use cases and mining mixed physical-digital services. Practitioners should work closely with academics to overcome these knowledge gaps. Only then will process mining be on the cusp of becoming a technology that allows new insights into customer processes by supplying business operations with valuable and detailed information.
Originality/value – Despite the scientific interest in process mining, particularly scant attention has been given by researchers to investigating its use in relatively complex scenarios, e.g. cross-system and cross-organizational process mining. Furthermore, coverage on the use of process mining from a service perspective is limited, which fails to reflect the marketing and business context of most contemporary organizations, wherein the importance of such scenarios is widely acknowledged. The small number of studies encountered may be due to a lack of knowledge about the potential of such scenarios as well as successful examples, a situation we seek to remedy with this study.
Design/methodology/approach – We propose a classification model that combines core conceptual elements of process mining with prior models from technology classification from the enterprise resource planning (ERP) and business intelligence field. Our model incorporates an organizational usage, a system-orientation and service nature, adding a focus on physical services. Our application is based on a systematic literature review of 144 research papers.
Findings – The results show that, thus far, the literature has been chiefly concerned with realization of single business process management systems in single organizations. We conclude that cross-system or cross-organizational process mining is underrepresented in the ISR, as is the analysis of physical services.
Practical implications – Process mining researchers have paid little attention to utilising complex use cases and mining mixed physical-digital services. Practitioners should work closely with academics to overcome these knowledge gaps. Only then will process mining be on the cusp of becoming a technology that allows new insights into customer processes by supplying business operations with valuable and detailed information.
Originality/value – Despite the scientific interest in process mining, particularly scant attention has been given by researchers to investigating its use in relatively complex scenarios, e.g. cross-system and cross-organizational process mining. Furthermore, coverage on the use of process mining from a service perspective is limited, which fails to reflect the marketing and business context of most contemporary organizations, wherein the importance of such scenarios is widely acknowledged. The small number of studies encountered may be due to a lack of knowledge about the potential of such scenarios as well as successful examples, a situation we seek to remedy with this study.
Original language | English |
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Journal | Business Process Management Journal |
Volume | 24 |
Issue number | 4 |
Pages (from-to) | 900-922 |
Number of pages | 23 |
ISSN | 1463-7154 |
DOIs | |
Publication status | Published - 2018 |
Keywords
- Service-dominant logic
- Systematic literature review
- Process mining
- Cyber-physical systems
- Organizational perspective