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Balancing Flexibility and Compliance in Response to Long-Tailed Business Process Changes (preprint)
ssrn; 2023.
Preprint
in English
| PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.4460901
ABSTRACT
The resilience of process-aware information systems (PAIS) is vital for enterprises' competitiveness in the ever-changing world. Enterprises need continuously maintain business processes in PAIS against uncertainty, resulting in the constant research topic of change management in business process management (BPM). However, previous efforts have left some gaps in dealing with uncertainties in change requirements, either due to high costs or technical incapability. Among these gaps, long-tailed change (LTC), characterized as the urgent and customizable maintenance needs in response to the residual uncertainty, has been largely undeveloped. COVID-19 and some emergent events in 2022 call for more effective solutions to such problems, to mitigate the business loss and to seek emerging opportunities. LTC challenges come from the contention between the degree of flexibility and compliance with business regulations in the context of rapid adaptation. In this paper, we develop a systematic approach to deal with these issues. First, we formulate the problem as a cooperation of multiple participants in the business by leveraging the separation of concerns principle to clarify the division of labor contributing to agility and fine-tuning capability of the approach, and to provide a controllable mechanism to balance operational resilience and dependable adaptation for PAIS. According to the framework, we develop a domain-specific language (DSL) and corresponding techniques to support business people in customizing business processes' behavior to meet circumstances. At the same time, business stakeholders can enforce core functions and service-level agreement (SLA) constraints on the whole business process. We validate our framework through two scenarios, one for design-time model adaptation and the other for run-time instance adaptation. These experiments reveal promising potentials of the framework in adapting to LTC and resolving the contention between agility/flexibility in change and compliance with business regulations, which significantly improves PAIS's resilience to wide-spectrum, low-frequent, sporadic, and transitory events.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-SSRN
Main subject:
COVID-19
/
Amnesia
Language:
English
Year:
2023
Document Type:
Preprint
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