Business process redesign (BPR) is an organizational initiative for achieving competitive multi-faceted advantages regarding business processes, in terms of cycle time, quality, cost, customer satisfaction and other critical performance metrics. In spite of the fact that BPR tools and methodologies are increasingly being adopted, process innovation efforts have proven ineffective in delivering the expected outcome. This paper investigates the eligibility of BPMN process models towards the application of redesign methods inspired by data-flow communities. In previous work, the transformation of a business process model to a directed acyclic graph (DAG) has yielded notable optimization results for determining average performance of process executions consisting of ad-hoc processes. Still, the utilization encountered drawbacks due to a lack of input specification, complexity assessment and normalization of the BPMN model and application to more generic business process cases. This paper presents an assessment mechanism that measures the eligibility of a BPMN model and its capability to be effectively transformed to a DAG and be further subjected to data-centric workflow optimization methods. The proposed mechanism evaluates the model type, complexity metrics, normalization and optimization capability of candidate process models, while at the same time allowing users to set their desired complexity thresholds. An indicative example is used to demonstrate the assessment phases and to illustrate the usability of the proposed mechanism towards the advancement and facilitation of the optimization phase. Finally, the authors review BPMN models from both an SOA-based business process design (BPD) repository and relevant literature and assess their eligibility. Information 2019, 10, 225 2 of 14 heuristics, which may eliminate redundant activities, decide between case-based and batch work modes, provide alternative task implementations, and compose smaller activities rather than larger ones; and BP behavior heuristics, which regulate the logic within the BP through applying the practices of resequencing, parallelism, knockout, and exception. Another redesign classification scheme is presented in [3] , through a quantitative manner that exploits queue theory to emulate the behavior of facilities (either human or machine) that execute tasks. The problems covered include: (a) the exact task ordering (e.g., whether a strict or partial task execution ordering is chosen); (b) resource allocation (e.g., whether subsequent tasks can be allocated to the same facility or not); (c) whether a specific facility takes management decisions at runtime; and (d) task implementation and considering the possibility of processing a specific task in a specialized rather than a generic manner. Finally, La Rosa et al. [4] introduced the notion of re-configurable processes where, at some point, different tokens in the same application may follow different paths. This notion encompasses modifications in ordering, task implementation and resource allocation, but no exact holistic technique is proposed. In spite of the fact that a thorough analysis of a BP typically sparks various ideas and directions for redesign, it is often approached in a non-systematic way, and is largely considered to be a creative activity. In this sense, parts of the wide-ranging spectrum of potential redesign options could be omitted, as in the majority of creative techniques [1] . The latter enhances the need for narrowing the redesign perspective and specifying the particular aspects and capability of a method to yield better redesign options. For instance, a BP can be reformed to optimize metrics like resource utilization, maximal throughput and flow time, and thus heuristics like task resequencing, parallelism, and task composition have to be applied [5] . Given many such alternatives, there is no systematic way to evaluate these heuristics and the tradeoffs among them. In [6], Kumar and Indradat describe a novel approach based on a formal model for optimizing the benefits or net effects of a redesign practice regarding a baseline design, and illustrate how it can be used to evaluate and compare alternative models in terms of both design and runtime. A limitation is that the user must identify all valid redesign strategies and manually include them in the model, which entails that more semantic information about the process model may be needed by the system. In [7], a flexible framework is proposed for modeling, simulating and reengineering BPs in a cost-effective way. Due to the fact that, in most cases, there are more than one redesign option, these are evaluated against the anticipated benefits and strategic objectives of the organization. The optimal ones are manually selected and further analyzed to identify neglected problems in a procedure that comprises a BPR methodology. A novel approach presented in [8] aims to provide automated performance optimization of the BP execution by transferring knowledge from the related field of data-centric workflows. This is achieved through a transformation process of an initial BPMN model to an equivalent annotated directed acyclic graph (DAG) and the optimization of the average performance of process executions. Data-flow optimization can lead to performance improvements, and more importantly, has the potential to lift the burden of manually fixing all implementation details from the data-flow designers (a key motivation for automated optimization solutions [9] ). An important factor that is overlooked in the majority of such approaches is the lack of an evaluation mechanism for the BP models to be redesigned. In the majority of existing redesign approaches, there is no consideration of the model type, its complexity level, the overall redesign feasibility, or, most importantly, the applicability of particular redesign heuristic(s). One of the obstacles for evaluating BPs is their complexity [10] , and new methodologies are needed to handle this complexity, especially in terms of how to integrate process information into enterprise networks [11] . In this paper, the authors introduce an evaluation mechanism for BPMN models that is motivated by this research gap and the adversities encountered in previous work [8] . This is achieved through a set of criteria that emulates a decision support system and assesses essential model characteristics like complexity, redesign capability and normalization, to render a model eligible for further transformation and optimization. The proposed mechanism can also be potentially used for supporting the creation of reusable component BP models. In [12] , a set of activities, including the execution of a decomposition
For example, in Reference REF , the authors focus on the presentation of the evaluation mechanism that measures the effectiveness of the BPMN model and its ability to effectively transform it into a directed acyclic graph and to determine the average efficiency of process execution.
Eligibility of BPMN Models for Business Process Redesign
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