Although business process management (‘BPM’) is a popular concept, it has not yet been properly theoretically grounded. This leads to problems in identifying both generic and case specific critical success factors of BPM programs. The paper proposes an underlying theoretical framework with the utilization of three theories: contingency, dynamic capabilities and task technology fit. The main premise is that primarily the fit between the business environment and business processes is needed. Then both continuous improvement and the proper fit between business process tasks and information systems must exist. The underlying theory is used to identify critical success factors on a case study from the banking sector.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1611789_code1485980.pdf?abstractid=1611789&mirid=5&type=2

The Critical Success Factors of Business Process Management

https://mail.tku.edu.tw/myday/teaching/992/sms/s/992sms_t1_paper_20110514_the_critical_success_factors_of_business_process_management%20.pdf

The critical success factors of business process management

One of the aims of process mining is to retrieve a process model from a given event log. However, current techniques have problems when mining processes that contain nontrivial constructs, processes that are low structured and/or dealing with the presence of noise in the event logs. To overcome these problems, a new process representation language is presented in combination with an accompanying process mining algorithm. The most significant property of the new representation language is in the way the semantics of splits and joins are represented; by using so-called split/join frequency tables. This results in easy to understand process models even in the case of non-trivial constructs, low structured domains and the presence of noise. This paper explains the new process representation language and how the mining algorithm works. The algorithm is implemented as a plug-in in the ProM framework. An illustrative example with noise and a real life log of a complex and low structured process are used to explicate the presented approach.

/pdf/flexible-heuristics-miner-fhm-32qyv177zl.pdf

Flexible Heuristics Miner (FHM)

A grey-based DEMATEL model for evaluating business process management critical success factors

Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects

There is an abundance of business process modeling techniques that capture and address different aspects of a business process. A limited number of these process models allow further quantitative analysis, and only a few enable structured process improvement. This paper reviews and classifies the main techniques for business process modeling with regard to their analysis and optimization capabilities. Three primary groups are identified, and a selection of representative business process modeling techniques is classified based on these. Similar classification is also presented for the analysis and optimization approaches for business processes that were identified in relevant literature. The main contribution of the paper is that it identifies which types of business process models are suitable for analysis and optimization, and also highlights the lack of such approaches. This paper offers a state-of-the-art review in the areas of business process modeling, analysis, and optimization-underlining that the latter two have not received enough coverage and support in the literature.

Business Process Analysis and Optimization: Beyond Reengineering

Purpose – This paper seeks to examine the area of business process mining, providing an overview of state‐of‐the‐art techniques. An outline of the main problems experienced in the practice of process mining is given along with reference to work that addresses the most challenging issues experienced in this field. This paper also aims to examine the application of soft computing techniques to process‐mining problems.Design/methodology/approach – This paper is based on a comprehensive review of literature covering more than 50 research papers. These papers are analysed to identify current trends and future research directions in the field.Findings – Process‐mining techniques are now becoming available as graphical interface‐driven software tools, where flow diagram representations of processes may be manipulated as part of the mining task. A significant number of papers employ mining heuristics to aid in the task of process discovery. Soft computing algorithms are increasingly being investigated to aid the ...

A review of business process mining: state‐of‐the‐art and future trends

The operational continuity of a business process is an important performance indicator that contributes to the perceived quality of service delivery, hence it is important to understand and monitor the underlying issues that can affect the performance of the process These issues might have been foreseen at the beginning of the process design and deployment phase, or might have emerged during the execution of the process, and must be viewed as risk threats to the business process In most cases risk is only considered from the project management angle or from financial, market, insurance and other general business perspective Operational risk at service provision level receives little attention and thus there is a need to develop methodologies and tools to identify and analyse business operational risks The authors concentrate on operational risk for business process management by introducing a novel way for applying risk assessment frameworks at the process activity level The paper briefly reviews existing risk frameworks and selects the COSO framework as the most appropriate for business processes This framework is modified in order to address and evaluate the main elements of business processes It defines a statistical approach towards operational risk assessment by quantifying risk factors in each activity within a business process for service provision A risk forecast is produced for each activity, and for the whole process, to model associated uncertainties and to contribute in identifying the risk factors that affect the business process objectives To demonstrate the framework, it is applied to a hypothetical process involving setting up a network service These results help to advise on which risk factors need higher attention in order to achieve successful process fulfilment

Operational risk analysis in business processes

Business process redesign and improvement has become an increasingly attractive subject in the wider area of business process intelligence. Although there have been many attempts to establish a business process redesign framework, there is little work on the actual optimisation of business processes with given objectives. Furthermore, most of the attempts to optimise a business process are manual and do not involve a formal automated methodology. This paper proposes a process improvement approach for automated multi-objective optimisation of business processes. The proposed framework uses a generic business process model that is formally defined. The formal definition of business processes is necessary to ensure that the optimisation will take place in a clearly defined, repeatable and verifiable way. Multi-objectivity is expressed in terms of process cost and duration as two key objectives for any business process. The business process model is programmed and incorporated into a software optimisation platform where a selection of multi-objective optimisation algorithms can be applied to a business process design. This paper outlines a case study of business process design that is optimised by the state-of-the-art multi-objective optimisation algorithm NSGA2. The results indicate that, although business process optimisation is a highly constrained problem with fragmented search space, a number of alternative optimised business processes that meet the optimisation criteria can be produced. The paper also provides directions for future research in this area.

/pdf/business-process-improvement-using-multi-objective-2ke3avo7hy.pdf

Basim Majeed

Papers

Business Process Analysis and Optimization: Beyond Reengineering

A review of business process mining: state‐of‐the‐art and future trends

Operational risk analysis in business processes

Business process improvement using multi-objective optimisation

Optimisation of business process designs: An algorithmic approach with multiple objectives