scholarly journals Business process improvement using Object‐Process Methodology

2019 ◽  
Vol 23 (1) ◽  
pp. 36-48
Author(s):  
Jason M. Casebolt ◽  
Ahmad Jbara ◽  
Dov Dori
2016 ◽  
Vol 22 (6) ◽  
pp. 1099-1117 ◽  
Author(s):  
Boyd A. Nicholds ◽  
John P.T. Mo

Purpose The research indicates there is a positive link between the improvement capability of an organisation and the intensity of effort applied to a business process improvement (BPI) project or initiative. While a degree of stochastic variation in applied effort to any particular improvement project may be expected there is a clear need to quantify the causal relationship, to assist management decision, and to enhance the chance of achieving and sustaining the expected improvement targets. The paper aims to discuss these issues. Design/methodology/approach The paper presents a method to obtain the function that estimates the range of applicable effort an organisation can expect to be able to apply based on their current improvement capability. The method used analysed published data as well as regression analysis of new data points obtained from completed process improvement projects. Findings The level of effort available to be applied to a process improvement project can be expressed as a regression function expressing the possible range of achievable BPI performance within 90 per cent confidence limits. Research limitations/implications The data set applied by this research is limited due to constraints during the research project. A more accurate function can be obtained with more industry data. Practical implications When the described function is combined with a separate non-linear function of performance gain vs effort a model of performance gain for a process improvement project as a function of organisational improvement capability is obtained. The probability of success in achieving performance targets may be estimated for a process improvement project. Originality/value The method developed in this research is novel and unique and has the potential to be applied to assessing an organisation’s capability to manage change.


2015 ◽  
Vol 22 (4) ◽  
pp. 215-228 ◽  
Author(s):  
Alejandro Vera-Baquero ◽  
Ricardo Colomo Palacios ◽  
Vladimir Stantchev ◽  
Owen Molloy

Purpose – This paper aims to present a solution that enables organizations to monitor and analyse the performance of their business processes by means of Big Data technology. Business process improvement can drastically influence in the profit of corporations and helps them to remain viable. However, the use of traditional Business Intelligence systems is not sufficient to meet today ' s business needs. They normally are business domain-specific and have not been sufficiently process-aware to support the needs of process improvement-type activities, especially on large and complex supply chains, where it entails integrating, monitoring and analysing a vast amount of dispersed event logs, with no structure, and produced on a variety of heterogeneous environments. This paper tackles this variability by devising different Big-Data-based approaches that aim to gain visibility into process performance. Design/methodology/approach – Authors present a cloud-based solution that leverages (BD) technology to provide essential insights into business process improvement. The proposed solution is aimed at measuring and improving overall business performance, especially in very large and complex cross-organisational business processes, where this type of visibility is hard to achieve across heterogeneous systems. Findings – Three different (BD) approaches have been undertaken based on Hadoop and HBase. We introduced first, a map-reduce approach that it is suitable for batch processing and presents a very high scalability. Secondly, we have described an alternative solution by integrating the proposed system with Impala. This approach has significant improvements in respect with map reduce as it is focused on performing real-time queries over HBase. Finally, the use of secondary indexes has been also proposed with the aim of enabling immediate access to event instances for correlation in detriment of high duplication storage and synchronization issues. This approach has produced remarkable results in two real functional environments presented in the paper. Originality/value – The value of the contribution relies on the comparison and integration of software packages towards an integrated solution that is aimed to be adopted by industry. Apart from that, in this paper, authors illustrate the deployment of the architecture in two different settings.


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