Effort Estimation of Business Process Modeling through Clustering Techniques

A critical activity in project planning, especially in business process modeling (BPM) projects, is effort estimation. It involves several dimensions such as business domain complexity, team and technology characteristics, turning estimation into a difficult and inaccurate task. In order to reduce this difficulty, background knowledge about past projects is typically applied; however, it is too costly to be carried out manually. On the other hand, Data Mining enables the automatic extraction of new nontrivial and useful knowledge from existing data. This paper presents a new approach for BPM project effort estimation using data mining through clustering technique. This approach was successfully applied to real dat

Tendências do BPM

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de InformaçãoAtualmente, as organizações encontram-se inseridas em ambientes de mercado cada vez mais competitivos, deparando-se com várias dificuldades, em que face a estas, necessitam de encontrar soluções. Por essa razão, viram o BPM como uma solução para melhorar o seu negócio. Um dos objetivos do BPM é ter a capacidade de identificar, monitorar e otimizar processos de negócio cujo resultado final é um conjunto de atividades realizadas. Com base nesta monitorização e otimização, as organizações tornam-se capazes de identificar possíveis lacunas nos seus processos e com isto melhorá-los. Com isto, verificou-se a falta de informação existente cientificamente em relação à identificação de novas tendências para o BPM. Neste sentido, com este trabalho propomos realizar uma investigação seguindo a metodologia de pesquisa em Design Science Research, em que iniciamos uma pesquisa de levantamento de tendência seguindo a abordagem proposta por Webster e Watson (2002), com base em duas conferências internacionais em BPM de ranking elevado, em que se identificou os tópicos mais abordados como também problemas e soluções desde 2013 até 2015. Posteriormente, com informação recolhida ao longo de três anos, através da criação de um framework identificamos algumas tendências para o BPM, de forma a melhorá-lo. Para garantir a credibilidade dos resultados, através da criação de um inquérito por questionário realizou-se a avaliação dos resultados obtidos.Nowadays, the market gets more and more competitive, thus companies need to learn how to manage and find the right solutions for their business when facing challenges. For that reason, they saw BPM as a great tool to expand their business. One of the features of BPM is the capacity to identify, monetize and optimize processes within the business which ultimately allow for an aggregation of performed activities. Thanks to these features, the business have been capable of identifying possible gaps in their processes and how to improve them. With this, it was verified the lack of scientific information regarding the identification of new trends for BPM. Therefore, with this work we propose to conduct an investigation that follows the searching methodology in Design Science Research, where we initiate a search of lifting trends as proposed by Webster and Watson (2002). This is based on two international conferences on BPM, in which it identified the most discussed topics and also the problems and solutions since 2013 until 2015. After this investigation, with collected information over 3 years, through the creation of framework we identify some BPM trends. To approve this results, we created a survey that was held an evaluation of the final results

An Effort Prediction Model Based on BPM Measures for Process Automation

BPM software automation projects require different approaches for effort estimation for they are developed based on business process models rather than traditional requirements analysis outputs. In this empirical research we examine the effect of various measures for BPMN compliant business process models on the effort spent to automate those models. Although different measures are suggested in the literature, only a few studies exist that relate these measures to effort estimation. We propose that different perspectives of business process models need to be considered such as behavioral, organizational, functional and informational to determine the automation effort effectively. The proposed measures include number of activities, number of participating roles, number of outputs from the process and control flow complexity. We examine the effect of these measures on the automation effort and propose a prediction model developed by multiple linear regression analysis. The data were collected from a large IS integration project which cost 300 person-months along a three-year time frame. The results indicate that some of the measures collected have significant effect on the effort spent to develop the BPM automation software. We envision that prediction models developed by using the suggested approach will be useful to make accurate estimates of project effort for BPM intensive software development projects