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A new way to diagnose the new product development process based on recurring current reality trees

Janaina Mascarenhas Hornos da Costa (Production Engineering Department, São Carlos School of Engineering, University of São Paulo, São Carlos, Brazil)
Creusa Sayuri Tahara Amaral (Bioengineering Department, Araraquara University, Araraquara, Brazil)
Sânia da Costa Fernandes (Production Engineering Department, São Carlos School of Engineering, University of São Carlos, São Carlos, Brazil)
Henrique Rozenfeld (Production Engineering Department, São Carlos School of Engineering, University of São Paulo, São Carlos, Brazil)

Business Process Management Journal

ISSN: 1463-7154

Article publication date: 4 July 2018

Issue publication date: 18 June 2019

Abstract

Purpose

The purpose of this paper is to propose and describe a method that uses recurrent problems to increase the efficiency and effectiveness of the diagnosis of new product development (NPD) processes and supports the identification of improvement opportunities. The proposed method, called Diagile, is based on recurrent current reality trees (CRTs) and is a new way of building CRTs that includes best project management practices, and the identification and prioritization of improvement opportunities. To support the execution of the method, recurrent problems were identified and a computational tool to aid the diagnosis, a database of improvement opportunities and an automated spreadsheet to prioritize improvement projects were developed.

Design/methodology/approach

The proposed method was evaluated through a controlled experiment at a multinational manufacturer of office supplies.

Findings

The results achieved confirm that the use of the Diagile method increases the diagnostic efficiency and effectiveness when compared to diagnoses performed by the traditional CRT method.

Research limitations/implications

The validity of the method must be tested on a larger scale, since this work involved only one controlled experiment for this purpose. The experiment involved the participation of postgraduate research assistants, who cannot be considered specialists in the diagnosis of NPD. One could question whether the method will be as helpful for proficient users as well. The authors did not have proficient users available to run the experiment. However, the authors believe that such a specialist would save time in carrying out a diagnosis with Diagile, and also be more effective in validating the diagnosis. However, this assumption could not be tested here and can therefore be considered a limiting factor of the experiment. Nevertheless, the positive results of the evaluations of the companies and users of the two case studies corroborate the statement that the objective of this work was attained.

Practical implications

The greater efficiency and effectiveness provided by the proposed Diagile method was also evident in the identification and prioritization of improvement opportunities. The experimental group drew up a more relevant and coherent list of improvement projects than the control group, and provided documentation for these projects in the form of project charts. The authors believe these results can be of a great impact if implemented by practitioners.

Originality/value

This paper proposes a new way to perform diagnostic of NPD process. In particular, this process is well known to be highly strategic, nevertheless, normally excluded out of improvement initiatives because of its complexity. The diagnostic method proposed is a powerful tool to assist practitioners finding systemic improvement opportunities, expanding the assessment to all dimensions of a business process, e.g. people, technology and process activities.

Keywords

Citation

da Costa, J.M.H., Amaral, C.S.T., Fernandes, S.d.C. and Rozenfeld, H. (2019), "A new way to diagnose the new product development process based on recurring current reality trees", Business Process Management Journal, Vol. 25 No. 4, pp. 667-687. https://doi.org/10.1108/BPMJ-01-2017-0020

Publisher

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Emerald Publishing Limited

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