R&D portfolio management practices in Brazilian electric power utilities

Eduardo Kazumi Yamakawa · Thayla Tavares De Sousa Zomer · Paulo Augusto Cauchick Miguel · Catherine P. Killen

5 citations0/0 files storedBenchmarking An International Journal

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Abstract

Purpose Project portfolio management (PPM) has been recognized as critical for the productivity of research and development (R&D) investments, but empirical research on PPM use and outcomes in non-commercial R&D environments is limited. The purpose of this paper is to investigate PPM processes and outcomes in a unique R&D context within Brazilian electric power utilities. Design/methodology/approach An exploratory best practice survey was used to collect data on PPM processes, methods and performance results in the power sector. Analysis of the data employs descriptive statistics and comparative analysis in the light of the literature. Findings The findings emphasize the importance of strategic value and the need for PPM to be customized for the specific context. The results also demonstrate the importance of adopting selection criteria and measures in accordance with the organizations strategic goals. Practical implications The findings may help organizations better understand how PPM can be tailored for the environment. PPM managers in utilities and other non-commercial R&D environments may find guidance in tailoring and improving their PPM approaches. Originality/value The contributions of this paper are twofold. First, it provides empirical findings to support PPM concepts on strategic alignment and the importance of context by demonstrating how PPM works to deliver strategy in a unique environment. Second, it contributes to the management of R&D projects and portfolios in power utilities, providing an example and analysis that may offer guidance. The contributions from this study may also offer insights that are valuable for R&D management in other utilities, or for R&D management in general.

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References

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2019Proposal and Solution of a Mixed-Integer Nonlinear Optimization Model That Incorporates Future Preparedness for Project Portfolio Selection

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