Title

A new strategic approach for R&D project portfolio selection using efficiency-uncertainty maps

Document Type

Article

Publication Date

1-2-2023

DOI

https://doi.org/10.1108/BIJ-02-2022-0129

Abstract

Purpose: New business practices and the globalization of markets force firms to take innovation as the fundamental pillar of their competitive strategy. Research and Development (R&D) plays a vital role in innovation. As technology advances and product life cycles become shorter, firms rely on R&D as a strategy to invigorate innovation. R&D project portfolio selection is a complex and challenging task. Despite the management's efforts to implement the best project portfolio selection practices, many projects continue to fail or miss their target. The problem is that selecting R&D projects requires a deep understanding of strategic vision and technical capabilities. However, many decision-makers lack technological insight or strategic vision. This article aims to provide a method to capitalize on the expertise of R&D professionals to assist managers in making informed and effective decisions. It also provides a framework for aligning the portfolio of R&D projects with the organizational vision and mission.

Design/methodology/approach: This article proposes a new strategic approach for R&D project portfolio selection using efficiency-uncertainty maps.

Findings: The proposed strategy plane helps decision-makers align R&D project portfolios with their strategies to combine a strategic view and numerical analysis in this research. The proposed strategy plane consists of four areas: Exploitation Zone, Challenge Zone, Desperation Zone and Discretion Zone. Mapping the project into this strategic plane would help decision-makers align their project portfolio according to the corporate perspectives.

Originality/value: The new approach combines the efficiency and uncertainty dimensions in portfolio selection into an integrated framework that: (i) provides a complete representation of the stochastic decision-making processes, (ii) models the endogenous uncertainty inherent in the project selection process and (iii) proposes a computationally practical and visually unique solution procedure for classifying desirable and undesirable R&D projects.

Language

English

Comments

This article is the authors' final published version in Benchmarking: An Interantional Journal, Volume ahead-of-print, Issue ahead-of-print, January 2023, Article number 14635771.

The published version is available at https://doi.org/10.1108/BIJ-02-2022-0129. Copyright © Emerald Publishing Limited.

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