Research and development (R&D) portfolio management in the electric utility sector: Does it change for the service sector?

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

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.

Scenarios for optimizing timing for new product exits: a trifecta of models' predictive performances

Purpose

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

Design/methodology/approach

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

Findings

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

Originality/value

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.

R&D portfolio management practices in Brazilian electric power utilities

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.