Managing Knowledge Requirements in the NPD Portfolio Selection Process Using Knowledge Clustering and Prioritization: A Case Study of an Australian Train Operator

Dastaki, Mohsen Sadeghi; Mahootchi, Masoud; Moehler, Robert; Afrazeh, Abbas

doi:10.1109/tem.2022.3202862

Cited by 5 publications

(5 citation statements)

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“…The ability of codified boundary objects to span complex boundaries is dependent upon object capacity and, in turn, structure and characteristics. The capacity of a particular boundary object to support knowledge transfer across increasingly complex boundaries, including syntactic, semantic, pragmatic, and temporal boundaries (Carlile, 2002, 2004; Whyte & Nussbaum, 2020), is constrained by the structure and characteristics of that object (Rosenkranz et al, 2014). We suggest that these challenges can be usefully reconceptualized as running the learning codification “gauntlet” that constrains project practitioners’ ability to codify project learnings.…”

Section: Discussionmentioning

confidence: 99%

“…Four key boundary types identified in the literature, representing increasing boundary complexity, are “syntactic,” “semantic,” “pragmatic,” and “temporal” boundaries (Carlile, 2002, 2004; Carlile & Rebentisch, 2003; Abraham et al, 2015; Maaninen-Olsson & Müllern, 2009; Whyte & Nussbaum, 2020). The extent to which codified boundary objects afford complex boundary spanning across increasingly complex boundaries hinges on inherent object capacity, underpinned by object structure and characteristics (Rosenkranz et al, 2014), with Ferres and Moehler (2023) proposing a schema of 30 discrete characteristics associated with boundary spanning capacity for project-to-project learning.…”

Section: Literature Review and Thematic Analysismentioning

confidence: 99%

“…Project-to-project learning is essential to prevent the reinvention of the wheel. Such learning can span a myriad of potential sharing interactions across individual, project, and parent organization levels (Prencipe & Tell, 2001;Bakker et al, 2011), and can support improved decision-making (Williams, 2008), common challenge identification and resolution (Boh, 2007;Yap et al, 2017), the avoidance of redundant work and repeated mistakes (Carrillo, 2005;Schindler & Eppler, 2003;Wiewiora et al, 2014), capability development (Schindler & Eppler, 2003;Moehler et al, 2018), harmonized methods (Hanisch et al, 2009), and accelerated product development (Sadeghi Dastaki, et al, 2022). Although the benefits of project learning are compelling, learning lessons is complex in practice (Fuller et al, 2010), with project temporality resulting in a "learning paradox" (Bakker et al, 2011, p. 494) whereby valuable knowledge, including learnings (also referred to as lessons learned within this article), are subject to knowledge fragmentation and "project amnesia" (Schindler & Eppler, 2003, p.p 219-220).…”

Section: Introductionmentioning

confidence: 99%

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Running the Codification Gauntlet: Why Intent Alone Cannot Afford the Codification of Project Learnings

Ferres,

Moehler

2024

Project Management Journal

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This article presents a first synthesis of the ability to codify challenges that constrain project learning codification and, in turn, limit the sharing of learnings between projects at scale. An improved understanding of these challenges supports the externalized sharing of project learnings, between communities of practice, that can scale beyond the temporal, geographical, and organizational barriers that constrain personalized sharing. Through an integrative cross-domain literature review, a learning codification gauntlet of seven key ability to codify challenges is reconceptualized, and significant new research gaps are identified for further investigation, including: the operation of identified challenges in practice, challenge interrelationships, and challenge-cumulative effects on project-to-project learning outcomes.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Review and Thematic Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Running the Codification Gauntlet: Why Intent Alone Cannot Afford the Codification of Project Learnings

Ferres,

Moehler

2024

Project Management Journal

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“…The second of the boundary spanning capacities, “interpretative and translation”, encompasses those characteristics that enable communication in the context of uncertainty (Carlile, 2002) such that common meaning can be developed (Abraham et al ., 2015; Dastaki et al ., 2022) and relate to: declared capture approach; authorship; declared specialised knowledge; context; summary information; narratives and storytelling; quotations; recommended actions; abstracted insights; annotations; engaging format; illustrations and graphics; and, related artefacts. Declared capture approach: A declared capture approach describes to the receiver the circumstances and process applied during boundary object creation to assist the receiver's interpretation and translation of object content. Declared capture approach information can include the timeliness of project experience capture at key milestones, the extent to which the entire project team was engaged in the experience capture process, whether an external neutral moderator was utilised and how collective insights evaluation was approached (Schindler and Eppler, 2003).…”

Section: What Structural Characteristics Do Boundary Objects Need To ...mentioning

confidence: 99%

Structuring concrete boundary objects for project-to-project learning: a state-of-practice review

Ferres,

Moehler

2023

IJMPB

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PurposeEffective project learning can prevent projects from repeating the same mistakes; however, knowledge codification is required for project-to-project learning to be up-scaled across the temporal, geographical and organisational barriers that constrain personalised learning. This paper explores the state of practice for the structuring of codified project learnings as concrete boundary objects with the capacity to enable externalised project-to-project learning across complex boundaries. Cross-domain reconceptualisation is proposed to enable further research and support the future development of standardised recommendations for boundary objects that can enable project-to-project learning at scale.Design/methodology/approachAn integrative literature review method has been applied, considering knowledge, project learning and boundary object scholarship as state-of-practice sources.FindingsIt is found that the extensive body of boundary object literature developed over the last three decades has not yet examined the internal structural characteristics of concrete boundary objects for project-to-project learning and boundary-spanning capacity. Through a synthesis of the dispersed structural characteristic recommendations that have been made across examined domains, a reconceptualised schema of 30 discrete characteristics associated with boundary-spanning capacity for project-to-project learning is proposed to support further investigation.Originality/valueThis review makes a novel contribution as a first cross-domain examination of the internal structural characteristics of concrete boundary objects for project-to-project learning. The authors provide directions for future research through the reconceptualisation of a novel schema and the identification of important and previously unidentified research gaps.

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“…A large body of research has shown that NPD processes fluctuate and are subject to enormous uncertainty in areas such as technical, organizational, and market acceptance [16][17][18][19][20][21][22]. An obvious gap exists between the two philosophies.…”

Section: Introductionmentioning

confidence: 99%

Risk Analysis: Changing the Story with the Statistical Stochastic Process and VaR

2023

Axioms

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With the dramatically increased demand for data analysis, statistical techniques play a key role in modern society for both academics and practitioners. Statistical techniques have been evolving from descriptive statistics to statistical inference in fields that require the evaluation of uncertainty and the quantification of risks. With the growing complexity of various fields, such as manufacturing and industrial applications, as well as business decision-making, modeling and quantifying risks has become essential. In this paper, we aimed to use statistical risk analysis and Value at Risk (VaR) to address the decision problem for project portfolios. Traditional economic evaluation criteria used in the management of project portfolios, as they pertain to new product development (NPD), are based on the assumption that pinpoint estimations will remain constant in the future. The assumption that NPD is static, however, is clearly unrealistic due to the inherent uncertainty of NPD projects. In this study, we stress the critical role that uncertainty plays in the selection of NPD portfolios, and clarify the reasons why it must not be overlooked. Using Value at Risk measurements, we show how uncertainty plays a critical role in evaluating and prioritizing NPD portfolios. The implications of this study regarding statistically modeling NPD portfolio decisions are provided for academics and practitioners.

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Managing Knowledge Requirements in the NPD Portfolio Selection Process Using Knowledge Clustering and Prioritization: A Case Study of an Australian Train Operator

Cited by 5 publications

References 53 publications

Running the Codification Gauntlet: Why Intent Alone Cannot Afford the Codification of Project Learnings

Running the Codification Gauntlet: Why Intent Alone Cannot Afford the Codification of Project Learnings

Structuring concrete boundary objects for project-to-project learning: a state-of-practice review

Risk Analysis: Changing the Story with the Statistical Stochastic Process and VaR

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