A Systematic Method for Specifying Effective Value Models

Lee, Benjamin D.; Binder, William R.; Paredis, Christiaan J. J.

doi:10.1016/j.procs.2014.03.029

Cited by 7 publications

(5 citation statements)

References 38 publications

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“…The quantified amounts of value, risk, and opportunity also provide an enabler for applying options- and scenario-based methods to project planning and valuation (e.g., Lévárdy & Browning, 2009; Wang & Yang, 2012). They also provide an opportunity for the direct integration of project management methods with emerging techniques in the engineering literature on value-based design (e.g., Kannan, Mesmer, & Bloebaum, 2017; Lee, Binder, & Paredis, 2014; Lee & Paredis, 2014; Yang, Ishii, & Karandikar, 2005).…”

Section: Resultsmentioning

confidence: 99%

Planning, Tracking, and Reducing a Complex Project’s Value at Risk

Browning

2018

Project Management Journal

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Uncertainty, risk, and rework make it extremely challenging to meet goals and deliver anticipated value in complex projects, and conventional techniques for planning and tracking earned value do not account for these phenomena. This article presents a methodology for planning and tracking cost, schedule, and technical performance (or quality) in terms of a project's key value attributes and threats to them. It distinguishes four types of value and two general types of risks. The "high jumper" analogy helps to consider how high the "bar" is set for a project (its set goals) and therefore how challenging and risky it will be. A project's capabilities as a "jumper" (to clear the bar and meet its goals) determine the portion of its value at risk (VaR). By understanding the amounts of value, risk, and opportunity in a project, project managers can design it for appropriate levels of each. Project progress occurs through reductions in its VaR: Activities "add value" by chipping away at the project's "anti-value"-the risks that threaten value. This perspective on project management incentivizes generating results that eliminate these threats, rather than assuming that value exists until proven otherwise.

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Section: Resultsmentioning

confidence: 99%

Planning, Tracking, and Reducing a Complex Project’s Value at Risk

Browning

2018

Project Management Journal

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“…Even if full data would be available, value models could easily become incomprehensible to those stakeholders who do not possess specialist knowledge in the technical domain (Collopy 2012), hindering communication among the decision makers. Lee et al (2014) further notice that value functions often fail to remain consistent with the established axioms and results of decision theory. Value is often defined and calculated separately from cost and risk, and it is not often clear whose value is being captured and what the preference aggregation rationale is.…”

Section: Limitations Of Monetary Objective Functions For Valuementioning

confidence: 97%

“…Lee et al. (2014) further notice that value functions often fail to remain consistent with the established axioms and results of decision theory. Value is often defined and calculated separately from cost and risk, and it is not often clear whose value is being captured and what the preference aggregation rationale is.…”

Section: Value Models In Engineering Design: a Literature Reviewmentioning

confidence: 99%

“…Value models are often criticized for being of impractical use in engineering design problems. This is because the lack of confidence in the quality of the monetary functions can stimulate costly and time-consuming iterations – a phenomenon referred to as ‘tragic feedback loop’ (Lee, Binder & Paredis 2014) – in the attempt to capture any existing knowledge item, no matter how insignificant.…”

Section: Introduction and Objectivesmentioning

confidence: 99%

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Iterative value models generation in the engineering design process

Bertoni

2019

Des. Sci.

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Value models are increasingly discussed today as a means to frontload conceptual design activities in engineering design, with the final goal of reducing cost and rework associated with sub-optimal decisions made from a system perspective. However, there is no shared agreement in the research community about what a value model exactly is, how many types of value models are there, their input–output relationships and their usage along the engineering design process timeline. Emerging from five case studies conducted in the aerospace and in the construction equipment industry, this paper describes how to tailor the development of value models in the engineering design process. The initial descriptive study findings are summarized in the form of seven lessons learned that shall be taken into account when designing value models for design decision support. From these lessons, the paper proposes a six-step framework that considers the need to update the nature and definition of value models as far as new information becomes available, moving from initial estimations based on expert judgment to detailed quantitative analysis.

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“…In the domain of manufacturing, sustainability considerations are often linked to economic growth indicators (Joung et al, 2012), ranging from the overall net profit earned by the organization (Hu and Bidanda, 2009), manufacturing costs (Witik et al, 2012), or Return On Investment (ROI) (Lee et al, 2014). Assessment methods often make use of Discrete Event Simulation (DES) to complement an LCA analysis (Thiede et al, 2013), or to more precisely account for sustainability indicators when dealing with Value Stream Mapping (VSM) (Paju et al, 2010).…”

Section: Environmental Impact Assessment and Life Cycle Assessmentmentioning

confidence: 99%

Assessing sustainability and value of manufacturing processes: a case in the aerospace industry

Hallstedt

Bertoni

Isaksson

2015

Journal of Cleaner Production

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a b s t r a c tIn spite of the growing awareness and significance of accounting for sustainability aspects in product development, design decision support is still immature in this end compared to other decision support areas, such as product performance and manufacturability. This paper proposes a novel decision support method that combines qualitative sustainability assessment techniques with a quantitative analysis, without losing transparency and still covering a full sustainability perspective. The aim is to contribute to an understanding for how to enable value assessment of sustainability issues already in early product development situations. The method, named Sustainability Assessment and Value Evaluation, combines two qualitative sustainability assessment techniques with a quantitative Net Present Value analysis based on alternative future scenarios. A case study, related to the development of a new hightemperature aero-engine component, illustrates both how the sustainability assessment identifies hotspots and clarifies potential sustainability consequences for a new product technology, and how Net Present Value is used to assess alternative solution strategies based on the hotspot, to facilitate early stage decision-making in design. The paper argues that the method serves two main purposes: i) to make sustainability consequences more concrete and understandable during design concept selection activities, rather than to have an exact measurement, and ii) to simplify and prioritize, systematically asking what is important in the sustainability analysis, rather than to reduce the sustainability problem. The method allows undertaking the sustainability assessment in a more structured way than what happens today in preliminary design, through scenario building based on socio-ecological assessments, including back-casting to cover the longer time perspective. In addition, the Sustainability Assessment and Value Evaluation-method provided the design team of a means for displaying sustainability consequences on an equal basis with other decision support tool results.

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A Systematic Method for Specifying Effective Value Models

Cited by 7 publications

References 38 publications

Planning, Tracking, and Reducing a Complex Project’s Value at Risk

Planning, Tracking, and Reducing a Complex Project’s Value at Risk

Iterative value models generation in the engineering design process

Assessing sustainability and value of manufacturing processes: a case in the aerospace industry

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