A ‘Peak shaving’ approach to project staff reallocation

Shaikh, Muzaffar

doi:10.1016/s0360-8352(98)00037-0

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…Kang et al (2011), based on interviews, identify individual-and team-level constraints influencing resource allocation in projects. Shaikh (1998) presented a model for project workforce reallocation with the objective of reducing chances of project overrun. In this regard, another study (Thakurta et al, 2009) also observed that a greater emphasis on managing the project human resource in projects that were considered endangered because of requirement volatility could lead to minimization of effort and schedule overrun.…”

Section: Human Resource Managementmentioning

confidence: 99%

Impact of HRM policies on quality assurance under requirement volatility

Thakurta

Suresh

2012

Int J Qual & Reliability Mgmt

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Purpose -Requirements of a project are found to change in various ways during the course of the same. Studies have investigated the effect of requirement volatility on different project parameters like effort, schedule, quality, etc. However, these studies have not looked into how different "patterns" of requirement volatility influence project quality; and which intervention strategies could be effective under the circumstances. This paper aims to address this issue. Design/methodology/approach -The "system dynamics" approach has been used for carrying out the research. Based on a recent finding, we implemented different resource management policies on a validated software process model on waterfall systems development life cycle. Subsequently, we examined the efficacies of these resource management policies on project quality under requirement volatility. Findings -Results indicate variations in quality metrics like error generation, error detection, and quality assurance effort across experimental scenarios as different patterns of requirement volatility and resource management policies impact the software project dynamics in different ways.Research limitations/implications -In absence of any imposed schedule penalty, the extent of variations in project parameters across the policy choices was not very significant. The results are also expected to differ depending upon the project development environment. Practical implications -Findings are expected to assist project managers in deciding on the workforce augmentation plan that would favorably satisfy both the organization's objectives as well as the users' quality requirements under requirement volatility. Originality/value -In present day context of shorter time to market and stringent quality requirements; meeting quality targets become difficult especially in scenarios where requirement volatility is a norm. This paper provides a dynamic view of the phenomenon of how quality gets affected; and explores the efficacy of different resource management strategies in improving quality under the experimental scenarios.

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Section: Human Resource Managementmentioning

confidence: 99%

Impact of HRM policies on quality assurance under requirement volatility

Thakurta

Suresh

2012

Int J Qual & Reliability Mgmt

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“…The literature has generally focused on the goals of increasing retention [1,28], building competitive advantage [4,33,41], operational performance [22,18,40], or coping with scarce IT labor resources [2,42]. Previous work has also addressed the impact of the manager's personnel selection decision on employee task assignments, and hence, on employee training and development opportunities [21].…”

Section: The It Development Decisionmentioning

confidence: 99%

Assessing the IT training and development climate

Wingreen

Blanton

Newton

et al. 2005

Proceedings of the 2005 ACM SIGMIS CPR Conference on Computer Personnel Research

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The Q-methodology was employed to address the managerial problem of deciding which of the firm's personnel development resources should be aimed at which personnel, or groups of personnel, through the various venues of development that are available to the firm for the development of its IT workforce. The procedure identified six interpretable groups of IT professionals that seem to be associated with the development priorities of the IT management, analytical, development & programming, and operations functions. Opportunities are identified for both future research and the practical application of the Q-methodology, its associated instrumentation, and analytical procedure as a managerial decision tool in the context of the internal development of the firm's IT personnel to meet the firm's goals.

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“…For such projects, we should consider the time value of funds when studying on the resource leveling optimization problem, which accords more with construction practice and is of great significance for optimizing the allocation of resources and saving construction funds. As Shaikh M. A. and Talbot F. B. pointed out, construction progress optimization aims to make a reasonable schedule provided that the total construction duration is given, making the resource allocation balanced and dynamic investment minimum [1][2]. For large-scale projects, this point is more important.…”

Section: Introductionmentioning

confidence: 99%

Multi-Resource Leveling Optimization of Large-Scale Projects in Perspective of Dynamic Investment

Ding

Wang

2010

2010 International Conference on Management and Service Science

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According to the main defects of the existing research on resource leveling problem, this paper put forward the multi-resource leveling optimization problem of large-scale construction projects in perspective of dynamic investment. By bringing in the concept of resource entropy and the idea of maximum net present value (NPV), resource leveling optimization model based on entropy function in perspective of dynamic investment was proposed. In order to overcome the shortcomings of traditional algorithms such as heuristic algorithms, the idea and method of searching for the Pareto optimal solutions of the model was presented based on genetic algorithm (GA).

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A ‘Peak shaving’ approach to project staff reallocation

Cited by 5 publications

References 2 publications

Impact of HRM policies on quality assurance under requirement volatility

Impact of HRM policies on quality assurance under requirement volatility

Assessing the IT training and development climate

Multi-Resource Leveling Optimization of Large-Scale Projects in Perspective of Dynamic Investment

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