3,489 research outputs found
Optimization of job allocation in construction organizations to maximize workers' career development opportunities
© 2019 American Society of Civil Engineers. Workforce planning in the construction industry too often ignores the symbiotic relationship between employee and employer objectives by overly concentrating on corporate objectives such as maximizing productivity at the expense of construction workers' career development needs. Overall, the consequence of this approach is suboptimal performance. To address this problem, this paper presents an innovative multiobjective model that enables managers to optimize the relationship between these interdependent corporate priorities. The proposed model was implemented and solved using mixed-integer nonlinear programming on a case study involving the allocation of tasks to employees with different skill levels in a multidisciplinary engineering consulting company. While leading to a small loss of productivity, the results show a significant improvement in the career development of workers compared to conventional productivity-oriented workforce planning models, with on average 8.6% improvement in employees' closeness to their ideal skill set. Furthermore, the model produced Pareto-optimal points and a Pareto curve that enabled client-model users to select optimum job allocation based on their preferences. This research represents a paradigm shift toward a new class of socially responsible workforce planning models in which the objectives of both employees and employers are optimized
SYSTEMS ENGINEERING TALENT MANAGEMENT AT NAVAL INFORMATION WARFARE CENTER (NIWC) ATLANTIC
This thesis analyzes challenges that Naval Information Warfare Center Atlantic (NIWC Atlantic) systems engineers face when they are assigned to Outside Continental United States (OCONUS) tours. These systems engineers are in overseas locations via Permanent Change of Station (PCS) travel orders for durations of time ranging from three to five years. This employee rotation creates professional systems engineering challenges that are accelerated from other existing management challenges found CONUS, such as resource planning and employee development. Utilizing an empirical approach, this study researches, defines and develops methods to mitigate these challenges using Competency Development Model (CDM) based assessments within talent management methodologies. In order to support opportunities for these systems engineers while on their OCONUS tour, a strategy is developed to continue their career progression, while continually meeting the needs of the command’s customers while accommodating personnel rotations. This analysis utilizes the NIWC Atlantic Overseas Engineering Competency structure as the basis for a case study. Through development of a Talent Management System prototype, the study identifies expected benefits that include a more efficient and effective tool to manage and plan OCONUS personnel rotations along with formalized strategies for mentorship and professional career growth of systems engineers.Civilian, Department of the NavyApproved for public release. Distribution is unlimited
TWO MULTI-OBJECTIVE STOCHASTIC MODELS FOR PROJECT TEAM FORMATION UNDER UNCERTAINTY IN TIME REQUIREMENTS
Team formation is one of the key stages in project management. The cost associated with the individuals who form a team and the quality of the tasks completed by the team are two of the main concerns in team formation problems. In this study, two mathematical models to optimize simultaneously cost and quality in a team formation problem are developed. Because team formation problem arises in uncertain environment, different scenarios are defined for the time requirement of the project. Two-stage stochastic programming and multi-stage stochastic programming are applied to solve the first and the second model respectively. The presented models and their solution methodology can be applied in different types of projects. In this study, a project that involves an overhaul of an aircraft is presented as a case study in which the goals are to minimize staffing costs and maximize the reliability of the aircraft by staffing workforce with high competency
Project manager-to-project allocations in practice: an empirical study of the decision-making practices of a multi-project based organization
Empirical studies that examine how managers make project manager-to-project (PM2P) allocation decisions in multi-project settings are currently limited. Such decisions are crucial to organizational success. An empirical study of the PM2P practice, conducted in the context of Botswana, revealed ineffective processes in terms of optimality in decision-making. A conceptual model to guide effective PM2P practices was developed. The focus of this study is on deploying the model as a lens to study the PM2P practices of a large organization, with a view to identify and illustrate strengths and weaknesses. A case study was undertaken in the mining industry, where core activities in terms of projects are underground mineral explorations at identified geographical regions. A semi-structured interview protocol was used to collect data from 15 informants, using an enumeration. Integrated analysis of both data types (using univariate descriptive analysis for the quantitative data, content and thematic analysis for the qualitative data) revealed strengths in PM2P practices, demonstrated by informants’ recognition of some important criteria to be considered. The key weaknesses were exemplified by a lack of effective management tools and techniques to match project managers to projects. The findings provide a novel perspective through which improvements in working practices can be made
Toward Understanding Enterprise Architecture Management’s Role in Strategic Change: Antecedents, Processes, Outcomes
As organizations face accelerated economic dynamics, it isincreasingly important to improve the capability of reacting agileto changes in the marketplace. This requires implementing andadapting internal structures in a timely manner and ensuringbusiness-IT coordination throughout the process. Enterprisearchitecture management (EAM) is frequently proposed as a meanto arrive at organizational forms that allow for timelyreconfiguration and to guide strategy-aligned change. Thisexplorative study seeks to contribute to an overall understandingof EAM’s application in strategic change processes. It is based onan in-depth content analysis of existing research in the field.Specifically, it identifies common EAM practices that have beensuggested for application throughout the planning andimplementation of strategic change. Furthermore, it revealsantecedents and outcomes of this application. The articlediscusses these findings in detail and summarizes the results in apreliminary process model of applying EAM for agile strategicchange
Improving New Nurse Manager Orientation and Onboarding Program
ABSTRACT
Purpose: Identify and adapt the best evidence for nurse manager orientation and onboarding programs into practice. Assess the program\u27s impact on job satisfaction and retention of new Nurse Managers (NMs) and Assistant Nurse Managers (ANMs).
Background: Constant turnover of ANMs and NMs within local and regional facilities is expensive and negatively impacts nursing leaders\u27 work environment, job satisfaction, and patient outcomes.
Local Problem: The lack of formal orientation and onboarding at the focus facility impacts the retention and job satisfaction of NMs. The sunsetting of a regional hub model of new NM orientation and onboarding led to a just-in-time model that was not developing NM competence or promoting job satisfaction and contributed to extensive ANM/NM turnover.
Methods: CINHAL and PubMed were reviewed and identified seventeen studies discussing nurse manager orientation onboarding, job satisfaction, and retention; single research, systematic reviews, and a meta-analysis were included and limited to 2008-2023 publications and English-only articles, inclusive of reverse reference reviews.
Interventions: Six key themes were identified from these studies: (a) the use of multi-modal interventions to impart knowledge, (b) organizational factors impacting NM effectiveness, (c) mentoring and coaching, (d) individual traits and characteristics, and (e) job satisfaction and retention, and (f) the impacts to organizations and patients.
Results: Pre- and post-interventional surveys using Qualtrics software were analyzed and evaluated for trends to demonstrate the impact of a structured, evidence-based orientation
program on NM job satisfaction and retention. Outputs generated quantitative statistical outcomes using SPSS software: a paired t-test from pre-and post-data sets.
Conclusions: In the targeted hospital, a quality intervention focused on improving new nurse manager orientation and onboarding demonstrated improvements in NM perceived competency and reductions in travelers on assignment
A modified greedy algorithm for the task assignment problem.
Assigning workers to tasks in an efficient and cost effective manner is a problem that nearly every company faces. This task assignment problem can be very time consuming to solve optimally. This difficulty increases as problem size increases. Most companies are large enough that it isn\u27t feasible to find an optimal assignment; therefore a good heuristic method is needed. This project involved creating a new heuristic to solve this problem by combining the Greedy Algorithm with the Meta-RaPS method. The Greedy Algorithm is a near-sighted assignment procedure that chooses the best assignment at each step until a full solution is found. Although the Greedy Algorithm finds a good solution for small to medium sized problems, introducing randomness using the meta-heuristic Meta-RaPS results in a better solution. The new heuristic runs 5000 iterations and reports the best solution. The final Excel® VBA program solves a small sized problem in less than one minute, and is within 10% of the optimal solution, making it a good alternative to time consuming manual assignments. Although larger, more realistic problems will take longer to solve, good solutions will be available in a fraction of the time compared to solving them optimally
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