scholarly journals As boas práticas do PMBOK® e as contribuições para o repensar do ensino da saúde

2015 ◽  
Vol 6 (2) ◽  
pp. 1968
Author(s):  
Cássio Murilo Alves Costa ◽  
Maria Auristela Menezes Costa ◽  
Carissa Menezes Costa ◽  
Linconl Agudo Oliveira Benito ◽  
Jônatas De França Barros ◽  
...  

As tecnologias da informação e comunicação (TICs) estão em crescimento exponencial nos tempos atuais, e a cada dia surgem novos artefatos tecnológicos oriundos da maior descoberta da humanidade, a internet. Nessa perspectiva novas ferramentas são acrescentadas ao cotidiano das pessoas, como tecnologias móveis, tecnologias de vestir, big data, dentre outras, e nesse cenário cabe avaliar os custos em não usufruir desse potencial disponível a todos. Diante desses avanços, a educação em saúde não usufrui das tecnologias em sua plenitude, como também, carece de efetividade em sua oferta. O objetivo desse artigo é apresentar as boas práticas da Gestão de Projetos, como contribuição para repensar o planejamento e a oferta do ensino na área de saúde mediado pelas TICs. O método utilizado foi um estudo exploratório, com abordagem qualitativa em uma narrativa descritiva, que se guiou na análise do referencial teórico sobre o tema. O resultado evidenciou a necessidade de aprofundar estudos nas áreas de conhecimento do gerenciamento de projetos, promovendo uma investigação futura para detalhar criteriosamente cada um dos quarenta e sete processos constante das boas práticas do Guia PMBOK® (5ª edição), preconizado pelo Project Management Institute (PMI), visando adaptá-los ao planejamento e oferta de uma educação tecnológica em saúde.Descritores: projetos, ensino, saúde. 

2022 ◽  
pp. 1786-1800
Author(s):  
A. Aylin Tokuç ◽  
Zeynep Eda Uran ◽  
Ahmet Tezcan Tekin

Big data is an emerging area of research that is of interest to various fields; however, studies in the literature and various sources claim that failure rates for big data projects are considerably high. There are different reasons for failure; varying from management processes to the use of wrong technologies. This study investigates how the project management framework proposed by Project Management Institute (PMI) can be effectively adapted to big data projects to reduce failure rates. The application of processes as mentioned in this study can help to eliminate the causes of failure in the early stages of the project; thus, increasing the successful completion rate of such projects.


Author(s):  
A. Aylin Tokuç ◽  
Zeynep Eda Uran ◽  
Ahmet Tezcan Tekin

Big data is an emerging area of research that is of interest to various fields; however, studies in the literature and various sources claim that failure rates for big data projects are considerably high. There are different reasons for failure; varying from management processes to the use of wrong technologies. This study investigates how the project management framework proposed by Project Management Institute (PMI) can be effectively adapted to big data projects to reduce failure rates. The application of processes as mentioned in this study can help to eliminate the causes of failure in the early stages of the project; thus, increasing the successful completion rate of such projects.


2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Yao Huang ◽  
Qian Shi ◽  
Jian Zuo ◽  
Feniosky Pena-Mora ◽  
Jindao Chen

The construction industry is facing a data tsunami, while emerging information technologies (IT) show great potential for the effective processing of these data or information. However, a comprehensive review for technological change, the resulting process, and organizational changes in the Big Data context, especially from the angle of whole lifecycle of construction project, is lacking. To fill the void, related works published in the databases of Web of Science, Science Direct, and American Society of Civil Engineers library are systematically reviewed. The general trend in emerging IT application in terms of construction project management (CPM) phases, technology and application, and research topics are revealed. Following this analysis, the particularized proposals in relation to each of the main topics within CPM is discussed. Furthermore, according to the advances and limitations of the current literature, corresponding future agendas such as the implementation of comprehensive data-driven CPM scenario are proposed to bridge the gaps between theoretical research and practical demands.


2013 ◽  
pp. 1253-1278
Author(s):  
Martin L. Bariff

Many project deliverables extend beyond a product or a service for sale to customers. The deliverable may include a new or a revised process for internal workflow or relations with customers, suppliers, or partners. The success of these projects will depend upon adoption of the new or revised process in addition to typical metrics for cost, schedule, risk, and quality. The project manager and team will be responsible for “managing organizational change”—a skillset that is not addressed within the Project Management Institute Body of Knowledge. The purpose of this chapter is to provide sufficient knowledge about approaches and implementation for organizational change to achieve total project success. Case studies are included to illustrate best practices and lessons learned.


Author(s):  
George Leal Jamil ◽  
Luiz Fernando Magalhães Carvalho

Knowledge generation for Project Management (PM) is a critical modern issue. Projects are a complex, inter-related set of tasks that aim to provide a service or product in a controlled, managed way. In these scenarios, there is a continuous producing of data and information, which is a potential situation for Knowledge Management (KM) interaction. This chapter evaluates aspects and factors on how it is possible to process data and information, in order to generate applicable knowledge to improve project management. A specific consideration is to understand the observation of contexts of huge amounts of data—known nowadays as Big Data—and its potential knowledge generation for project management, as presented in the final study case. A better comprehension on how knowledge management practices, applied to Big Data contexts, can improve project management processes is the main objective in this chapter.


Author(s):  
Vicky Triantafillidis

Project management skills and professional certification are quickly developing into required core practice (Hammond et al., 2006). Peter Shears, CEO of the Australian Institute of Project Management (AIPM), stated at a April, 2006, conference, that there was increased demand for skilled project managers within all organizations across all industry sectors (Hammond et al., 2006). AIPM is an Australian Project Management Web portal offering certifications of AIPM’s Registered Project Management (RegPM). As a supporter of the project management profession, the Project Management Institute (PMI) also plays an enormous role. The PMI Web portal encourages a standard with the Project Management Body of Knowledge (PMBOK) Guide describing what should be done to manage a project. PMI’s Project Management Professional (PMP®) credential program is also available from the PMI Web portal recognizing and approving skills (Project Management Institute, Inc., 2006).


Author(s):  
Daniel M. Brandon

The Project Management Institute (PMI) project management process groups include initiation, planning, execution, control, and closing. In practice, however, the initiation processes of a project are often not part of a project for budgeting and control issues, but rather are charged to management and administration (M&A) or operations and maintenance (O&M) general ledger accounts. In some organizations, these charges are later reversed back to a project after it is decided to move forward with that project. Thus, only the planning, execution, and control processes become part of the project for accounting purposes; sometimes detail planning is part of a project but not overall planning. Similarly, the closing process group may or may not be a formal part of the project, and sometimes those processes are performed by an independent organization. This chapter is concerned with detail project planning, particularly the schedule and cost plan.


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