Evaluating Federal Information Technology Program Success Based on Earned Value Management

Despite the use of earned value management (EVM) techniques to track development progress, federal information (IT) software programs continue to fail by not meeting identified business requirements. The purpose of this logistic regression study was to examine, using IT software data from federal agencies from 2011 to 2014, whether a relationship between schedule variance (SV), cost variance (CV), and actual cost (AC) could predict the success of IT software program, as operationalized by meeting the identified business requirements. The population of interest was 132 IT software programs developed between 2011 and 2014 for federal agencies. The sample source was an archival database located at ITdashboard.gov. The theoretical framework for the study was earned value (EV) project management theory. The EV project management theory is a project performance measurement system that involves integrating cost, schedule, and performance elements for planning and control. EVM contributes to project success by providing early warnings when programs deviate from cost and schedule plans. This study found that only SV was significant (SV days, p = .002). The null hypothesis was rejected, suggesting that a relationship exists between IT program success and the SV, CV, and AC. This study may contribute to social change by increasing the program managers\u27 understanding of EV in federal project management and by decreasing federal spending through successful programs and more cost-efficient use of taxpayers\u27 money

A Framework for Leveraging Artificial Intelligence in Project Management

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThis dissertation aims to support the project manager in their daily tasks. As we use artificial intelligence (AI) and machine learning (ML) in everyday life, it is necessary to include them in business and change traditional ways of working. For the purpose of this study, it is essential to understand challenges and areas of project management and how artificial intelligence can contribute to them. A theoretical overview, applying the knowledge of project management, will show a holistic view of the current situation in the enterprises. The research is about artificial intelligence applications in project management, the common activities in project management, the biggest challenges, and how AI and ML can support it. Understanding project managers help create a framework that will contribute to optimizing their tasks. After designing and developing the framework for applying artificial intelligence to project management, the project managers were asked to evaluate. This study is essential to increase awareness among the stakeholders and enterprises on how automation of the processes can be improved and how AI and ML can decrease the possibility of risk and cost along with improving the happiness and efficiency of the employees

Optimising project controls for construction using BIM and Big Data Analytics

Construction projects are the main contributors to economies and the wealth of nations. The industry is perceived to lead to developments and prosperity in countries. Projects in the construction industry often have high investment during the construction stage. Advancements in science and development of human needs lead to more complex designs in response to new demands by end-users. Sophisticated designs make projects more difficult to manage and consequently increased the rate of budget and time overruns. A plethora of studies has been conducted to investigate the causes of delays in construction projects. A considerable proportion of these studies have reported poor planning, scheduling, and controls as top contributors to delays. Previous literature exploring project success factors were focused primarily on the cost, time and quality. The rise of technology has led to an exponential increase in the amount of data produced by the industry due to using systems for digital engineering, finance, and scheduling or using new technology that collates data and stores them in a central repository. The increase of data opens the potential for new horizons to use this data for informed decision-making. However, data within the industry is fragmented, inconsistent, and hard to link due to different segmentation and structuring objectives for data creators' objectives. This research aim is to formulate optimised integrated project controls to improve the success of projects. The first objective was to explore the factors affecting the success of projects beyond the traditionally studied cost, time and quality. The association between the efficiency of project controls and the success of projects was the main focus of objective three. The third objective was to investigate the relationship between project controls' efficiency and its three pillars: people, processes, and technology. The research's final objective is to test the impact of new technologies as BIM and big data analytics on the efficiency of project controls. The research methodology followed in this study is a sequential mixed method. In the first phase, literature was reviewed and gaps in knowledge were identified to justify the research. Job advertisements of project controls roles were analysed to determine the skills and knowledge required. These analyses were followed by a quantitative questionnaire that was developed to measure and test the hypothesis. The questionnaire was piloted to 25 participants and feedback incorporated in the final version. The questionnaire was administered online, and 610 participants completed the survey. Responses were analysed using statistical tools to validate the hypotheses of the studies. The results of the analysis were used to inform the design of semi-structured interviews. The research was concluded by conducting four interviews to understand the trends revealed in the survey. The correlation between project controls efficiency and projects' success was a modest positive correlation of value 0.63. The third objective analysis found a high correlation of people, processes, and systems to project controls' efficiency to be 0.864, 0.860, and 0.804, respectively. The analysis and results showed a modest correlation between efficient project controls and project success of value 0.63. The third objective investigated the association of the three pillars of project controls. Results indicate high correlations between people, processes, and systems and efficiency of project controls with values of 0.864, 0.860, and 0.804, respectively. The interviews analysis led to an integrated controls system that uses building information modelling (BIM) to integrate data and store it in a central repository. This data was then used to apply analytics concepts for enhancing decision-making. The system implemented under this study demonstrated a proof of concept on big data analytics and BIM integrations and how it improves accessibility to data in models. This study used the findings to drive theoretical and practical implementation. BIM and data analytics were mentioned as drivers for the efficiency of project controls. A conceptual framework was developed to integrate project controls function with BIM models. The framework was implemented by integrating BIM into business intelligence as part of the data analytics. A classification model for BIM elements was developed with high accuracy. The model results showing a high level of accuracy was implemented as part of this study. The design of semi-structured interview questionnaire. The research was concluded by conducting four interviews to gain in-depth understanding of trends revealed in survey. The analysis and results showed a high level of correlation between efficient project controls and project success. The second objective investigated the importance of the three pillars of project controls, and results indicate importance between people, systems and processes and efficiency of project controls. The interviews analysis led to design of an integrated controls system that uses building information modelling (BIM) to integrate data and store it in a central repository. This data was then used to apply analytics concepts for enhancing decision-making. The system implemented under this study is a proof of concept on how big data analytics and BIM can help improve project delivery

Strategy Management for Guyana’s Public Investment Projects Fulfillment

The public sector investment program (PSIP) hinges on the proper alignment of government strategies with project outcomes. The contingency theory offers insights for alignment in adopting the best project management approach. Yet, some of Guyana’s PSIP managers struggle with alignment for the success of their projects. Using the contingency theory, the purpose of this qualitative multiple case study was to explore strategies PSIP managers used to align project outcomes with government strategies. Data collection was through the reviewed documentation and semistructured interviews with five successful managers who work for four project-based organizations in Demerara/Mahaica, Guyana. Yin’s 5-step process was used to analyze the data. Four themes emerged: government/executive commitment and support for the project teams, efficient project management skills, aligning national strategy with project processes, and managing public project processes with information communication technologies. A key recommendation is for project executives to develop new project management paths for improved project performance fused with a portfolio intended to improve citizens\u27 standard of living. The implications for positive social change include the potential for knowledge sharing among project practitioners and policymakers. Successful project outcomes may result in competitive advantages for those other businesses linked to public investment, enhancing citizens\u27 social well-bein

Extensão da técnica Earned Value Management utilizando dados da qualidade em projetos de software.

Esse trabalho apresenta uma extensão da técnica de Gerenciamento de Valor Agregado (GVA), do inglês, Earned Value Management (EVM). A extensão apresentada integra dados da qualidade, baseados em requisitos de qualidade, para atualizar indicadores tradicionais da técnica de GVA. A proposta tem como objetivo principal melhorar a previsibilidade do Indicador de Desempenho de Custo (IDC) e Indicador de Desempenho de Prazo (IDP) e introduzir medidas de qualidade a técnica de GVA. A técnica proposta foi avaliada de acordo com uma metodologia baseada em evidência. Os estudos conduzidos mostraram melhor exatidão na técnica proposta de extensão da técnica de GVA em relação à técnica tradicional de GVA

Integrated cost management system for delivering construction projects

Cost management forms a major discipline in delivering construction projects of different sizes and complexity. Traditional cost management systems are mostly based on principles enacted several decades ago. A notable feature of these traditional cost management systems is that key information required for critical decisions is usually produced too late, and is often too aggregated and configured in a form that is not amenable to the requirements for current project management practice. Other problems associated with traditional cost systems relate to inadequacies in estimating and cost control processes and particularly the lack of integration of cost management across the whole project. The lack of integration means measurements provided by traditional cost systems do not sufficiently align with the goals and objectives set for the project. To address these inherent weaknesses in the current practice of cost management, a number of studies have argued for an integrated alternative that better responds to the information demand and decision making need to be developed. The thesis presents the development of a solution to such an integrated cost management system. The developed solution addresses the gaps of the traditional option by integrating the stages making up the whole life cycle of the project to enable professionals gain an appreciation of the ramifications of any early decisions made. The investigation conducted to support the development of the integrated cost management system and the applied model addresses user requirements and determination of the system boundary conditions for efficacious use by key decision makers. The new cost management system developed achieves a linkage of the planning and control stages into one, with a continuous stream of cost management information in both stages. The integration ensures that cost information is more relevant to the circumstances of the modern project manager

Rethinking relationships in the construction industry : integrating sustainable development into project management processes

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A Structured Systemic Framework for Software Development

The purpose of this research was to develop and apply a systems-based framework for the analysis of software development project performance. Software development project performance is measured at the project level; that is, cost, schedule, and product quality that affect the overall project. To date, most performance improvement efforts have been focused on individual processes within the overall software development system. Making improvements to sub-elements, processes, or sub-systems without regard for the overall project is a classic misbehavior entered into by practitioners who fail to use a holistic, systemic approach. Attempts to improve sub-system behavior are at odds with The Principle of Sub-optimization. (van Gigch, 1974) The traditional method of predicting software development project performance, in terms of sub-system performance is too restrictive. A new holistic, systemic view based on systems principles offers a more robust way to look at performance. This research addressed this gap in the systems and software body of knowledge by developing a generalizable and transportable framework for software project performance that is based on systems principles. A rigorous mixed-method research methodology, employing both inductive and case study methods, was used to develop and validate the framework. Two research questions were identified as integral to increasing the understanding of a systems-based framework. (1) How does systems theory apply to the analysis of software development project performance? (2) What results from the application of a systems-based analysis framework for analyzing performance on a software development project? Using Discoverers\u27 Induction (Whewell, 1858), a systems-based framework for the analysis of software development project performance was constructed, adding to the systems and software body of knowledge and substantiating a comprehensive and unambiguous theoretical construct for software development. Then, the framework was applied to two completed software development projects to support validation. The structured systemic framework shows significant promise for contribution to software practitioners by indicating future software development project performance. The research also made a contribution in the area of research methodologies by resurrecting William Whewell\u27s Discoverers\u27 Induction (1858) and furthering the use of the case study method in the engineering management and systems engineering domain, areas where their application has been very limited