1S1745PMO DataViz Project

References

• ROMV(CMS) CORPORATE S.A. (2023). Repositorio de Informacion de proyectos 1S1745 SEATOR - Astillero/Marina. https://seator-boats.ec
• Bostock, M. (2020). D3.js - Data-Driven Documents. https://d3js.org/
• Munzner, T. (2014). Visualization Analysis and Design. CRC Press. https://www.crcpress.com/Visualization-Analysis-and-Design/Munzner/p/book/9781466508910
• Meeks, E. (2020). Observable - Explore, visualize, and analyze data. https://observablehq.com/
• Wilkinson, L. (2005). The Grammar of Graphics (Statistics and Computing). Springer. https://www.springer.com/gp/book/9780387245447

Project 1

Project Activities DataFrame and Indicators, Case Study: Shipyard/Marina.

In shipbuilding activities, efficient project management is crucial to ensure not only profitability, but also long-term sustainability. With the aim of optimising the management of a shipyard's project portfolio, the Company's Project Management Office (PMO) division has carried out a comprehensive analysis of data from almost 250 projects developed over a ten-year period. This report presents the key findings of this analysis, providing a detailed view of project performance in terms of costs, schedules, complexity, risks, and other earned value indicators. The analyzed dataset includes complete information on each of the projects, covering critical aspects such as planned and actual costs, duration of activities, construction complexity factors, earned value performance indices (CPI and SPI), and identified and materialized risks. This information has been collected and systematized to provide a solid foundation that allows the shipyard's shareholders and managers to make informed and strategic decisions. One of the main objectives of this analysis is to assess the accuracy of cost and time estimates, as well as to identify areas where variability is greatest. The projects have been classified into different types: design, consultancy, construction, maintenance and reconstruction. This classification has allowed for a comparative analysis that highlights the differences in performance and management of each type of project. For example, construction projects have been observed to exhibit greater variability in actual versus planned costs, suggesting the need to improve cost estimation and control practices in these projects. In addition, the analysis has delved into the relationship between the complexity of projects and their performance. Using construction complexity factors, we have assessed how complexity affects the duration and costs, as well as the likelihood and impact of the identified risks. The results indicate that projects with higher levels of complexity tend to have more significant deviations in the schedule, underscoring the importance of detailed planning and proactive risk management. The report also addresses risk management and its impact on project performance. A significant correlation has been found between the probability and impact of the identified risks and the performance indices (CPI and SPI). Projects with a higher probability of risk tend to perform worse in terms of costs and schedules, highlighting the need to implement effective risk mitigation strategies. In addition to these analyses, the report presents a comparison of the performance of projects over time. An improvement trend has been observed in projects initiated in recent years, which could be related to the adoption of new technologies and project management practices. This improvement is reflected in key indicators such as the CPI and SPI, which show greater efficiency and effectiveness in the use of resources. This project then provides a comprehensive view of the shipyard's project performance, identifying critical areas that require attention and proposing data-driven recommendations to improve project portfolio management. The preliminary findings presented here will serve as a guide for strategic decision-making, helping the shipyard to optimize its operations and secure its competitive position in the market.