Executive Summary

_{Author: Bianca Cuba Bersan — Advisor: Fernando Celso De Campos}

^{Summary prepared by the ResumeAI tool, an artificial intelligence solution developed by Instituto Pecege focused on synthesis and writing.}

This work develops a management panel (dashboard) to integrate and visualize data from dispersed teams, allowing for efficient control, information analysis, and strategic calculations such as budget planning and pricing. The purpose is to support decision-making in Information Technology (IT) projects for multinational companies, which face challenges in managing personnel in remote and hybrid work models. The need for the tool was accentuated by the COVID-19 pandemic, which accelerated the adoption of new work models and exposed gaps in the control and capacity planning systems for distributed teams.

The transition to remote work, despite its benefits, has complicated IT human resource management. The dispersion of teams has rendered traditional monitoring methods obsolete, requiring solutions with a unified, real-time view of the workforce (Souza et al., 2021). In this scenario, capacity management, position control, and alignment of personnel with strategic goals have become critical challenges. The absence of a centralized data source results in decisions based on fragmented information, generating imbalances such as overstaffing in some areas and overload in others (Mariani et al., 2024).

Data visualization is a strategic response to these challenges, transforming large volumes of information into intuitive graphical representations. Interactive dashboards meet the informational needs of different management levels, from operational to strategic (Rahman et al., 2017). The customization of these tools is crucial to ensure their relevance for each manager (Vazquez-Ingelmo et al., 2019a). By consolidating key performance indicators (KPIs) in a single interface, dashboards allow for continuous performance monitoring, facilitating the identification of trends, anomalies, and opportunities.

The effectiveness of a dashboard depends not only on data accuracy but on communication clarity. Data storytelling techniques, which structure information narratively, are fundamental to guide the user and facilitate understanding of the context (Liem et al., 2020). Business Intelligence (BI) tools like Microsoft Power BI® offer a robust environment for creating interactive reports that integrate multiple data sources and apply advanced visualization principles (Becker and Gould, 2019). The platform was chosen for its integration with the Microsoft ecosystem and its user-friendly interface, which democratizes access to data analysis (Town and Thabtah, 2019).

Therefore, this study details the process of building a BI solution for managing global IT teams. The research covers data collection and processing to the development of visual dashboards to support complex decisions, such as workforce planning, diversity analysis, and vacancy control. The developed solution addresses an operational problem and establishes a foundation for a data-driven organizational culture, where strategic decisions are based on evidence and predictive analytics (Provost and Fawcett, 2013).

The methodology was structured in five sequential steps. The first was the collection of data on positions and collaborators from the IT infrastructure department, consolidating information from different systems. The second step was data treatment to ensure quality and reliability. Three main databases were used: the Cost Driver Planning (CDP) system, which controls the allocation of people by cost center; COMPAS, an HR system that centralizes collaborator information; and Planisware, a tool for budget planning and time recording.

The third stage involved data modeling and analysis to define indicators and manage risks. The data were integrated into a single database in MS-Excel® and modeled in MS-Power BI® to establish relationships between tables. In this phase, risks that could impact data integrity, such as synchronization errors or update failures, were mapped, allowing the creation of control mechanisms. Key indicators were defined in collaboration with managers to ensure the relevance of the metrics.

The fourth stage was the development of the dashboard in MS-Power BI®. From the unified database, visualizations were created to present the information clearly and interactively. The design was conceived for different user profiles, with “cards” displaying high-level KPIs, such as total number of positions, current employees, and open vacancies. Dynamic filters were implemented that allow data disaggregation by department, group, location, and gender, offering flexibility to explore the information from different perspectives.

The fifth stage comprised testing and deployment. Validation sessions with the leaders of each IT group analyzed the functionality, data accuracy, and interface usability. The feedback collected was fundamental for refining filters, adjusting visualizations, and ensuring the tool met user expectations. After the adjustments, the dashboards were published, with a monthly maintenance process established to ensure continuous data updating, consolidating the tool as a strategic asset for people management.

The execution of the methodology resulted in a robust analytical solution. In data collection, files from the CDP, COMPAS, and Planisware systems were centralized. The presence of the unique identifier Person ID in all datasets was crucial for efficient information integration. The consolidated database, with approximately 3,823 records from CDP/COMPAS and 500 records from Planisware, formed the foundation for a holistic view of the personnel.

The data treatment was a critical phase, where problems that compromised information quality were corrected, such as record duplication, blank mandatory fields, naming inconsistencies, and outdated data. Overcoming these obstacles through cleaning and validation routines was essential to ensure the accuracy of the indicators, transforming raw data into a cohesive informational asset.

In the modeling process, a consolidated spreadsheet in MS-Excel® served as an intermediate layer to organize the processed data into logical categories, such as employee information, position details, department data, and work capacity. This structure facilitated the import and relationship of data in MS-Power BI®, as well as optimizing dashboard performance and simplifying the creation of complex calculations.

The development in MS-Power BI® resulted in two main dashboards. The first tracks new positions and their approval stages (PANFs), with filters by location type, department, and group, and KPIs on process status (in approval, closed, on hold). Bar charts detail the status of each vacancy, a pie chart classifies the nature of the hire (replacement, new position), and a funnel chart highlights countries with the highest volume of active positions. The tool transformed a manual process into a transparent and monitorable workflow.

The second dashboard, focused on the overall analysis of employees, supports strategic workforce planning. Aimed at senior management, it presents indicators such as total employees, ongoing hires, and headcount projections for 2025-2027. Charts display the distribution of employees by hierarchical level, the proportion between leadership and non-leadership, and allocation by product and country. A diversity and inclusion section presents gender distribution by product, location, and tribe, allowing for the monitoring of equity goals. The dashboard’s interactivity enables scenario simulation and identification of future needs, aligning human capital management with long-term objectives (Davenport and Harris, 2007).

The testing and deployment phase validated the solution’s effectiveness. The participation of managers allowed for the refinement of the tool, incorporating suggestions that increased its applicability. The importance of visualizing the dynamics of job occupancy, such as tenure and performance evolution, was highlighted, providing crucial information for succession planning, aligned with the competency-based management model (Fleury and Fleury, 2001). The analysis of the employee structure, segmented by growth forecast (Forecast), diversity, geographical distribution (Country Share), and hierarchical structure (SLx Position), demonstrated the tool’s ability to transform data into insights. The implementation marked the transition from a reactive process to a proactive, data-driven model.

The evolution of the management process was remarkable. Previously, management was characterized by manual processes, decentralized and error-prone data, resulting in a fragmented view. With the new tool, the process became automated, with centralized and updated data, providing an integrated and strategic view. The ability to generate analytical reports and projections allowed for more assertive vacancy planning, diversity monitoring, and precise budget management. Positive feedback from managers confirmed the acceptance and value generated. The developed model not only solved the challenges of the IT department but also established a standard that can be replicated in other areas, reinforcing the importance of using BI to support decision-making (Sharda, Delen, and Turban, 2017).

The transformations in the corporate environment have consolidated remote and hybrid work models, demanding new approaches for team management. This study demonstrated that data visualization, through dashboards on platforms like MS-Power BI®, is a strategic resource for monitoring, communication, and decision-making. The application of data storytelling and the personalization of dashboards promote manager engagement and alignment with organizational objectives. The solution developed for IT team management has subsidized more assertive tactical and strategic decisions, addressing challenges of dispersion and coordination.

The work was limited to the context of an Information Technology department, which gives practical relevance to the results for organizations with similar structures. As developments, it is suggested to apply the model in other areas, such as finance and human resources, to validate its effectiveness. Future research may investigate the impact of adopting such tools in promoting a data-driven culture, evaluating how information visualization influences collaboration and agility. It is concluded that the objective was achieved: it was demonstrated that the development of integrated management dashboards enables efficient control of dispersed teams and supports strategic decision-making in multinational companies.

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Executive summary from the Final Project of the Specialization in Data Science and Analytics from the MBA USP/Esalq

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