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Data Science and AI

Fueling Data-Driven Transformation With Aboitiz Data Working Group

By Mark Lagatao and Aly Virrey

Organizers and attendees of the Data Working Group (DWG) gather to learn and share best practices, furthering Aboitiz’s Great Transformation vision by uniting the Group's technology teams to elevate data strategy and implementation across the organization.

Since its successful relaunch last February, the Aboitiz Data Working Group (DWG) has played a crucial role in shaping our Great Transformation, primarily, as it spearheads how we leverage data and AI in operations and strategies. Led by the GT Technology Pillar, the DWG remains steadfast in its mission to elevate the collective data maturity of the Group by enhancing data strategy and implementation capabilities, fostering collaboration, and nurturing a culture of perpetual learning across the organization.

What’s New?

The DWG is building on the momentum it started, as it continues to provide access to top data experts, unite the Group's technology teams, and empower them to fully harness the power of data.

Focused on data enablement and building a community of experts, the DWG committee has conducted six sessions to promote new knowledge, concepts, and practices on data capabilities. Two of these were Special Sessions open to all Team Members of the Group, including those outside of Data or Information Technology teams, to provide hands-on training in core data skills such as preparation, analysis, visualization, and storytelling. Meanwhile, the regular DWG sessions update and train leaders and data practitioners within each business unit to formulate and execute data strategies that align with their business goals. The sessions are meticulously designed to cover crucial aspects of data such as data governance, management, analytics, architecture, and infrastructure. By facilitating interactive discussions on data challenges and successes, incorporating engaging demonstrations and providing hands-on exercises, the DWG fosters a comprehensive and immersive learning experience, empowering participants to grasp complex concepts and apply them practically.

Featuring both external and internal industry experts, data leaders, and practitioners, these sessions provide valuable insights and practical knowledge for all. Data practitioners from AEV, AboitizPower, UnionBank, Aboitiz Foods, and Aboitiz Data Innovation have collaborated with DWG to share their expertise across a range of data topics.

Session Topics and Objectives Key Lessons Learned
Feb 1 Relaunch and Kick-Off
In collaboration with AEV Data Privacy Office
Building the data value stream to manage and use data effectively is the foundation of a successful data strategy, as it enables the organization to achieve its business goals. This system must be supported by a clear plan for data protection and security to ensure that data is used ethically and lawfully.
Data Strategy and Governance
Trends for Modern Data Strategy Best Practices
Data Privacy
Data Threats and Security
A clear data strategy enables an organization to generate more business value.
Business goals can be achieved through lawful and ethical use of data.
Organizations must protect data by following cyber and information security best practices and standards, and being aware of new and emerging threats.
Mar 21 Establishing Data Governance Foundations and Data Management Practices
In collaboration with Aboitiz Data Innovation
Effective metadata management ensures that data is properly cataloged, defined, and understood, which is essential for maximizing the value of data and enabling data-driven decision-making.
Data Catalog,
Data Dictionary,
Business Glossary,
Getting Value from Data (End-to-End Ingestion, Data Prep to Dashboard demo)
Access to data and information about the data is crucial to extract business value.
A central data repository allows easier access to data, and enables business users to make data-driven decisions.
Apr 15 Powering Up Data Strategy for Business Impact
In collaboration with Aboitiz Power Data Services Team
Data integration patterns are essential for accelerating the accessibility and availability of data, which in turn drives business value generation. By streamlining the process of combining data from various sources, these patterns empower organizations to unlock the full potential of their data assets and make well-informed decisions.
Extract-Load-Transform (ELT) vs Extract-Transform-Load (ETL),
Data Quality,
Insights from Data
Business users must be able to trust data provided.
Data practices must incorporate data quality reporting to increase trust on data.
Development and use of frameworks can speed up data processing tasks, such as for ingestion.
May 17
DWG Special (aimed at all A-People to build Core Capabilities)
Building Data Analytics Capability
In collaboration with UnionBank AI and Innovation Center of Excellence
Data analytics is crucial for understanding and effectively communicating business performance to drive informed decision-making.
Data Storytelling
Data Visualization
Effective data storytelling requires appropriate visualization and flow.
Selecting the right visual is crucial for data analysis. Using appropriate visualization enhances the intuitiveness and comprehension of the analysis.
Specific tools are needed for more advanced analysis and to access other visualization techniques, such as violin plots, word clouds, and treemaps.
June 20 Ensuring Data Quality, Integration, and Fostering Trust on the Data
In collaboration with Aboitiz Foods
Data-driven decisions are the cornerstone of successful modern businesses, but these decisions are only as sound as the data they're built upon. Ensuring data quality is paramount as it directly impacts the reliability and accuracy of insights.
Data Quality Metrics (accuracy, completeness, consistency, uniqueness, validity, and integrity)
Data Quality Management
Master Data Management
Data Quality KPIs must be monitored and communicated to immediately implement corrective actions when data issues are detected.
Data definitions, validation rules, and protection mechanisms are essential for ensuring data quality throughout the organization.
Data quality management should be integrated into the data lifecycle from generation and collection to processing.
Master Data Management aims to establish a single source of truth by consolidating and reconciling data from various systems.
July 19
DWG Special (aimed at all A-People to build Core Capabilities)
Data Literacy for Everyone
In collaboration with AEV
Enable A-People across the Group to build and use foundational data and analytics skills to understand business performance, generate insights, and for decision-making; contributing to the Techglomerate core capabilities in digital and data.
Data Collection
Data Preparation
Visualization
Business definitions and data types guide preparation or cleansing, data quality profiling and validation during collection.
Using Google Sheets and Excel formulas and tools to clean, prepare, and analyze data.
Business Intelligence and Dashboarding tools used in the Group to get insights, such as Looker, PowerBI and Tableau.

To support the DWG monthly sessions, a dedicated Google Chat Space for DWG members was also created to facilitate quick exchange of ideas and resources such as links to articles discussing data, data quality, and other data related topics on data strategy, governance, management and analytics.

A+10 Behaviors in Action

At the DWG, members didn’t just talk shop—they dove into the real challenges and lessons they’ve faced in crafting and rolling out their data strategies and initiatives. From overcoming hurdles to unleashing the power of analytics in both strategy and day-to-day operations, they had plenty to share. Here are some of the standout insights from the DWG members and how they’ve demonstrated the A+10 behaviors along the way:

Open & Entrepreneurial: Jobelle Ariola from Aboitiz Land’s IT Team shared that, despite being in the early stages of their data journey, they have already realized significant business value. With strong support from management, the Data Insights and Analytics team, led by Richmond Dy, has demonstrated how leveraging data can drive business decisions that boost revenue. Previously, their focus was on enhancing operational systems, but they have now committed to establishing a dedicated team to advance data initiatives. These initiatives include improving data governance, exploring data warehouse and data lake solutions, and facilitating data sharing across other business units.

Purpose-driven & Synergetic: Jecca Cruz from Aboitiz Power’s IT Team emphasized that gaining key stakeholder support, effectively strategizing, and prioritizing data initiatives are crucial for success. Management and functional teams must be actively involved, as they are the primary users of the data and analytics. It's essential to strategize and prioritize by focusing on what matters most—such as selecting the right data sets to ingest, implementing appropriate data management practices, and targeting the most impactful areas of the business. Viewing the data journey holistically is vital to sustaining these solutions over time.

Smarter & Entrepreneurial: Illan Aboitiz from AEV’s Synergy Office and Aboitiz Land shared how they leveraged a geographical map of Aboitiz Group assets to identify potential synergies. The process involved several challenges, including data gathering from diverse sources, inconsistencies in asset information standards, and the preparation of data. However, through collaboration with the Transformative Technology Team, the data was standardized and prepared for visualization. The resulting dashboard effectively highlighted strategic opportunities for synergy by showcasing assets along with their respective inputs, outputs, and performance metrics.

Delivering More Value for Stakeholders

The DWG also introduced a Data Maturity Model and Assessment, along with a Data Capability Baselining, with the goal of achieving a baseline and gaining visibility into the current state of data capabilities and data journey maturity across the Aboitiz Group. This initiative is crucial for identifying alignment challenges, as well as highlighting opportunities and synergies that can advance our overall data maturity.

The Data Maturity Model offers valuable insights into the strengths of each business unit while also revealing potential challenges and opportunities for synergistic growth. This model not only helps to advance the Group’s data maturity but also provides tailored recommendations covering key areas such as Organization, Resources, Architecture, Data Life Cycle, and Governance. These insights allow data strategists to customize their approaches to align with their business objectives.

Meanwhile, the Data Capability Baselining serves as a mechanism for identifying subject matter experts within the organization, which facilitates knowledge sharing and the dissemination of best practices. It also acts as a roadmap for where to invest in capability building, ultimately increasing our delivery capabilities. By assessing current proficiencies in areas like Data Governance, Data Management, Data Integration, Data Analytics, Data Infrastructure, and Data Ops, we can pinpoint areas for improvement and capitalize on our strengths.

The Data Maturity Model and Assessment were shared with business units’ IT, data, and business leaders, with each respondent receiving their assessment results immediately via email. These results provide a comprehensive view of where each unit stands, helping leaders understand their current positioning and what steps are needed to elevate their data maturity.

Sample recommendations on elevating the maturity in Data Life Cycle and Governance Dimensions of the Data Maturity Model
Sample summary visualization of Capability Baselining for two employees. This is only a small part of a report with more detailed discussion on the baseline data capabilities of the business unit following an evaluation of 6 dimensions consisting of 27 capabilities. Similarly, the Data Maturity Assessment of each business unit covered 85 areas across the 5 key dimensions of Data Journey Maturity.

The DWG has also fostered discussions on how to formulate and execute data strategies, creating a platform for business executives, IT and Data Leaders, and data practitioners to interact and share their experiences. While challenges are inevitable, the exchange of learnings, experiences, knowledge, and insights among the many experts within the Aboitiz Group is paving the way for a more mature and synergistic approach to data.

Moving Forward

The DWG Team has successfully organized six capability building sessions since January, discussing new and existing technologies to help bring more value to the Group. AEV VP for Transformation and Head of the GT 2025 Technology Pillar Wolfgang Merkt gave the closing remarks during the activity in May held at NAC Tower.

The DWG has announced upcoming sessions covering various topics, including data quality, data platforms, cloud analytics, and big data. These sessions aim to provide insights and best practices for data management and utilization. Business Units are encouraged to send representatives to participate actively in the discussions and ensure the outcomes are relevant and actionable.

The Aboitiz Group continues to transform to become the first Techglomerate in the Philippines that leverages data for operations and strategies. The GT Technology Pillar invites the community of IT and data experts, and business leaders in the Group to continue working and sharing their expertise to elevate each other's data maturity to continue advancing business and communities.

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