联合国西亚经济社会委员会-西亚经社会数据战略（英）-2021.8-42页_4mb

ESCWA Data Strategy Summary

Core Content

The ESCWA Data Strategy is inspired by the United Nations Secretary-General's 2020-2022 Data Strategy, aiming to enhance the use of data and statistics to support policy analysis, advice, and advocacy for a sustainable and prosperous Arab region. It outlines a comprehensive approach to data utilization, emphasizing innovation, collaboration, and alignment with global frameworks like the 2030 Agenda for Sustainable Development.

Main Goals

The strategy is designed to achieve the following key objectives:

• Stock-take data sources relevant to ESCWA users.
• Map data resources to current and future needs.
• Deploy advanced data technologies to improve policy advice.
• Synergize data sources with analytical models and platforms.
• Promote data visualization for better decision-making.
• Enhance data-related skills and jobs at ESCWA.
• Introduce sustainable measures to protect data in stock and transit.
• Improve statistical services for member States.
• Ensure data quality and reliability through organization-wide frameworks.
• Become an active node in the broader United Nations data ecosystem.

Key Work Areas

The strategy focuses on four main work areas:

A. Statistical Data

• Covers sectoral statistical development in the Arab region.
• Includes statistics on conflict repercussions, population and housing censuses, social indicators, economic statistics, gender statistics, and environment data.
• Emphasizes interagency and intergovernmental collaboration.
• Aligns with the ESCWA Statistical Committee and Regional Working Group on Data and Statistics.
• Coordinates with UN regional commissions and United Nations Statistics Division.

B. Data Analytics

• Focuses on improving analytical capacity and modeling practices.
• Recommends the creation of a centralized model base for better resource sharing and collaboration.
• Encourages cross-functional team collaboration and access to diverse data sources.
• Promotes the use of statisticians, data scientists, and policy experts in analytics teams.

C. Data Management

• Addresses data discrepancies, errors, and latency in data production.
• Highlights the need for data governance and oversight.
• Encourages data literacy and secure data utilization.
• Seeks to streamline data handling across the organization.

D. Data Platforms

• Seeks to enhance data sharing and accessibility.
• Develops a unified data portal for reliable and consistent data dissemination.
• Ensures alignment with global statistical standards and national data sources.
• Aims to reduce data gaps and discrepancies through reliable sources and estimation techniques.

Strategy Enablers

To implement the strategy effectively, the following enablers are emphasized:

• Technology: Deployment of modern data technologies and platforms.
• People and Culture: Encouraging a data-driven culture and upskilling of staff in data science and analytics.
• Budget Requirements: Allocating resources for training, hiring, and system upgrades.
• Data Governance and Oversight: Establishing clear governance structures and data quality frameworks.
• Partnerships: Collaborating with regional and global organizations, including AITRS, GCC-Stat, and the Data-Pop Alliance.

Implementation Approach

The strategy follows an iterative process, aligning with Agile methodologies and the Acquire, Analyse, Adapt, Advise (AAA) cycle. It is built using a fishbone diagram for gap analysis and outlines a PDCA (Plan, Design, Check, Adjust) cycle for continuous improvement and adaptation.

Scope and Vision

• Vision: ESCWA as a data-driven think tank aligned with the broader United Nations data ecosystem.
• Mission: To produce innovative knowledge, support regional consensus, and provide transformational policy advice aligned with the 2030 Agenda.
• Scope: The strategy aims to streamline data handling, enhance data literacy, and improve statistical reporting for member States.
• Timeframe: Open-ended, with incremental updates and roadmaps guiding implementation.

Key Challenges

• Internal Data Gaps: Lack of modern data technologies, inconsistent data practices, and poor metadata management.
• External Data Issues: Imported data may have bottlenecks and quality issues.
• Interoperability and Similarity: Data from national sources may lack consistency and integration.
• Cybersecurity Concerns: Need for advanced data security measures beyond traditional perimeter protection.

Strategic Framework

• The strategy is not prescriptive or exhaustive, but rather flexible and adaptable.
• It encourages innovative data use cases and customized recommendations for implementation.
• A data strategy action group is proposed to oversee implementation and coordinate with the UN Data Governance Group.

Collaboration and Coordination

• ESCWA collaborates with national statistical offices, regional organizations, and specialized UN agencies.
• Participates in global working groups on statistical methodologies.
• Supports common country assessments, SDG reporting, and technical advisory services.
• Works closely with the CEB System-Wide Roadmap and the UN Data Strategy.

Conclusion

The ESCWA Data Strategy is a comprehensive and forward-looking framework that aims to modernize data systems, enhance analytical capacity, and support evidence-based policymaking in the Arab region. It emphasizes collaboration, innovation, and alignment with global standards to ensure data quality, security, and accessibility for all stakeholders.