Data Management Strategy and Governance

The Entity shall self-assess the current capabilities across all data management domains, and technology landscape. The entity shall, at a minimum:

• Assess the maturity across all Data management domains to provide maturity rating and areas of improvements of each data management capability
• Document list of all existing technologies and tools within the Entity used for data management including data storage, processing, integration, analytics, and security
• Document list of existing data platforms within the Entity such as data warehouse and data lake
• Document list of key operational and analytical dashboards and reports
• Develop Data management current state maturity report to identify data management domains gaps and prioritize domains that require uplifting
• Create a benchmark study for analytics use cases and when needed other specific and emerging technologies with best practices already delivered at similar entities in other countries

• The Entity shall automate the Data management maturity assessment framework using accelerators or tools to facilitate periodic self-assessment in the future, to save time and cost

The Entity shall assess the source systems and readiness of data needed to deliver the business requirements and prioritized use cases. The Entity shall, at a minimum:

• Document necessary datasets and critical data elements and their readiness criteria that must be met to consider data fit for use
• Develop the source system analysis template and prepare source system analysis report after performing the analysis. The template shall cover the following
  • Schemas
  • Key entities/objects
  • Key attributes per entity
  • Data Owner & Data Stewards
  • Data Domain
  • Reference & master objects/entities
  • Data volumes
  • Attributes count
  • Records count
  • Environments
  • Basic data quality checks
• Generate data profiling report that includes quality insights about critical data elements to indicate data readiness

The Entity shall design the high-level target data & platform architecture including enterprise analytical data model aligned to the data architecture and modeling standards and supporting the prioritized use cases. The Entity shall at a minimum, develop the following:

• High-level target data & platform architecture design document (Referring to the standards in the Domain)
• Enterprise Analytical Data Model Design Document

In alignment with the defined strategic objectives, the Entity shall consolidate the documented operational and analytics business requirements into a comprehensive list of initiatives. These initiatives shall then be prioritized for implementation to ensure the successful achievement of the strategic objectives. To develop the data strategy roadmap, the Entity shall at a minimum:

• Develop a prioritization framework to prioritize the identified initiatives based on business impacts and ease of implementation and identify the immediate priority, mid-term, and long-term initiatives
• Develop initiative charters for the identified initiatives including at a minimum:
  • Overview
  • Owner
  • Stakeholders
  • Budget
  • Key Activities
  • Indicative Timeline
  • Expected outcomes
• Develop a data strategy roadmap by listing all the initiatives and develop a consolidated timeline for all initiatives and key activities, considering their priority and dependencies
• Develop the overall data strategy budgetary estimates for the initiatives collectively, and develop detailed budgetary estimate per each initiative and related milestone

The Entity shall design the data operating model needed to activate and drive the data strategy including, at a minimum:

• Data committee charter and required working groups charters (including the mandate, members, key activities, key outcomes, meeting frequency) based on the data management requirements
• Target org. structure design in alignment with National organizational structure guidelines
• Design interim-state and target-state data capacity plan for data roles and responsibilities in alignment with the national data operating model based on the entity’s requirements and size
• Manpower sourcing framework and criteria in alignment with national guidelines and templates to identify the jobs / roles that could be outsourced for the Entity
• Processes needed to manage the interaction between various departments inside the Entity and other external partners or entities

The Entity shall publish the data governance policy following the below guidelines:

• Review the draft policy with the Entity’s Data Committee or equivalent body
• Incorporate Data Committee or equivalent body’s feedback
• Review draft policy for auditability
• Incorporate internal audit feedback
• Seek policy review and guidance from the National Data Governance Office, and incorporate the received feedback
• Publish the policy on Entity’s digital channels such as entity’s website
• Socialize the policy within the Entity to drive adoption and change management

The Entity shall activate the data committee and working groups defined in the data operating model by accomplishing at a minimum:

• Determine the individuals who will play the determined roles identified in the data committee and working groups charters
• Conduct a kickoff meeting led by the chairperson of each working group and data committee
• Schedule data committee and working groups meetings as per meeting frequency outlined in the charters

The Entity shall establish key performance indicators (KPIs) to measure and report on the Entity's data strategy. KPIs shall include, at a minimum:

• Strategic key performance indicators (KPIs) to enable executive stakeholders to measure and monitor the impact of the data strategy
• Operational key performance indicators (KPIs) to monitor and report the performance of data strategy operational activities

The Entity shall monitor and report on the data strategy at a predefined frequency and based on the defined KPIs. This shall include, at a minimum:

• Dashboards to track, analyze, and display data in an aggregated format to gain deeper insight on the overall performance and trends across the operational data strategy KPIs
• Reports detailing, at a minimum:
  • Executive summaries highlighting key achievements and challenges across the data strategy
  • Detailed analysis of strategic and operational KPIs and performance metrics
  • Progress against the data strategy roadmap
  • Financial analysis including budget adherence
  • Identified risks and mitigations