Fusion Framework

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Description: Establish a governance model that includes representatives from each domain to oversee data integration and ensure collaborative decision-making.

Implementation Steps:

Governance Committee: Form a committee with members from each domain.

Roles and Responsibilities: Define clear roles and responsibilities for data management.

Decision-Making Protocols: Establish protocols for resolving conflicts and making decisions collectively.

To decide who takes control and who makes the final decision:

Role Assignment: Assign a Chief Data Officer (CDO) or a similar role to oversee the entire data integration process.

Delegated Authority: Empower the governance committee to make decisions within their respective domains.

Escalation Path: Define an escalation path for unresolved issues, where the CDO has the final say in critical matters.

By following this framework, you can ensure seamless integration of data across various domains, maintain alignment towards common goals, and establish a clear decision-making process.

Description: Create a centralized data platform that ingests and integrates data from all relevant domains. This platform should support dynamic data correlation and root cause analysis.

Implementation Steps:

Data Ingestion: Use AI and ML tools to collect data from all silos.

Data Integration: Standardize data formats to ensure seamless integration.

Real-Time Analytics: Implement real-time analytics for immediate insights and root cause analysis.

Description: Implement a continuous improvement process to ensure the framework evolves with organizational needs

Implementation Steps:

Feedback Mechanisms: Set up regular feedback sessions with stakeholders.

Performance Metrics: Define and monitor key performance indicators (KPIs) to measure the effectiveness of the integration.

Iterative Improvements: Use feedback and performance data to iteratively improve the system.