Data Supply Chain Governance via Enforceable Contracts
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Solution Overview
Problem
Current data governance methods are fragmented, incomplete, and fail to address the concerns of data consumers and suppliers regarding data quality, accountability, and regulatory compliance, especially in a complex, rapidly evolving data landscape.
Innovation Solution
A data supply chain governance environment is established using contracts that define data objects, services, specifications, and metrics, with a governing authority to adjudicate disputes and incentivize compliance, ensuring accountability and quality across the data supply chain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fragmented or partial data governance solutions are implemented individually by consumers or suppliers, then some specific concerns may be addressed, but comprehensive data quality, accountability, and compliance cannot be achieved across the entire data supply chain
Solution Approach 1:
The patent segments data governance into discrete, standardized contracts that can be independently implemented between specific supplier-consumer pairs. Each contract addresses particular data quality and compliance requirements, allowing organizations to start with focused governance initiatives rather than attempting comprehensive governance all at once. This modular approach builds reliability incrementally while managing complexity through standardized, reusable contract templates.
Solution Approach 2:
The patent creates universal contract templates and standardized governance frameworks that can be applied across multiple supplier-consumer relationships and different data types. These standardized contracts serve multiple functions: defining data quality requirements, establishing accountability mechanisms, ensuring regulatory compliance, and providing dispute resolution processes. This universality allows the same governance structure to scale across the entire data supply chain without proportionally increasing complexity.
2Reliability
If comprehensive data governance is implemented across the entire data supply chain, then all concerns regarding data quality, accountability, and compliance can be addressed, but implementation complexity and resource requirements increase significantly
Solution Approach 1:
The patent provides pre-defined contract templates, standardized governance frameworks, and established best practices that organizations can deploy immediately without having to design governance mechanisms from scratch. These preliminary artifacts include standardized data quality metrics, compliance checklists, and dispute resolution procedures that reduce implementation effort while ensuring comprehensive coverage of data quality, accountability, and compliance requirements across the supply chain.
Solution Approach 2:
The patent incorporates continuous monitoring and feedback mechanisms within the contract framework, including data quality metric tracking, compliance reporting requirements, and performance measurement standards. This feedback enables organizations to identify implementation gaps and address issues proactively, making comprehensive governance more manageable by providing visibility into the state of data quality and compliance across the entire supply chain.
3Manufacturing precision
If detailed specifications and metrics are defined for data services, then data quality and compliance can be ensured, but the time and resources required to define and enforce these specifications increase
Solution Approach 1:
The patent provides standardized data quality metrics, compliance thresholds, and performance parameters that can be directly applied to data services without requiring extensive customization. These pre-established parameters cover common data quality dimensions such as accuracy, completeness, timeliness, and consistency, allowing organizations to quickly define specifications for new data services while maintaining high precision in quality requirements.
Solution Approach 2:
The patent enables organizations to replicate proven governance specifications and contract terms across multiple data services and supplier relationships. By copying and adapting standardized contract templates and performance metrics from established governance implementations, organizations can rapidly deploy detailed specifications for new data services without reinventing the governance framework, significantly reducing the time and resources required while maintaining specification precision.
Data Source
AI summary
The present disclosure is directed to the application of data governance within the domain of a data supply chain, under the jurisdiction of a governing authority. Governance is specified and administered through the mechanism of a data contract, which binds a data supplier to perform a data service on a data object per a specification for a data consumer. Contractual incentives enforce compliance. The data supply chain is the collection of all data contracts operating within the domain identified by the governing authority. The governing authority may monitor the health of the data supply chain, and take actions to improve the health of the data supply chain.