Regulatory Framework around Data Governance and External Benchmarking

Abstract

Regulatory compliance is a set of formal requirements, and lack of clarity on regulations can lead to significant legal and ethical consequences pertaining to collection, storage, or sharing of data among organizations. It can create ambiguity, or regulatory gaps around external benchmark frameworks employed to measure and compare performance among participating organizations. The purpose of this study is to review current US laws and regulations and governing case law concerning data governance, and to aid examination of the framework of federal antitrust and Safe Harbor rules around benchmarking and data warehousing. This study explores gaps between academic research and formal requirements for data governance and benchmarking in the federal space. A systematic review of the literature, federal laws, agency regulations, and relevant case law was conducted to further organize the relevance of the literature in the academic, federal, and legal domains. A quantitative approach was adopted wherein academic scores of relevance (SoR), a legislative score of relevance (LoR), and an overall ranked score of relevance (RoR) were calculated. Guidance on business implications around data governance frameworks is provided to academic and industry professionals engaged in data sharing and analytics.