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Introduction

“Grey data” -- data related to health and well-being but not protected by healthcare legislation -- creates complex data privacy concerns because it is frequently handled by the enterprise yet no concrete guidelines exist for its management.

Highlights

  • Protecting privacy and increasing individual control over grey data collection can actually increase the quality and value of data.
  • Regional data privacy regulations can provide a useful template for grey data management policies, particularly when the strictest regulations are chosen as models.
  • The presence of consent and a process for obtaining consent are critical to ethical collection and use of grey data within the enterprise.

Features and Benefits

  • Identifies common sources of grey data within the enterprise and highlights best practices for management.
  • Assesses the impact of current data collection and consent practices on the long-term relationships with customers.
  • Evaluates regional regulation for PII (personally identifiable information) and assesses how these standards can be applied to grey data management.
  • Identifies current practices and methodologies in data collection that harm the user experience and hamper consumer trust.
  • Compares "quantity versus quality" approaches to grey data collection, as well as their implications for privacy.

Key questions answered

  • What is grey data, and what are the potential sources of grey data within the enterprise?
  • How do regional regulations for PII provide a useful model for building best practices for grey data management?
  • How can increasing privacy and consumer control over data build trust and increase overall data quality?
  • Why are current consent methodologies not sufficient for grey data collection in the IoT era?
  • What actions can the enterprise take to protect against potential future regulation of grey data?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

Grey data is increasingly common, and is woven between work and personal life

  • Grey data is data related to health and well-being, but not protected by traditional healthcare privacy protections
  • Because of its sensitive nature, grey data is particularly susceptible to security breaches and misuse
  • The enterprise has varying degrees of control over different grey data sources

Regional data privacy regulations can provide a useful template for global grey data policies

  • The strictest regional standards for PII set a good example for management, and protect against future regulation
  • The enterprise needs to ensure that existing requirements for PII are being met
  • Security best practices need to be an integral part of grey data best practices

Consent, and the process of obtaining it, is critical to the ethical use and management of grey data

  • Current consent processes are frequently combative in nature, and do not scale well
  • When it comes to grey data consent, "opt-in" is in
  • The "all or nothing" approach to data collection and consent does not work well with grey data

Increasing individual control over data collection can actually increase the quality and value of data

  • Building trust in data practices builds better, more profitable long-term relationships
  • Giving users more control over the data they share results in higher-quality data

Appendix

  • Methodology
  • Further reading
  • Author

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