There is no doubt as to the potential value of the huge volume of data generated by corporations, governments and individuals. Releasing that value involves data mining, storage and analysis at enterprise level; understanding and investing in the socio-economic benefits of data flow at government level (in fields such as health and traffic); and trust, legal and commercial frameworks to both protect the consumer and exploit personal data as an economic and social asset.

Personal data is the new asset – but to realize its value a trust framework is required to both protect and share the data: important tensions between privacy, data rights and security must be addressed and balanced.

  • Data must be allowed to flow: like oil underground or buried money, data in itself has no value until it is extracted from the system, given meaning and allowed to flow safely and securely.
  • Telcos have two unique advantages in the data space:
    • Highly regulated, trusted by consumers as custodians of personal data.
    • Hold huge amounts of data through customer relationship management, billing, and tracking.
  • Data can be monetized through innovative models and services :
    • Predictive models of behaviour involving big data and machine learning: sophisticated analysis of data from sensors, GPS and mobile phones to track interactions, social networking, stress levels or mood from individuals to large-scale encrypted data projects.
    • Location-based services offering value to customer and commercial entity alike.
    • Personal data vaults to store data securely, encrypt, extract and use as necessary (in banking, insurance, health, for example). The individual is aware of, and responsible for, all data held.
    • Gathering personal data to digitalize all experiences as life logging – either performed by individual or offered as service.
    • The quantified self, using body sensors to measure and track health, body content, meals.
    • Aggregation of data and personal preferences to demand attention and create markets in a form of reverse advertising.
    • Exploitation of government-released demographical data.
    • Data journalism to provide better, tailored services to users through established trust relationship.
    • Improve efficiency of global systems through feedback loops.
  • Protecting privacy and establishing trust are essential to enable data to flow, through frameworks of rights and responsibilities between individual and entity; transparency on data collected; and empowering the consumer to opt in or out of data disclosure on sliding scale.
  • Economic, cultural and generational differences are important: there is no global framework for data protection and the approach of our children towards privacy is completely different than ours.
  • Regulators must focus on best practice, auditable and enforceable standards rather than fine-grain micro-management that will block innovation and quickly become outdated (as “technology outruns the law”).
  • Data flow involves a continual balancing act of checks and controls between data mining and data governance in a balanced risk model.
  • The consumer is centre-stage: as source of data, as consenting partner, as market for value-added services. Maintaining consumer trust and meeting consumer needs are paramount. Giving consumers control, access rights and an appropriate infrastructure will enable data to flow.
  • Addressing data in terms of property right ownership is fragmented, complex and barely relevant given the volume of existing data and speed with which it is generated. There is no entity with absolute control, no definitive deletion of data and no guaranteed security beyond risk management.