Accessing Big Data

Business models and incentives

In a new OECD Statistics Working Paper, titled Access to New Data Sources for Statistics, we examine legal requirements and business incentives to obtain agreement on private data access, and more generally ways to facilitate the use of Big Data for statistical purposes. Using practical cases, the paper analyses the suitability of five generic data access models for different data sources and data uses in an emerging new data ecosystem. Concrete recommendations for policy action are presented in the conclusions.

Executive Summary

New data sources from the private sector have enormous potential to complement and enhance official statistics by, for example, providing more timely data and developing new areas for analysis. The increasing number of research projects using this data underlines its potential. However, progress to operationalize the use of such data sources in the world of official statistics is proving to be slow due, in part, to barriers in gaining access to data from private corporations. Such barriers take the form of concerns on the part of private companies about losing their competitive advantage; legal constraints concerning privacy and confidentiality of client information; and the costs of setting up the necessary infrastructure and training staff for a non-core business related activity.

Nonetheless, several business models that enable data exchange between private corporations and official statistics are emerging, including:

  1. in-house production of statistics
  2. transfer of data sets to end users
  3. remote access to data
  4. trusted 3rd parties (T3Ps)
  5. moving algorithms rather than data.

Each of these business models, along with their associated risks and technical and governance requirements, are examined in this paper.

Incentives for private companies to share their data include the mutual benefits accrued from working with National Statistical Offices (NSOs), the potential to develop new analytical skills, improve their reputations, generate revenue, meet regulatory compliance and demonstrate corporate responsibility. There is growing recognition among many companies – albeit slowly – of these many incentives for making data available for public good.

After examining various data sharing models and incentives, the paper makes a number of recommendations for policy actions. These recommendations suggest the need for NSOs to enter into partnerships with private providers:

  • Corporations should consider electing “data stewards” to act as focal points for data access.
  • A network to share experiences and know-how around data sharing and evidence of impact should be created.
  • A repository of case-studies that highlight innovation in sharing practices should be developed.
  • A decision tree to help assess benefits and risks of sharing corporate data should be defined.
  • A standardized safe environment for sharing data without risk of compromising customer privacy should be developed.

The full paper is available in the OECD Statistics Working Paper Series.


comments powered by Disqus