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Big data: Bringing competition policy to the digital era – STUCKE – November 2016 OECD discussion

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OECD Directorate for Financial and Enterprise Affairs
OECD Directorate for Financial and Enterprise Affairs

This presentation by Maurice E. Stucke from the Konkurrenz Group was made during the discussion on "Big Data: Bringing competition policy to the digital era" held during the 126th meeting of the OECD Competition Committee on 29 November 2016. More papers and presentations on the topic can be found out at www.oecd.org/daf/competition/big-data-bringing-competition-policy-to-the-digital-era.htm

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Big Data and Competition Policy OECD 29 November 2016 Maurice E. Stucke | The Konkurrenz Group MauriceStucke@Konkurrenzgroup.com
Issues 1.Are the current competition tools adequate to address big data? 2.Should we expect privacy issues to be solved by privacy laws and/or by the sole functioning of the market system?
Our Aims • First to understand what is Big Data and the 4 Vs of data – namely the volume, velocity, variety and value of personal data • Second to better understand the competitive significance of Big Data • Third to examine whether market forces will always provide consumers with mechanisms to protect their privacy interests • Fourth to look at how the EU and US review data-driven mergers • Fifth to identify the risks if the antitrust agencies ignore Big Data
Big Data Exposes Several Weaknesses in Today’s Antitrust Framework • Antitrust has gravitated to assessing mergers’ short- term price effects in narrowly-defined markets What is readily measurable has become increasingly more important Parameters of competition that are harder to quantify (such as quality when the product is free) are marginalized or ignored • Data-driven mergers can defy the conventional antitrust categories • Antitrust looks at substitutability – but data-driven mergers may be driven for the variety of data
5 Signposts of Progress for the Competition Agencies • 1st Signpost: recognizing when privacy and competition policy intersect
5 Signposts of Progress for the Competition Agencies • 2nd Signpost: identifying and prosecuting data-driven abuses by dominant firms
5 Signposts of Progress for the Competition Agencies • 3rd Signpost: escaping from their current price-centric antitrust trap
5 Signposts of Progress for the Competition Agencies • 4th Signpost: recognizing (and having the tools to assess) data-driven efficiencies
5 Signposts of Progress for the Competition Agencies • 5th Signpost: greater cooperation among competition, privacy and consumer protection officials
The Collusion Analytical Framework • The Messenger Scenario  Topkins • Hub and Spoke  Uber • Tacit Collusion on Steroids: The Predictable Agent • Digital Eye  God View and Artificial Intelligence  Big Data and Big Analytics

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Serial Acquisitions and Industry Roll-ups –TZANAKI – December 2023 OECD discu...
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Serial Acquisitions and Industry Roll-ups – GOGA – December 2023 OECD discussion
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Serial Acquisitions and Industry Roll-ups – KOKKORIS – December 2023 OECD dis...
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Serial Acquisitions and Industry Roll-ups – OECD – December 2023 OECD discussion
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Big data: Bringing competition policy to the digital era – STUCKE – November 2016 OECD discussion

  • 1. Big Data and Competition Policy OECD 29 November 2016 Maurice E. Stucke | The Konkurrenz Group MauriceStucke@Konkurrenzgroup.com
  • 2.
  • 3. Issues 1.Are the current competition tools adequate to address big data? 2.Should we expect privacy issues to be solved by privacy laws and/or by the sole functioning of the market system?
  • 4. Our Aims • First to understand what is Big Data and the 4 Vs of data – namely the volume, velocity, variety and value of personal data • Second to better understand the competitive significance of Big Data • Third to examine whether market forces will always provide consumers with mechanisms to protect their privacy interests • Fourth to look at how the EU and US review data-driven mergers • Fifth to identify the risks if the antitrust agencies ignore Big Data
  • 5. Big Data Exposes Several Weaknesses in Today’s Antitrust Framework • Antitrust has gravitated to assessing mergers’ short- term price effects in narrowly-defined markets What is readily measurable has become increasingly more important Parameters of competition that are harder to quantify (such as quality when the product is free) are marginalized or ignored • Data-driven mergers can defy the conventional antitrust categories • Antitrust looks at substitutability – but data-driven mergers may be driven for the variety of data
  • 6. 5 Signposts of Progress for the Competition Agencies • 1st Signpost: recognizing when privacy and competition policy intersect
  • 7. 5 Signposts of Progress for the Competition Agencies • 2nd Signpost: identifying and prosecuting data-driven abuses by dominant firms
  • 8. 5 Signposts of Progress for the Competition Agencies • 3rd Signpost: escaping from their current price-centric antitrust trap
  • 9. 5 Signposts of Progress for the Competition Agencies • 4th Signpost: recognizing (and having the tools to assess) data-driven efficiencies
  • 10. 5 Signposts of Progress for the Competition Agencies • 5th Signpost: greater cooperation among competition, privacy and consumer protection officials
  • 11. The Collusion Analytical Framework • The Messenger Scenario  Topkins • Hub and Spoke  Uber • Tacit Collusion on Steroids: The Predictable Agent • Digital Eye  God View and Artificial Intelligence  Big Data and Big Analytics