This presentation by Cyril Ritter, European Commission, DG COMP 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

1. Cyril Ritter
European Commission, DG COMP
OECD, 29 November 2016
EU competition law,
personal data,
and big data

2. Background
• Two claims by some stakeholders: some large online service
providers
– are not delivering level of data protection/privacy that
people want
– are gaining an insurmountable advantage by
accumulating big data
• If these claims are true, can and should EU competition law
address them?
• Other concerns better addressed primarily through other
policies than competition law: profiling, hacking
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3. Main milestones
• 2006: Asnef judgment
– Data protection "as such" = not relevant to competition case
• 2008: Google/Doubleclick merger decision
• 2014: Facebook/WhatsApp merger decision
• 2016: Commissioner Vestager's speeches; merger consultation
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4. What data? What uses of data?
• Personal data = identifies any individual through any parameter
• Not all big data is personal data
• Big data  useful to improve services
• Personal data  useful for targeted advertising
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5. "Zero price" markets
• Covered by EU data protection law & consumer protection law
• Importantly, also covered by EU competition law
– 1991 Höfner judgment
– Competition law = price, quality, output, choice, &
innovation
– Many EU competition decisions on "zero price" markets
• Market definition usually not a problem in practice 5

6. Viewing data through four different
perspectives
• Data as a currency
• Data protection as quality (= mostly about personal data)
• Data as an input/asset (= mostly about big data)
• Data as an output
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7. Data protection as quality
• Cartel
• Exploitative abuse
• Merger
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8. Data as an input/asset
• Addressing the "data advantage" through abuse or merger cases
• But when is there a "data advantage"?
– Is data a key element of the success of the product?
– Is it about the data or the ability to analyse data?
– Is the data replicable or available from other sources?
Does it experience decreasing returns?
– How quickly does the data become outdated?
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