Issues about data – for example customer lists and purchase histories – have been relevant to competition authorities for decades. But various technological developments have led to rather revolutionary changes in the amount and kinds of data that can be gathered and the ways in which that data can be analyzed and used. So the era of so-called Big Data is likely to present new competition law issues. But we’re fairly close to the beginning of the road of assessing how Big Data may raise competition concerns. Having massive quantities of data and even achieving a great advantage in data scale does not inherently yield dominance or give rise to incentives to preserve that dominance through anti-competitive conduct. Nor would the acquisition of a “data rich company” necessarily lead to dominance or significantly impede competition.
A number of instances might arise where data and scale will give rise to competition problems, but every situation will have to be addressed on its own facts. There are three areas where data and competition law may intersect: (i) merger control and data; (ii) dominance cases involving data; and (iii) the use of data and concerted practices. Each will be addressed in turn.
2. Merger control and data
There is a need to distinguish between two issues: (i) whether the existing Merger Regulation thresholds should be modified to require notification of data-driven acquisitions that are currently not subject to review by the European Commission (“EC“), and (ii) the assessment of potential harm to competition in cases that are subject to merger control (either under the existing thresholds or some new ones meant to capture more data-related deals).
At the beginning of October the EC launched a public consultation on the possibility of changing the existing Merger Regulation’s purely turnover-based notification thresholds. Some have suggested that the purely turnover-based thresholds do not necessarily capture some transactions that could raise serious competition concerns. For example, an innovative target with little or no income could be a tempting acquisition, especially if the acquirer can combine the target’s assets with its existing assets – perhaps including data — in a way that yields a competitive advantage – or, if by acquiring the target, an existing large market player can avoid disruption of the market by an innovative new competitor.
Potentially, the acquisition by an existing large player of another company with little current revenue but large quantities of unique data that is not easily replicable could establish barriers to entry and establish or maintain a dominant position.
In the pharmaceutical sector, an existing large player might be after a target pipeline; the target might have developed a promising new drug that’s not yet approved for sale (which might compete with the acquirer’s existing products).
In theory, acquiring a company with these kinds of assets might result in “a significant impediment of effective competition“, even though the company’s turnover might not be high enough to meet the Merger Regulation thresholds. Nevertheless, one should be cautious about making changes to the merger notification thresholds. It is important to find the right balance in order only to cover mergers that could have potentially negative effects on competition, without making life harder for innovative startups.
One key question is whether there really is any evidence that potentially anti-competitive transactions are falling through the cracks. Some suggest that Facebook’s acquisition of WhatsApp in 2014 presented an example of a gap in the EC Merger Reg. Facebook paid USD 19 billion for a company with 600 million customers, but the merger did not need to be notified to the EC because WhatsApp’s turnover was too low. Other than Facebook/WhatsApp, which is not necessarily the best example of a case proving a need to change the EU thresholds because the case was ultimately referred to the EC by the national competition authorities of three Member States, there seem to have been no cases suggesting there is such a need. As such, there does not seem to be any concrete experience demonstrating the jurisdictional rules should be changed in order to look beyond turnover as a means to identify whether or not a merger should be notified.
It should be noted that Germany is moving on this front. The Government published a proposed amendment to the German Antitrust law for a new merger control notification threshold based on transaction value. The German proposal resembles the size-of-transaction test used in the United States. One question that arises in this context is this: why, if a size-of-transaction test works in the U.S., would it be so bad for one to be adopted by Germany or the EC?
3. Dominance and data
Second, it is worth considering data in the behavioural context. There are two aspects to it:
(i) Can controlling data and having a large advantage in data scale give rise to dominance?
(ii) To what extent can a dominant company’s conduct related to data restrict competition?
Controlling data and having a large data scale advantage does not inherently yield dominance. Nevertheless, achieving scale in data may create barriers to entry and can be a means to establish or strengthen market power.
Search and search advertising is one area with which the EC has become very familiar over the years (going back at least to Double Click). Thus, the search and search advertising areas are more ripe than any others for addressing the consequences of data and scale and may well present differences from how scale and data is or should be analyzed in other areas.
In search, having a huge scale advantage in query-related data will yield dominance, and a dominant search company’s interest in retaining its data scale advantage and buttressing barriers to entry – and to monetize its data in ever-expanding ways – will give rise to incentives to engage in conduct that might be deemed unlawful under the antitrust laws.
In relation to search engines specifically, it is query scale – not technology – that is the primary driver of search engine profitability and competitiveness, due in particular to machine-learning aspects of search. Search algorithms learn from user queries and how users interact with search results, and the greater the scale advantage with respect to number of queries (in particular so-called “long tail” queries), the more relevant results the search engine will be able to show to users.
This helps explain why barriers to entry can be so high in a search engine market where one company has an overwhelming advantage in scale of queries.
Having considered dominance, it is also necessary to examine to what extent a dominant company’s conduct related to data can actually restrict competition.
Can foreclosing competitors’ access to data constitute an abuse? Many argue that this depends on the type of data, and its replicability. This has already been analyzed in the merger context: if the data acquired by the acquiring company from the target is easy to obtain from other sources, then there may be no anti-competitive effects.
What if a dominant company changes its privacy practices to combine sources of data that gives it abilities to monetize that data in ways no competitor can match? Might this be an exploitative abuse under Article 102? And if it forecloses competition by other advertizing competitors, might it be an exclusionary abuse?
4. Concerted practices and data
A third example of potentially infringing data-related conduct arises in the context of potential concerted practices. What if competitors on the market used artificial intelligence means to determine prices? Let’s say those tools determined that the most profitable way to respond to an increase of the price by a competitor would be to increase one’s own price (rather than keeping one’s price down to capture a higher volume share). There would be in principle no agreement between companies themselves, yet the result for the consumers would be an increase in prices.
Many data-related antitrust questions and interesting debates are still to come. Some instances might arise where data and scale will give rise to competition problems, but every situation will have to be addressed on its own facts.