Non-personal data as an IP asset

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Report on a session of the International Commerce and Distribution Committee at the IBA Digital Operations Conference in Hamburg

Thursday, 14 November 2019

Session Co-Chairs

Marc Hilber  Oppenhoff & Partner, Cologne; Senior Vice-Chair, IBA Technology Law Committee

Martin Oder  Haslinger/Nagele Rechtsanwälte, Vienna; Assistant Programme Officer, IBA International Sales Committee

Speakers

Stephanie Pautke  Commeo, Frankfurt; Committee Liaison Officer, IBA Healthcare and Life Sciences Law Committee

Barton Selden  Taulia Inc, San Francisco; Committee Liaison Officer, IBA Corporate Counsel Forum

Susanne Wende  Noerr, Munich

Prof Dr Andreas Wiebe  Chair for Civil Law, Intellectual Property Law, Media Law and Information and Communications, Georg-August-University, Göttingen

Christian Winkelhofer  Accenture, Vienna

This session provided an interesting conclusion to the conference by building on concepts of digitisation and the disruptive technological transformation of the supply chain and focusing on data as a building block and source of competitive advantage. The speakers discussed the notion – and implications – of data viewed as not only auxiliary and subsidiary to digitised solutions to business, but also as foundational and, in its own right, as an asset with intrinsic commodity value and attracting intellectual property status and protection.

The speakers described the context leading to the increasingly strategic role of data in the supply chain by reference to the development and adoption of ever more sophisticated mechanisms for access, analysis, use and dissemination of such data (eg, various models) and the novel possibilities unravelled by the use of data for business efficacy and efficiency. The belief seems to be spreading that data can now warrant treatment and protection accorded to intellectual property assets. Such treatment and concomitant protection raise stimulating questions, covered in animated debate in the session’s workshop component, about data’s utility, desirability and limits. The session specifically addressed the following:

• how data-driven business models work;

• how data can be protected from an IP and civil law perspective;

• international use of data/protection of data under unfair competition law;

• when data should be considered non-personal and what claims individuals have affecting the data asset;

• which rights exist for companies to access data under antitrust law; and

• contracts, data and electronic invoicing.

The workshop component extended the debate with the inclusion of the headline-making news this year of the German regulators’ ongoing court saga concerning Facebook’s activities in Germany. This took place in the aftermath of the Cambridge Analytica scandal. The discussion centred on the appellate victory for Facebook in the Higher Regional Court in Dusseldorf in August this year regarding a German antitrust order relating to Facebook’s alleged user data collection practices across the company’s platforms, which included apps such as Instagram and WhatsApp.

The Court essentially vacated a decision (of the German Federal Cartel Office) that would have prevented Facebook from combining or aggregating the data that the company collects about users across its platforms and on third-party apps and websites. The Cartel Office indicated that it would appeal this decision to the German Federal Court of Justice.

To put this in context, one needs to consider Facebook’s position as the world’s biggest social network and the repository of what is consequently and by all accounts an unprecedented amount of information from users. The crux of the discussion was the Cartel Office’s allegation that Facebook used its dominant market position (ie, as the world’s biggest social network) to gather information about users without their consent.

The Cartel Office’s concern was apparently with how Facebook gathers data from third-party apps and its online tracking of non-members who engage in exchanges with these platforms through online participation via Facebook’s settings (its ‘like’ and ‘share’ prompting buttons.)

The key takeaways from the workshop relate to the implications of the decision for the free circulation of non-personal data for the vitality of business and the data economy. The concern expressed by some participants was whether competition (antitrust) law remedies were in this case aptly invoked or whether they were merely raised as a functional equivalent to privacy laws. In the context of non-personal data, some viewed the Cartel Office’s initial intervention as not necessarily inconsistent with the right of individuals (and companies) to store and process non-personal data freely. Others viewed this as an exercise of regulatory fiat in the context of perceived monopolistic or anticompetitive practices in respect of an otherwise underlying legitimate pursuit (the commoditisation of the data in issue) for distinct competitive advantage in the marketplace of a digital world.

Either way, the final word is still out. In the interim, the consensus appears to be (as reflected, among other things, by the Regulation 2018/1807 on the free flow of non-personal data in the European Union, cited by many participants in the workshop) that the data economy is here to stay and that we will have to balance and harness competitive realities (both private and public) within competing (no pun intended) privacy and individual dignity interests. On both counts (the competitive and the private), our participants concluded, user data safeguards are more relevant than ever.

Another workshop was led by Christian Winkelhofer, an expert for digital transformation and new business models at Accenture. The focus was on modelling data and illustrating how to unlock trapped value for organisations and customers by leveraging technology and process innovation through data. In essence, this was a good practical demonstration of the value of data as a commodity and the tactical and strategic potential use that data can be put to in maximising value propositions. One of the issues under discussion – a latent and persistent theme throughout the conference, I may add, whether it be in the use of blockchain in supply chain or predictive models in autonomous transportation settings – was the reliability of the underlying data for the various steps that the data purported to validate. Accordingly, the issue of ‘quality’ of the data emerged in discussion as another important (and sometimes intractable) variable in using data as an asset.

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