13 Nov Longa Via: Data driven innovations and infrastructure regulation
Together with my colleague Brenda Espinosa (PhD researcher at TILEC – Tilburg Law School) I have been working on a paper on data driven innovations in vital infrastructure sectors. The paper has been written within the context of ‘LONGA VIA’ ; a research project funded by the Netherlands Organisation for Scientific Research (in Dutch ‘NWO’) and the Next Generation Infrastructures network (NGInfra). The project brings together five large infrastructure operators in the Netherlands with legal and business management scholars who investigate possible regulatory and organizational challenges related to the implementation of Data driven innovations in the management of infrastructures. This short blog discusses key points of our first paper under the LONGA VIA project: ‘Exploring the regulatory challenges of using Data Driven Innovation in the management of key infrastructures’ (Espinosa Apraez & Lavrijssen, 2018, under review). Furthermore we will reflect on future research challenges.
Big Data has become a driver of multiple innovations in different sectors in the recent years: think of the cure of medical diseases based on big data analytics, automated cars, the provision of services via digital platforms (Uber, Amazon, Airbnb) etc. Acknowledging this trend, in a 2015 report the OECD introduced a definition of data driven innovation (DDI) as the significant improvement of existing, or the development of new, products, processes, organizational methods and markets arising from the dynamics generated by the use of big data (OECD 2015). In the report, the OECD highlights the opportunities brought by DDI to address economic and social challenges. The management of infrastructures employed for the provision of vital services such as transport, water and energy to the citizens, is one of the sectors which may benefit from the implementation of DDI. For example, smart sensors and Big Data infrastructure enhance the use of maintenance techniques such as data-driven Condition-Based Maintenance (CBM) or Risk-Based Maintenance (RBM) (Akkermans, Besselink, van Dongen & Schouten, 2016) and might even enable Predictive Maintenance (PdM) (Mainnovation & PwC, 2017). The result is a more targeted and timelier (‘not too early, not too late’) maintenance of infrastructures, leading to “improved availability of installations, reduction of failure costs and lower costs over the entire life cycle” (Fang, van de Kerkhof & Lamper, 2018, p. 9). Furthermore, DDI enables new types of interactions with the users or consumers of the services provided through key infrastructures (Espinosa Apráez & Lavrijssen 2018). On the one hand, thanks to data-based innovations consumers are shifting from a merely passive role to become more active and engage in activities that may contribute to a better management of the networks. Take for example smart grids and smart meters, which make possible that consumers of electricity participate in demand response programs (adapting their consumption to the network capacity), helping DSOs to balance the network load (Edens & Lavrijssen, 2018). The same technologies, together with self-generation mechanisms, make possible that consumers are able not only to take electricity from the grid, but also can feed it to the grid, acting as ‘prosumers’ (Lavrijssen & Carrillo Parra, 2017). On the other hand, users and consumers may also be a ‘source’ of information revealing insights of the condition and functioning of infrastructures, e.g. via smart meters (employed for utilities such as electricity, water and gas) or applications used to report a failure or damage in certain assets.
In sum, DDI offers new possibilities of action for the infrastructure managers, but at the same time brings questions regarding the suitability of existing regulations to deal with the opportunities and possible concerns brought by DDI. For example, current regulations usually are based on the assumption that the infrastructure operators should make large capital investments in ‘copper and wire’, thus it could be questioned whether these regulations sufficiently allow to recover the investment costs in ICT and smart technologies via the network tariffs set by the national regulatory authorities. Furthermore, regulations often do not consider the enhanced possibilities for interaction between the consumers and the infrastructure operators, as it occurs currently with the provision of flexibility services by consumers in the electricity sector (Edens & Lavrijssen, 2018). The mismatch between technological changes and legal reality is often denoted as ‘regulatory disconnection’ (Bennet Moses, 2007; Brownsword & Goodwin, 2012; Marchant, 2011b; Butenko & Larouche, 2015).
In our paper we explore possible challenges of using data driven innovation in the management of key infrastructures. The identification of such issues is necessary in order to anticipate and/or overcome possible regulatory disconnections. Policy-makers should be aware of the type of problems that may arise, the need for solving them and how they may be dealt with by balancing on the one hand the benefits of fostering innovation and on the other hand, the need to protect social interests or individual rights that may be affected by the implementation of DDI.
Furthermore, our paper explicitly considers that the implementation of DDI for infrastructure management takes place in the context of highly regulated sectors (e.g. the provision of water and energy), which often translates into more legal constrains and stricter supervision for the operators of the infrastructure, compared to firms in less regulated markets (e.g. online platforms).
To study how such challenges may become apparent in practice, we analyze the possibility of introducing smart metering for drinking water in the Netherlands. In the European context, a great deal of attention has been paid to the large scale roll-out of smart meters for the small consumers in the energy sector (electricity and gas), but considerably less is discussed about smart metering in the drinking water sector, with a few exceptions in countries such as Malta (see OECD, 2017) and more recently the United Kingdom.
We observe that introducing smart water meters in the Netherlands (provided that there is a positive cost-benefit analysis of the technology) might bring both opportunities and concerns that are not adequately dealt with in the regulations in place at micro level (i.e. metering activity) and macro level (drinking water legislation and regulations). Regarding the opportunities, our analysis concludes that under the existent rules the use of water meters serves only the purpose of determining water consumption, excluding additional uses of the meter data such as leak detection or better monitoring of the network. With regard to the concerns, we find that current rules might be ill-equipped to deal with the issues (in terms of data protection and privacy) that may arise from a more intensive use of data generated at the homes of consumers.
Topics for further research
Next to the abovementioned challenges, the LONGA VIA project is investigating other aspects of DDI that may require the attention of policy-makers. Access to technical data and user data is of crucial importance for the infrastructure managers to perform their public tasks to operate and manage their infrastructures. In practice, they cannot always have access to the data they need, e.g. because of certain provisions in the contracts that are closed with construction companies that maintain the infrastructures or as a consequence of strict regulations. Not only the infrastructure managers but also new companies may want to have access to data regarding the functioning and the use of the networks, in order to offer new innovative services to the infrastructure managers or to the users of these infrastructures. However, regulations or dominant positions may limit access to the relevant data, stifling innovation in the development of new services that could enhance the performance of the infrastructure managers. Furthermore, there may be a tension between the data protection rules on the one hand and the performance of the public interests’ tasks by the infrastructure operators on the other hand, which may require the processing of personal data in a frequent way. Currently there is no clear balancing framework for the policy-makers and the operators themselves to substantiate how the public interest tasks of the network operators can be balanced against the right to the protection of personal data of the network users. The absence of such legal framework may cause legal uncertainty and controversies regarding the proper legal base for the processing of personal data in the infrastructures, as illustrated by recent discussions regarding the proper legal base for distribution network operators to process data in the energy sector.
When it is identified what type of issues may arise, policy makers can make better assessments whether the issues are real, what interests are at stake, how these interests could be balanced and what would be proper regulatory responses. In any event it is clear that more empirical and legal research is needed into the type of data that is available or should be made available in the infrastructure sectors, who needs this data for what purpose and whether there is a proper legal basis for the processing of this data. With our Blog and papers, we will keep you updated of the relevant developments. To be continued…..
Akkermans, H., Besselink, L., van Dongen, L., & Schouten, R. (2016). Smart Moves for Smart Maintenance. World Class Maintenance. Retrieved from https://www.worldclassmaintenance.com/publicaties/smart-moves-for-smart-maintenance/
Bennett Moses, L. (2007). Recurring Dilemmas: The Law’s Race to Keep Up With Technological Change. Journal Of Law, Technology & Policy, 2007(2), 237-285. Retrieved from http://illinoisjltp.com/journal/wp-content/uploads/2013/10/05-05-08_Moses_AHW_Formatted_FINAL.pdf
Brownsword, R., & Goodwin, M. (2012). Law and the Technologies of the Twenty-First Century. Cambridge: Cambridge University Press.
Butenko, A., & Larouche, P. (2015). Regulation for innovativeness or regulation of innovation?. Law, Innovation And Technology, 7(1), 52-82. doi: 10.1080/17579961.2015.1052643
Cuijpers, C., & Koops, B. (2013). Smart metering and Privacy in Europe: Lessons from the Dutch Case. In S. Gutwirth, R. Leenes, P. de Hert & Y. Poullet, European Data Protection: Coming of Age (pp. 269-293). Dordrecht: Springer. Retrieved from https://www.springer.com/gp/book/9789400751842
Edens, M., & Lavrijssen, S. (2018). Balancing Public Values During the Energy Transition – How Can German and Dutch DSOs Safeguard Sustainability?. TILEC Discussion Paper, DP 2018-015. doi: 10.2139/ssrn.3179372
Espinosa Apraez, B. & Lavrijssen, S.A.C.M. (2018), ‘Exploring the regulatory challenges of using Data Driven Innovation in the management of key infrastructures’, under review (2018).
Fang, F., van de Kerkhof, R., & Lamper, L. (2018). De waarde van Smart Maintenance voor de Nederlandse Infrastructuur. World Class Maintenance. Retrieved from https://www.worldclassmaintenance.com/publicaties/de-waarde-van-smart-maintenance-voor-de-nederlandse-infrastructuur
Lavrijssen, S., & Carrillo Parra, A. (2017). Radical Prosumer Innovations in the Electricity Sector and the Impact on Prosumer Regulation. Sustainability, 9(7), 1207. doi: 10.3390/su9071207
Mainnovation and PwC. (2017). Predictive Maintenance 4.0: Predict the unpredictable. PwC. Retrieved from https://www.pwc.nl/en/publicaties/predictive-maintenance-40-predict-the-unpredictable.html
Marchant, G. (2011b). The Growing Gap Between Emerging Technologies and the Law. In G. Marchant, B. Allenby & J. Herkert, The Growing Gap Between Emerging Technologies and Legal-Ethical Oversight (pp. 19-34). Springer. Retrieved from https://link.springer.com/book/10.1007%2F978-94-007-1356-7
OECD. (2015). Data-Driven Innovation: Big Data for Growth and Well-Being. Paris: OECD Publishing. Retrieved from http://dx.doi.org/10.1787/9789264229358-en