The Obsolescing Bargain Model and the Digital Economy

The obsolescing bargain model was born in the early 70s, a period when large American multinational corporations – mostly oil companies – rapidly expanded into resource-rich developing countries[1]. Essentially, the model describes a situation where a large multinational corporation (MNC), which, owing to its substantial financial capital and technological know-how, is able to negotiate an initial agreement with a host country from a favorable bargaining position. However, over time the balance of bargaining power tips towards the state, which may develop its own assets and capacity to extract resources, and, given the growing contribution of the local enterprise to the MNCs revenues, can bargain for a better deal.

Data, not oil, is the most valuable resource today – but it is still the developing markets that offer most of the newly created riches for data-extraction MNCs. So, since governments are increasingly aware of the role of data in value creation, are we to expect the Obsolescing Bargain Model appearing in the today’s digital economy?

While there are many similarities – large high-tech multinationals extracting data from developing nations where technology takes an ever-greater role in everyday living, there are important differences. For starters, while oil riches, even if unequally spread, have clearly lifted national economies by creating jobs, infrastructure, and enabling social packages of varying generosity, the promise of a massive net effect of digital ecosystems, which made countries roll out red carpets to high-tech investment and channel funds into building up local Silicon Valleys, has proven to be an elusive one. The contribution of digital technologies to national economies has been notable, but likely far from the transformative effect that developing countries rushing to catch up with the digital revolution have hoped for. Notwithstanding the many inspiring success stories of successful digital entrepreneurs, even in developed countries such as most EU members, the contribution of the ICT sector to GDP remains below 6%[2], and rises up to 8% in the US – home to the largest global internet companies, and India[3] – the world’s top software outsourcer.

Growing connectivity and explosive mobile internet adoption in developing markets has indeed created vast volumes of data, and digital MNCs – not the local economies or players, with a few exceptions – have been best positioned to reap the benefits. In addition to the near-monopoly position in data processing, the digital giants “enjoy such high profits that they can quickly capture new markets by buying out competitors or developing a rival service; local startups, including those in developing countries, are left with tiny niche markets”[4].

The economic might of digital powerhouses such as Google, Facebook and Amazon may not be dissimilar to the positions enjoyed by the energy giants of the past, but major data companies are reliant neither on local labor nor local suppliers as much as the extraction companies were. Data extraction businesses do not need to continuously train local specialists who would later advocate for a better deal or substitute MNCs’ knowledge and expertise with their own. The local R&D centers of MNCs may help countries build their own digital talent pipeline and contribute to the development of the local digital ecosystems, but they do not create interdependent relations between local labor and global revenues that form around natural resource extraction. The digital MNCs can enter or withdraw from the market relatively cheaply – on a whim, even.

In the Obsolescing Bargain Model, host countries over time develop capital and knowledge to steer negotiations in their favor, but in the digital world, where a company does not even need to be present to collect data, the key leverage a state has over the digital giants is the access to the local data itself. This is no trifling matter, since developing markets are a major source of growth – for instance, developing nations account for nine out of 10 countries with the largest number of users of Facebook[5], with India alone being home to more than 10% of the 2.7 billion Facebook users in the world. Hence, the chain of recent regulatory measures aimed at data localization or cross-border data flows may be viewed as nations striving to take control over what they consider their ‘natural resource’.

The conversation around data regulation is often framed around ‘security’ (or ‘protection’) and ‘enablement’ (or ‘competitiveness’), but this should not confuse the observer... – these are simply two sides of the same data-ownership coin. Governments increasingly recognize that digital or cyber security are not achievable without enabling domestic players to tap into data collected within a country, and no enablement of domestic players can occur without them considering what their government defines as security. In fact, to some countries data security is not an impediment to technological development; on the contrary, it is often an enabler for domestic digital businesses. For instance, there is a lot to learn from the rise of Chinese tech unicorns, but favorable, even protective, conditions created for local internet companies by data flow restrictions coupled with the sheer size of the country’s market are certainly carefully studied by governments across the world. Conversely, the European focus on personal data protection aims to level the playing field for European startups that compete with aggressive and data-hungry peers from the US and China both within the EU and beyond. Even the US ban of TikTok on grounds of ‘security’, followed by a nudge to sell the business to a US-based company, falls well into this list of data localization efforts, despite the official American policy calling for a borderless open internet.

More so, governments, often mocked by high-speed digital businesses as slow and inefficient, do not shy away from developing their own data-driven platforms of scale. The world’s largest biometric database Aadhar in India, Estonia[6] and Singapore[7] achievements in building advanced e-government ecosystems with public funds and by public institutions, and even the controversial attempt to centralize medical data of Australians under My Health Record[8] initiative are all cases in point. People may not necessarily trust their local authorities to handle their data properly (although they rarely know how much of it is being collected and stored and often have little choice anyway) but, just like local regulators, they often trust multinational corporations even less. MNCs’ cavalier approach to personal data caused a pushback of landmark smart city developments driven by the private sector, such as Google’s project in Toronto[9]. Successful smart cities – from Medellin[10] to Moscow[11] to Shenzhen[12] – are already built and run by municipal authorities that tap into the data they collect to better manage infrastructure and security, and to better service the growing urban populations.

The key difference between public and privately-funded digital projects is that, contrary to Silicon Valley’s mantra, the former fail rather late and after several budget increases – but some initiatives live on and even thrive – especially in markets applying the mixed state-private ownership model. Contrary to the popular belief of governments selling off their services to private sector players, in many ways the public sector continues to use data ownership to secure its exclusive role as the sole provider of critical services. MNCs’ attempts to break into the territory the state considers its own are shot down early, like what happened with COVID-19 tracking apps developed by Apple and Google despite their potential advantages over hastily developed domestic solutions.

Companies striving to expand into foreign markets need to adapt their business strategies to the changing reality on the ground. In the traditional offline economy, a miscalculation in negotiating a deal between an MNC and a state comes at a price – the ultimate illustration of the Obsolescing Bargain Model in practice is the long list of oil assets nationalized since the 70s. While it is unlikely that governments will nationalize data extraction mechanisms anytime soon, there is little doubt they will continue to seek ways to assert control over data collection, transfer and usage, and tighten regulations to allow domestic digital players and policies to catch up. Data regulations on their own may not create local Googles or Facebooks, but the all-powerful digital giants will soon find themselves negotiating terms and conditions of surrendering, sharing, and co-developing their local data assets. Obsolescing bargain or not, the balance of power in the digital economy is clearly tipping towards the state – and companies used to being creative disruptors of the status quo may need to learn to become, at least partially, disciplined enablers of government initiatives.

[1] Raymond Vernon (1971) Sovereignty at bay: The multinational spread of U.S. enterprises.

[2] Eurostat: Percentage of the ICT sector on GDP. Accessed on September 10, 2020. https://ec.europa.eu/eurostat/databrowser/view/tin00074/default/table?lang=en

[3] Seconded European Standardisation Expert in India (SESEI). Indian ICT Sector Profile Report (2019). http://www.sesei.eu/wp-content/uploads/2019/02/ICT_Sector-Profile-Report.pdf

[4] A World Bank Group Flagship Report. Digital Dividends (2016), p. 20. http://documents1.worldbank.org/curated/en/896971468194972881/pdf/102725-PUB-Replacement-PUBLIC.pdf

[5] Statista. Leading countries based on Facebook audience size as of July 2020, accessed 10 September 2020. https://www.statista.com/statistics/268136/top-15-countries-based-on-number-of-facebook-users/

[6] Nick Heath. “How Estonia became an e-government powerhouse”. TechRepublic, February 19, 2019 https://www.techrepublic.com/article/how-estonia-became-an-e-government-powerhouse/

[7] Yun Xuan Poon. “Inside Singapore’s GovTech Rapid Deployment Unit”. GovInsider, November 22, 2019. https://govinsider.asia/innovation/singapore-govtech-li-hongyi-open-government-products-parkingsg/

[8] Josh Taylor and Amy Corderoy. “My Health Record: amost $2bn spent but half the 23m records created are empty”. The Guardian, January 22, 2020. https://www.theguardian.com/australia-news/2020/jan/23/my-health-record-almost-2bn-spent-but-half-the-23m-records-created-are-empty

[9] Ian Austen and Daisuke Wakabayashi. “Google Sibling Abandons Ambitious City of the Future in Toronto”. The New York Times, May 07, 2020. https://www.nytimes.com/2020/05/07/world/americas/google-toronto-sidewalk-labs-abandoned.html

[10] David H. Freedman. “How Medellín, Colombia, Became the World's Smartest City”. Newsweek, November 11, 2019. https://www.newsweek.com/2019/11/22/medellin-colombia-worlds-smartest-city-1471521.html

[11] Arseny Kalashnikoff, “Time to move to Moscow? The city has the world’s best digital government”. Russia Beyond, August 2, 2018. https://www.rbth.com/science-and-tech/328886-moscow-best-digital-government

[12] William Zheng, “China’s Shenzhen is using big data to become a smart ‘socialist model city’”. South China Morning Post, November 01, 2019. https://www.scmp.com/news/china/politics/article/3035765/chinese-city-shenzhen-using-big-data-become-smart-socialist