Is data really that important to a business?
A quick survey of the top companies by market capitalisation readily reveals that data is key.
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Global | Publication | February 2021
A quick survey of the top companies by market capitalization readily reveals that data is key. While one or two depend on physical infrastructure or even hardware sales, generally speaking the remainder have:
Such insight can enable timely investment decisions, improvement in product and services offerings (for example, detecting defects and modifying products to suit customer needs),1 maximization of cost efficiencies, personalization of experience (bringing the business and customer ever closer), and an increase in revenue and profits.
Historically, businesses used vast amounts of capital to build proprietary software and systems, providing a ready barrier to entry as against competitors and new market entrants. However, with the ubiquity of open source software and everything “as a service” on the cloud, such a strategy is not nearly so effective now at shoring up market position.
Instead, the new digital market frontier is the development of sophisticated data analytics in combination with the ability to collect and process vast amounts of data – a position reinforced by their use in combination with increasingly sophisticated AI.
Some governments have for some time been encouraging more open availability of data, both that held by the state and that held by businesses; and a number of competition / antitrust authorities are paying far more attention to data held by businesses.
Perhaps partly in recognition of this, we may be witnessing the first tentative steps being taken by some of the world’s largest businesses in the direction of making some of their data available to a wider range of stakeholders with a view to collaborating, and perhaps even in furtherance of wider environmental, social and governance (ESG) objectives.
Recent cooperative ventures in relation to COVID-19 tracing apps are a case in point.
A quick survey of the top companies by market capitalisation readily reveals that data is key.
The value that can be gained from data by businesses will inevitably lead to an increase in the use of data to improve daily operations and to develop new products, services and processes.
In many jurisdictions pure information, or data, is not considered to be property. This is because a claim to property in intangible information presents obvious definitional difficulties.
There is a patchwork of different rights, intellectual property rights and contract rights that may apply to data. Understanding the way in which these rights come into play enables a business to understand how its data assets can be protected.
Disruptive technologies, such as AI, IoT, AVs, distributed ledger technology (DLT), cryptocurrencies and smart contracts, generate many different forms of data. What are the particular characteristics of such data, and to what extent can intellectual property rights or other rights protect them?
In this section, we review the EU’s position with regards to industrial and non-personal data and look at whether other jurisdictions have similar initiatives.
Data location laws (in relation to industrial and non-personal data) can be restrictive (as in banking secrecy laws, which may require some types of data to remain onshore or to be “localised”) or liberalising (as in laws that ban the prohibition of export of data from a locality).
In furtherance of the objective of leveraging existing datasets paid for by public funds, a number of jurisdictions have sought to make public sector information (PSI) available to industry.
The exclusive possession or control of data can have antitrust / competition law considerations, giving rise to access disputes.
The uncertain nature of intellectual property rights in data means that “contract is king” in data transactions.
Data is an incredibly valuable resource for businesses, enabling organisations to effectively operate and to make business improvements. In order to exploit this value most effectively, businesses must invest in good data management.
Errors, incompleteness or biases within data may flow through, and be amplified by, data analytics process outputs upon which a business's strategic and investment decisions may depend, potentially causing business losses. In this section we deal with liability arising out of use of data / datasets that are in some respect sub-optimal.