* This piece was first published in the February 2018 issue of the Practical Lawyer (2018) PL (Comp. L) Feb 75

The boom in the technology and internet arenas has globally accelerated the growth of the digital economy. This has significantly aided the mechanism of collecting, processing and commercially exploiting the data in the hands of large corporations and even start-ups. Commonly referred to as ‘big data’, the concept refers to large volumes of a variety of data which is collected at high velocity and is then processed by computing softwares to produce unique datasets which has significant commercial value.[1] While the collection and use of personal data falls under the domain of data protection laws, a question that is now being examined by several competition law regulators is whether the use of big data can impact competition in the markets.

Before we delve into this question, it is pertinent to consider the advantages and efficiencies which result from the commercial exploitation of big data. Consider the modus operandi of any frequently used search engine. It would use self-learning computing algorithms which would observe, record and analyze search terms keyed in by the users, the websites ‘clicked on’ and combine it with data collected from its other applications and services such as e-mail or data processing services to create detailed user profiles. It would then use, and maybe even sell, these unique and individualized information assets to various online advertisers and retailers for targeted advertising.[2] Consider also the personalized recommendations of products and services that a user receives on various e-commerce platforms or on social networking websites based on the purchasing history, the keywords typed, and the general and personal information provided to these websites. Therefore, by closely tracking and analyzing the users’ needs and studying the consumer demand pattern, big data immensely assists in improving the quality of goods and services and their targeted advertising. It also improves the decision-making on the supply side by improving market predictions and the operational efficiency of manufacturers.[3]

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