India’s goal to become $1 Trillion Digital economy by the year 2025 is gaining high visibility due to the current pandemic situation and its impact on the ecosystem. The investments in digital technologies is going to change the demand curve and generate businesses exponentially in near future.

The digital economy is mainly comprised of three essential parts- the infrastructure, how the business is conducted, and the selling of goods through online mechanism.

Industry 4.0 is also helping in making the processes more flexible, efficient and effective to produce high-quality goods at reduced costs by leveraging these digital technologies, thereby, enabling the growth of the digital economy. In the Indian context, the manufacturing sector needs a push through incentivization and reforms to increase the GVA which was estimated at US$ 397.14 billion in FY20PE (Financial Year 2020 Provisional Estimate by Ministry of Statistics and Programme Implementation). Moreover, this will also help the government in achieving its overarching aim to create 100 million new jobs in the manufacturing sector by 2022.

Since digital data is becoming an increasingly valuable economic resource, it is very important to understand how to rapidly create value from it. The drivers of value creation in the digital economy consist of two vital elements which are as follows:

1. Digital Platforms– As per Geoffrey Parker, “platform is a business based on enabling value-creating interactions between external producers and consumers. The platform provides an open, participative infrastructure for these interactions and sets governance conditions for them”. Digital platforms offer these mechanisms online and can be both intermediaries and infrastructures. The intermediaries connect different groups of people.
   
   For example, Facebook or any other social media channel connects users, advertisers, developers, companies and others, and Uber or any other online taxi hiring medium connects riders and drivers. Many platforms also serve as infrastructures. For example, users can develop profile pages on Facebook, and software developers can build apps for Apple’s App Store. The growth of digital platforms as a result of technological developments is strongly linked to their increasing capacity to collect and analyze digital data.
   
   The two significant types of platforms- Transaction platforms, which are sometimes alluded as two/multi-sided platforms, offer an infrastructure, typically an online resource, that supports exchanges between several different parties. They have become a core business model for major digital corporations like Amazon, Alibaba, Facebook and eBay.
   
   Another type is the Innovation Platforms which are sometimes alluded to as Engineering or technology platforms. These platforms provide ways for sharing common designs and for interactions across a sector. Related examples include operating systems (e.g. Android or Linux) and technology standards including solutions, configuration and utilization standards.
   
   Digital platforms can facilitate value-creating interactions between the different sides of the platform, as producers and consumers of different goods and services. But essentially, their effective functioning relies on digital data, and the main source of their value creation emerges from leveraging those data in intelligent ways.

2. Data and Digital Intelligence- Data-related activities are no longer mere side activities in the production of goods and services; instead, they have become an essential feature of the production process and a key aspect of economic activity. The following aspects discuss the complex dimensions of digital data as an economic resource, with implications for trade and development.

• Complex nature of data– The origin of the digital economy lies in the extraordinary amounts of detailed machine-readable information available about almost everything. The development and policy implications of data collection and use depend greatly on the type of data involved.  Data can be classified according to different criteria, for example:

• Personal or non-personal data

• Private and public data

• Data for commercial purposes or governmental purposes

• Data used by companies, including corporate data, human resources data, technical data and merchant data

• Unstructured and structured data

• Immediate and historic data

• Sensitive and non-sensitive data

• B2B, B2C, government to consumer (G2C) for paying taxes etc. or consumer to consumer (C2C) data such as online auctioning.

• Economic value of data- It is the quantification of the relationships and patterns around customers, products, services, operations and markets that drive operational, management and strategic predictions.
  
  Data Value chain– An entirely new value chain has evolved around firms that support the production of insights from data, including data acquisition (to provide new sources of data), data storage and warehousing, data modelling and analysis, and data visualization. At the lower levels of the “data value chain”, information content is limited, and therefore, the scope for value generation is also low. Value increases as the information and knowledge content rises.

The outcome of this value chain is “digital intelligence” that can inform firms in their decision-making and innovation efforts. In addition, the data can be used to improve the algorithms used for automated decision-making in the development of products, processes or services.

• Data Monetization– Some digital platforms provide different products and services “free” of charge. However, these transactions still generate value for the platform owners, as users and consumers provide them with different aspects of their personal data, such as location, preferences, relationships and personal behavior. The value creation of data arises once it is transformed into digital intelligence and monetized through commercial use.
  The various types of transaction platforms such as advertising platforms (like Facebook and Google), e-commerce platforms (include online marketplaces like Amazon, eBay), product platforms (converts traditional goods into a rentable service) and cloud platforms (like AWS, Google Cloud Platform and Microsoft Azure) are used to monetize data for generating revenue. It is important to note that individual data are of little or no value. Value emerges once data are compiled in large volumes and processed to provide insights and enable data-driven decisions by individuals, businesses, governments and other organizations.

Thus, it is the capacity of digital platforms to aggregate, process, transmit, store, analyze and make sense of data that allows them to generate value. Digital data and digital platforms can, therefore, be viewed as two sides of the same coin for much of the value creation that takes place in the digital economy.

• Ownership of data- In the traditional economy, property rights in well-established markets comprising producers and consumers strongly determine who is the beneficiary of the value of the corresponding goods and services. In view of data, the situation is less clear, as it is difficult to establish “ownership” of the data. The value of personal data is tied to the data subject or producer, and this cannot be sold. What matters more are the control, access and rights over the data.
  The data sources (i.e., the data producers or data subjects) are not able to capture any part of the economic value created with their data. Moreover, there is a risk of misuse of information, which can do harm to the user and to others. Once the data have been extracted, users typically have limited or no control over how these are used. Overall, it would operate on the dual principles of collective ownership and individual control. Collective ownership approaches may also be based looking to the greatest value of data which lies in their relationship with other data in order to provide insights or intelligence.

Summary:

As discussed above, the data value chain is an iterative process in the digital economy and data is monetized continuously unlike linear production cycle converting raw material into a finished product before reaching the consumer. Overall, it is important to consider the potential for value addition and development originated both from traditional structural change and from digital transformation. Hence, platformization and the growing reliance on data are the crucial dimensions for value creation and capture in the digital economy along with the liberal policies for promoting the high revenue-generating sectors.

Acknowledgments and References:

1. Digital Economy Report 2019- Value Creation and Capture: Implications for Developing Countries published by United Nations Conference on Trade and Development (UNCTAD/DER/2019)
2. https://www.ibef.org/industry/manufacturing-sector-india.aspx