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Digital Technology and Marketing Communication Essay


The new wave of technology revolution has fundamentally transformed the life of the masses. It has changed how they live, work, and communicate with one another. The new technology is much larger in scope, scale and complexity than anything that humanity has experienced so far. Its complete effect on humankind is yet to be entirely unravelled, yet it is essential to understand how it may further alter economic and social life in future.

The first industrial revolution mechanised production using water and steam. The second ushered in the use of electricity to help in mass production. Electronic and information technology brought in the third industrial revolution. This has brought in the possibility of a fusion of technologies that blurs the line between the physical, digital, and biological spheres. Today, we stand at the juncture of another technological revolution, which will change the way people live and work. This new technological change is being called the Fourth industrial revolution. The new technology had immense ramifications for production, management and governance. Extraordinary advancement in the field of artificial intelligence also brought about other aspects of the revolution such as robotics, Internet of things, nanotechnology, etc.

This technology presents both opportunity and challenges for the organization. In future, this technology will also increase efficiency and productivity and will usher in an age of market-driven growth. It will alter supply chains and help in making business more cost-effective. This new-age technology presents both opportunity and challenges for the organization. Ordering a cab, booking a ticket for a flight or film has changed. It is no longer necessary to stand in queues to do these things. A ticket is just a click away. In future, this technology will also increase efficiency and productivity and will usher in an age of market-driven growth. It will alter supply chains and help in making business more cost-effective. However, it also raises certain concern regarding the increase in inequality of income. Nevertheless, the ramification of the new technology for business organizations is mostly positive. Hence, it is necessary to understand how this technology will further transform business and communication in future.

The scope of the third revolution is so huge that its social and economic influences must be evaluated. As the way people communicate has changed drastically, it has become important for organisations to rethink their communication strategy. This paper outlines some of the socio-economic impacts of digital technology and its underlying implications for the next generation of marketing communication.

Background of the Fourth Industrial Revolution

What is the industrial revolution? This is the advent of new technology that changes the scope and speed of production, communication, and businesses drastically. This is a concept that ushers a rapid and fundamental change in society and the economy.

The first industrial revolution began in England at the beginning of the 18th century when there was the mechanisation of the production processes boosting industrial production using the power of steam power and the invention of the modern mechanised factories (see figure 1). This revolution shifted the production process from manual, labour driven enterprises to mechanised operations with the aid of water and steam.

The second industrial revolution at the beginning of the 20th century ushered in the moving assembly line of production, introduced by Ford motors which revolutionised factory production. The introduction of conveyor belts and mass production accelerated the production process (see figure 1). This increased the speed of production significantly enabling industries to produce similar products at a phenomenal speed. This reduced the cost of production and increased efficiency. The third industrial revolution began at the beginning of the 1970s brought in by digital technology (see figure 1).

Digitisation introduced applied electronics and information technology to the production process, which helped in mass customisation and additive manufacturing. The fourth industrial revolution is a concept of innovative technology, which is an upgrade of the third digitisation revolution (see figure 1). It is not only an extension of the third industrial revolution because the new age technology will change the velocity, scope, and system of the whole production process. The new technology brought in by the fourth industrial revolution will transform the entire process of production, business management and organizational structure. Schwab points out the fourth industrial evolution bring in the “transformation of entire systems of production, management, and governance.” (Schwab 2015, p. para. 3). The advent of artificial intelligence and the Internet of things are expected to change the economy and the way it works.

Evolution of the Industry, Source.
Figure 1: Evolution of the Industry, Source (Baweja et al. 2016).

The fourth industrial revolution is more of a data and information-based revolution rather than technology-based. The overabundance of information accumulated from the Internet and other sources has created this necessity to process these data to derive relevant results. The amount of the available data is so large that it cannot be analysed by the human brain and so it has become necessary to develop a mechanical brain that can analyse all the data available. Hence the development of the three most promising concepts of the fourth industrial revolution – Big Data, Internet of Things, and Artificial Intelligence.

Big Data

The new technology has brought in a deluge of information and data available to all, which has brought in the concept of big data. This is relevant to all kinds of subjects from finance and business to biological and environmental research. The International Data Corporation (IDC) predicts that by 2020 the digital world will increase exponentially by a factor of 300 that will increase it from 130 Exabyte to almost 40,000 Exabyte. The big data industry is increasing exponentially and will expand 20-fold in the next 10 years. Data is the most important thing for a business. Manufacturing industries are expected to store the maximum amount of data and they store consumer and operational information, which can help in future operations:

…in a consumer packaged goods company that produces a personal care product, a single machine alone generates 5000 data samples every 33 ms, resulting in four trillion (i.e., 4 Tera) samples per year. (Yin & Kaynak 2015, p. 143)

Big data is believed to play an important role in the fourth industrial revolution. It is expected that big data will be available in the fourth industrial revolution through Cyber-Physical System (CPS). The aim of the use of big data is to understand if the manufacturing plants can be made smarter which will help to produce intelligent products and will transmit the data as and when it is required. Therefore, it is expected to produce fault-free products and increase cost efficiency without affecting the quality of the produce. This will essentially help manufacturers to reduce the cost of production and assembly cost by almost 50%. Considerable reduction in working capital is also possible using big data.

The rise in online searches, social media posts and messages have helped the Internet giants to accumulate a large amount of data regarding people. Big data has been considered as a new kind of economic asset by the World Economic Forum held in 2012. It is expected that big data will be used in both corporate and government organizations. However, the scope of big data is not limited to business only. The plethora of data collected through the information age has shown an evident impact on other fields such as scientific research, public health, sports, advertising, and academics.

The overabundance of data is expected to accelerate the advancements in computing which will help in advancements in artificial intelligence through machine-learning algorithms. For instance, Siri, which is a talking application in Apple devices. Apple introduced it in 2010. People talk to the application and ask it questions and Siri replies to it based on all the information available to it through the Internet. Siri is increasingly becoming adept as a personal assistant program with more and more people asking it for help. Another example of usage of data is the police department in New York that uses computerized mapping analysis to find the “hot spots” of crime based on historical data of “arrest patterns, paydays, sporting events, rainfall, and holidays” (Lohr 2012, p. para. 17). Clearly, there is a general tendency to move towards a more data-centric analysis to predict future outcome. People will rely less on chance and take rationally analysed decisions based on the available information. This is expected to change the way people lived earlier.

The advantages of big data are enormous. Recent research shows that big data can increase customer-centric outcome by 49%, operation optimization by 18%, reduce the risk of financial management by 18%, increase the success of new business model by 14%, and employee collaboration by 4% (Yin & Kaynak 2015). Big data helps to accumulate information about the customers and analyse their preferences. Such customer analytics helps to understand the future behaviour of the customer and service them according to those predictions. Such analytics shows what kinds of functionalities the customer prefers and what kind of new functions they would accept. Further, this would also help in after-sales services as organizations can more proactively monitor the needs of the new customers and take preventive measures based on data analytics.

Clearly, business is becoming more intelligent with the help of big data. Business intelligence and analytics (BI&A) refers to the usage of the data set and analytical techniques of a large amount of data to predict outcomes. It is widely used for storage, management, and visualisation of a large amount of data. It has been adopted by major industries as it helps companies to store rationalised database provided by information technology vendors like IBM, Microsoft, SAP, and Oracle. BI technologies evolved through years of data collection and storage processes. The advent of the Internet, web-based content storage, mobile technology brought in e-commerce, e-governance, advancement in science and technology, and so on. These new technologies have brought in the next step in technology i.e. analytics of data available from various sources which are shown in the following figure.

Evolution of BI&A into futuristic data analytics.
Figure 2: Evolution of BI&A into futuristic data analytics, Source: (Chen, Chiang & Storey 2012).

Thus, the Internet is the key source for data collection for most processes. Several IT technologies such as high-speed network help to make this data revolution easier. The Internet was developed in the 1970s but it was not until 1990s that the World Wide Web gained large-scale adaptation. Since then, it has helped businesses to collect and generate data. Many by government, e-commerce, as well as health organizations have adopted the Big Data, which utilises all the information that has been accumulated since the advent of the Internet.

Thus, Big Data and BI&A helped developing one of the fastest-growing economies – the web and e-commerce industry. Leading Internet companies like Google, Amazon, and Facebook are dedicated to developing cloud computing, web analytics, and social media as these are supposed to provide great impetus for the future. Data from social media are captured through text and sentiment analysis, which helps to recommend a product based on the customer’s preference and mood.

Science and technology also utilize a large amount of data available for research and analysis. Scientific fields such as oceanography, astrophysics, environmental research, etc. have significantly benefited from the data-sharing program of the National Science Foundation (NSF). Many scientific fields have started using data analytics. One such field is biology that has utilized NSF data and cyberinfrastructure to develop iPlant, which is a collaborative effort to help students and academicians working in plant sciences. Similarly, Sloan Digital Sky Survey (SDSS) also helps to compute data about the position of the stars and helps to make decisions based on these accumulated historical data. In the medical and health industry, electronic health records help to access the medical record of the patient by medicine practitioners, which facilitates a deeper understanding of the patient’s medical history and complications. Security and public safety also have become a matter of serious concern for governments since 9/11. Big data helps to create analytics that helps to predict and stop the incidence of violence based on historical and real-time data available through the World Wide Web:

  • Development of advanced information technologies, systems, algorithms, and databases for security-related applications, through an integrated technological, organizational, and policy-based approach. (Chen, Chiang & Storey 2012, p. 1172)
  • Researchers have divided the bid data analytics for future into certain categories such as web analytics, network analytics, and mobile analytics. These will definitely help in the advancement of businesses in the future.

Internet of Things

Internet of Things (IoT) has been described as an “open and comprehensive network of intelligent objects” that helps in auto-organizing, sharing information, reacting to situations, and handling data without any external assistance (Madakam, Ramaswamy & Tripathi 2015, p. 165). It has been identified as one of the most promising Internet developments of the future. According to Gartner’s Hyper Cycle, the possible time it would take for the market to adopt this new technology was 5 to 10 years in 2012. The advent of a giant global network with self-computing and configuring capabilities creates both the physical and the virtual “Things” that have an identity (Xu, He & Li 2014, p. 2233).

The question that arises is how IoT works. IoT can be visualised as a global computational base with interconnected sensory, communication, information processing, and networking capabilities (Nolin & Olson 2016). One of the foundational technologies of IoT is RFID and WSN (Rifkin 2014). A significant advancement in both technologies contributes to the development of IoT. IoT has already started being used in logistics, retailing, manufacturing and pharmaceutical industries. The advancement in mobile phone technology such as increased usage of smartphones, wireless communication, and sensor technologies has had a large impact on the information communication and enterprise systems technologies (Jin et al. 2014).

Many governments have also invested in IoT. For example, the UK government has launched a £5 million project to develop IoT and it is expected that it would fetch a boost in industries £325 billion by 2030 (David 2017). The government’s investment in IoT is expected to boost industries and change the lives of people. Governments are investing in IoT in order to tap the potential of increasing economic growth and predict market situations in future with the help of this new technology which may help them not only to boost the market but also avoid financial pitfalls (Borgia 2014). Further, it also helps in predicting natural disasters and helps to save cities from such calamities (Tremaine & Tuberson 2017).

For businesses, IoT provides the platform to stay connected with customers and provide an unbeatable customer experience. Based on the information generated through the Internet of Things it is possible to reveal, organize, and uncover unique ways to influence customers and their purchasing trends (Ismail 2017). Therefore, IoT has the capability to boost the economic performance of companies and therefore improve the economy as a whole.

Artificial Intelligence

Artificial intelligence (AI) is technology is based on the premise of the development of an artificial brain that can improve and evolve on itself through a process of learning called machine learning. Thus, the machine will attain the ability to improve its knowledge and performance without human assistance (Singh, Okun & Jackson 2017). For instance, an AI has mastered the game of Go without human assistance. This is a huge step for science and technology as this technology helps to automate many tasks without constantly putting in commands for the same (Brynjolfsson & Mcafee 2017). AI can transform the way businesses are done. Many believe that AI has the capability to sustain a competitive advantage to businesses and help new business ventures. Many companies who have adopted AI have not been able to completely utilise its capabilities resulting in gaps. However, there are many companies who have successfully adopted AI have strong senior management support.

According to the research on AI and business’s adoption, the former is expected to have a huge impact on certain industries such as telecommunication, media, and technology (Columbus 2017). Further, the main functional areas in an AI-driven industry are expected to be the automation of marketing, support, information technology, and supply chain. However, the MIT Sloan report suggests that less than 39% of the companies who have adopted AI have a strategy in place to adopt this new technology (Ransbotham et al. 2017). The problem identified is that the new technology does not have complete access to the data. AIs learn through analytical data crunching. In most companies, the AI algorithms have been given full access to organization data that prevents the technology from learning more about the company’s business. The companies where AI has been successfully adopted have shown great appreciation for the need for the technology and have created a culture for development and learning for the system. AI is being used to develop customer service in many industries (Korzeniwoski 2017). It is believed once AI’s intelligence surpasses human learning and intelligence, the spread and adoption of AI will be much faster.

Big data, IoT, and AI are the three latest technologies that are expected to change the way business is done. The widespread adoption of these technologies by private and governmental organizations alike shows the ushering of a new age of technology and its widespread influence on people’s lives.

Impact on Media and Creative Industry

Socio-economic Impact

As businesses ride on the euphoria of a new technological revolution, scientists and business think tanks are less than enthusiastic about the new developments. The fourth industrial revolution promises to bring in greater automation in the production process with the aid of the Internet, robotics, and AI. This raises various concerns from the economic and social perspective. Jack Ma, the founder and visionary behind Alibaba, a Chinese e-commerce company, believes that AI will do more harm to humans as they become increasingly intelligent (Marks 2017). Renowned scientist and Noble prize winner Stephen Hawkins too has expressed his reservations regarding the advancements and adoption of AI (Griffin 2015). He points out that the real concern with AI is superior competence of the self-thinking robots. Clearly, the point Hawkins tries to make is that an AI will be more adept at attaining its goals due to its high intelligence and that will show that man is a less efficient performer.

However, AIs are being adopted for businesses in many industries. For instance, Elon Musk, the CEO of Tesla and SpaceX, points out that AIs pose an “existential threat to the human civilization” (Sulleyman 2017, p. para. 1) yet the company has continued to build its own AI for self-driven cars (Huddleston 2017). Airbus too has adopted AIs for its production of aeroplanes, which are expected to make their production system more efficient. Mathew Evans, the vice president of Airbus explains how AI will streamline the production process and make it more efficient. With the help of AI, companies will be able to look into the problems and take into account all the relevant and contextual information, which are then matched with the description of the problem at hand. After analysing this information, the employee on the floor will immediately be given an instruction regarding how this can be solved. Since, the Ai has all the information regarding the functioning of the unit, it has information from other sections of the plant which allows them to analyse all the previous data to come to a solution taking less time. Clearly, AI will help to solve problems speedily. Therefore, the adoption of new technology definitely has advantages but not without serious implications.

New Age Marketing and Communication

The new age of digital technology has immense implication for marketing and communication. The new era of business to consumer and business-to-business marketing is changing drastically. Conventional media marketing has lost its competitiveness over the digital marketing format such as through social media websites like Facebook or Twitter. Further, business-to-business marketing is done through digital platforms. The conventional forms of marketing are fast becoming out-dated. For instance, Google has acknowledged that its current search engine, which was the main source of its revenue earner, will soon become obsolete and they have to develop a new age, mobile-friendly engine that will be adept to cater to the needs of the new Internet.

Big data is definitely a very useful tool for next-generation customer-centric companies. How are these data collected? For instance, Facebook collects data from its users and analyses the “likes” of the demographic cohorts to adjudge the general trend of the people towards a particular product, politician, incident, etc. (Mosco 2015). Further, cloud computing stores a large amount of data on the Internet. Large tech companies like Google, Amazon, and Facebook are adopting robotics technology to increase their efficiency. For instance, Amazon uses it to optimize the speed of their delivery system. Governments too have started adopting robotics as they intend to automate warfare.


The fourth industrial revolution has the capacity to completely change the way people live. It has the potential to improve productivity and efficiency of manufacturing and services sector. Innovations like big data and AI have the capability to alter the way work is done today. Clearly, there are a lot of optimism as well as reservations regarding the fourth industrial revolution. There are concerns regarding the safety and existence of humanity as well as optimism about the economic benefits of the new technology. However, it can be unanimously agreed upon that the fourth industrial revolution provides many possibilities for developing marketing and communication of businesses.

Reference List

Baweja, B, Donovan, P, Haefele, M, Siddiqi, L & Smiles, S 2016, ‘Extreme automation and connectivity: the global, regional, and investment implications of the Fourth Industrial Revolution’, World Economic Forum Annual Meeting, Davos-Klosters, Switzerland, pp. 5-33.

Borgia, E 2014, ‘The Internet of Things vision: key features, applications and open issues’, Computer Communications, vol. 54, pp. 1-31.

Brynjolfsson, E & Mcafee, A 2017, , Web.

Chen, H, Chiang, RHL & Storey, VC 2012, ‘Business intelligence and analytics: from big data to big impact’, MIS Quarterly, vol. 36, no. 4, pp. 1165-1188.

Columbus, L 2017, , Web.

David, J 2017, , Web.

Griffin, A 2015, , Web.

Huddleston, TJ 2017, , Web.

Ismail, N 2017, How IoT is changing the game in the public sector, Web.

Jin, J, Gubbi, J, Marusic, S & Palaniswami, M 2014, ‘An information framework for creating a smart city through internet of things’, IEEE Internet of Things Journal, vol. 1, no. 2, pp. 112-121.

Korzeniwoski, P 2017, ‘Bots should be in your contact centre’s future: the technology emerges as businesses look to artificial intelligence to improve customer service’, CRM Magazine, May, pp. 28-32.

Lohr, S 2012, , Web.

Madakam, S, Ramaswamy, R & Tripathi, S 2015, ‘Internet of Things (IoT): a literature review’, Journal of Computer and Communications, vol. 3, pp. 164-173.

Marks, P 2017, ‘In the loop’, New Scientist, vol. 234, no. 3124, pp. 24-25.

Mosco, V 2015, , Web.

Nolin, J & Olson, N 2016, ‘The Internet of Things and convenience’, Internet Research, vol. 26, no. 2, pp. 360-376.

Ransbotham, S, Kiron, D, Gerbert, P & Reeves, M 2017, ‘Reshaping business with Artificial Intelligence’, MIT Sloan Management Review, 6 September, pp. 1-16.

Rifkin, J 2014, The zero marginal cost society: the internet of things, the collaborative commons, and the eclipse of capitalism, St. Martin’s Press, New York.

Schwab, K 2015,, Web.

Singh, S, Okun, A & Jackson, A 2017, ‘Learning to play Go from scratch’, pp. 336-337.

Sulleyman, A 2017, , Web.

Tremaine, K & Tuberson, K 2017, , Web.

Xu, LD, He, W & Li, S 2014, ‘Internet of Things in industries: a survey’, IEEE Transactions of Industrial Informatics, vol. 10, no. 4, pp. 2233-2243.

Yin, S & Kaynak, O 2015, ‘Big Data for modern industry: challenges and trends’, Proceedings of the IEEE, vol. 103, no. 2, pp. 143-146.

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