The Role of Data in Business Transformation

Data allows organizations, governments, and enterprises to visualize relationships between what is happening in different locations, departments, and systems. Nowadays, the most gifted organizations to collect, use and interpret data are the GAFA (Google, Apple, Facebook, Amazon) and the BATX (Baidu, Alibaba, Tencent, Xiaomi). The data collected has made it possible to create new business models and create new jobs, such as the professions of Data Scientist, Data Engineers and Data Analysts, which did not exist a few years ago.

To set the scene and have a first overview of the question, the first figures to consider are those of the evolution of the volume of data generated by companies in the world, in zettabytes. According to the IDC Worldwide Global Datasphere Forecast 2020 – 2025, this is an impressive volume since it will be multiplied by 3 between 2020 and 2025, going from 36 Zo to 122 Zo. Remember that a zettabyte is equal to 10 to the power of 21 bytes and that in 1999, humanity had generated only 1.5 exabytes of data that year, (10 to the power of 18 bytes for an exabyte). One thing is clear: the progression is exponential.

According to forecasts by the firm IDC, the revenues generated by the data sector in the world amount to USD 189 billion – an upward trend that could be confirmed by 2022 and reach USD 274 billion. Geographically, the market remains dominated by the United States (USD 100 billion), ahead of Europe (40), Japan (9.6) and the United Kingdom (9.2).

The European Future Enterprise Resilience Survey 2021, a study carried out among more than 150 companies with at least 500 employees, demonstrates an ever-increasing awareness and attention to data analysis. For 61% of these companies, data analysis is one of the technology investment priorities for the next two years. It represents a “very high priority” for 20% of them and a “quite high” priority for 41%.

But what is data?

The usual definition of data is the quantities, characters, or symbols on which operations are performed by a computer, which may be stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media. I personally prefer Jensen's 1950 definition of data: The story should have retained capere, or "capture" in French. Indeed, for science, it is a question of selecting, of capturing in the existing rather than understanding the data as something previously “given.” This historical difference highlights the selective and partial character inherent in the data.

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Data: generator of new business models

Since the dawn of time, being informed first has been a decisive advantage, whether in politics or in war. Obviously, the more the information is relevant in relation to the context, the more the advantage of the one who holds it is pushed. This has never been truer as we carry on in a digital era, which is accelerating trends. Since the Covid-19 pandemic, we have seen that this is still true in all areas, especially since the validity time for information has been considerably shortened – what was relevant the day before is no longer necessarily so the next day.

Today, the elementary data used to develop information is produced in very large numbers, unlike previous eras, and can no longer be processed by the same methods. To be exploited, the initial data must be transformed into digital code, which initially makes it commonplace. To give it meaning, humans must contextualize and interpret it. Then the data takes on its full value and becomes relevant.

But how can brands use data to elevate the customer experience and become more efficient?

Developed countries are organized around data, whether to manage businesses, the economy or understand user needs. In the digital age, the ability to collect and transport data at very high speed has led to the development of means and methods of operation that are different from those we were forced to use just a few years ago. And the key ingredient to finding the full potential of data is focusing on the consumer. We can leverage data to better understand the human on the other side of technology, and brands can use these insights to create personalized experiences for their customers – increasing sales, improving efficiencies, and securing brand loyalty.

In a recent discussion on data management, Chandra Mostov connected with Salesforce to consider humanizing data algorithms. He says, “The most sophisticated brands in the world, if you measure them by skills of human interaction, wouldn’t even be in kindergarten. They would get kicked out the door for not listening, not learning, not respecting – for thinking it’s all about them.” As the world pivots to become increasingly digitized, brands must adapt to better understand their customers. Just as humans can understand each other’s needs on a personal level, brands must leverage data to do the same. Personalization drives performance through trust, leading to a more efficient and profitable customer journey.

For instance, Big Tech companies have made it their specialty to meet customer needs and to improve the customer experience and build loyalty. Amazon is the perfect example! Amazon has an in-depth knowledge of customer desires and needs through the collection of research from its customers. Amazon can anticipate that a customer is expecting a baby, and therefore offer them additional goods based on their purchases or searches. The effect on the customer is powerful because we meet their needs by providing an unparalleled user experience and facilitate the purchasing action even before it is needed.

Some technology companies are helping companies leverage this data to turn it into a source of revenue. Salesforce and Amazon Web Services (AWS) have decided to evolve their partnership to facilitate data sharing and the creation of applications.

Salesforce will allow developers to use Amazon data on its platform without having to code it manually. “Whether you work with Amazon or otherwise, we will make the data appear as native data on the platform,” Salesforce said in a statement .

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Why is data termed the “new oil” in the 21st century?

Like oil, data is valuable, but if it's not cleaned and refined, it can't really be used. Oil must be transformed to create value to be exploited. As a result, does the data need to be broken down and analyzed for it to have value?

According to Peter Sondergaard, former global head of Research at Gartner, information is the oil of the 21st century, and analytics is the combustion engine. Data overtook oil as the world's most valuable asset. The individual data has become a valuable asset. Some key opinion leaders say the individual should be responsible for this personal property.

Are we at the dawn of a new business model generated with the development of personal data as an asset? At the end of 2021, China decided to create a data exchange market in Shanghai with the goal of putting data into the hands of entrepreneurs who can use it most efficiently. One thing is certain: the 4th Industrial Revolution is being driven by data.