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The value of a data-driven strategy to boost competitiveness and growth

A large part of our business fabric is at an early stage in the development of a data-driven strategy, which is conditioning its competitiveness, especially in the global market. Placing the value of data at the center of business strategy is a learning process that companies can and should apply to reinvent themselves and create new business opportunities.


Byte TI Magazine - Editorial Team

July 26, 2022

https://revistabyte.es/actualidad-it/estrategia-basada-en-datos/

Since the beginning of the last decade, when access to high-performance computing became affordable, a two-pronged race for a data-driven strategy has begun: that of generation and that of exploitation.


The former has to do with the production of a continuous flow of information from the sources, i.e., the activity of customers during the consumption of products and the use of services. For example, financial transactions such as the buying and selling of securities on the stock exchange, or the banking operations of individuals.


The second element, exploitation, concerns the development of algorithms based on the analysis of source data. In the financial example, machine learning models make it possible to build algorithms for the identification of fraudulent transactions, or the detection of risks of non-payment of loans. Also, the detection of "good customers" to whom loans are granted without a prior solvency study, since the bank has already done so on the basis of the data available to it.


Barriers to growth: technology and human resources

Data generation and exploitation have been and continue to be two handicaps not only for growth, but also for the survival of many companies.


Generation is relatively simple compared to the latter, within the complexity of setting up a scalable IT infrastructure for a growing number of clients.


However, exploitation imposes a whole series of requirements to be able to put it into practice. The first of these is the collection of data in a structured way, something that has to be done from the generation stage, as the data is received from the sources.


The second requirement is to have qualified personnel, the analysts, specialized in information processing. Together with the data engineers, they design the recommendation algorithms, sales projections, etc. And also the dashboards for decision making in the companies' boards of directors.


Survival and competitiveness

From this perspective, there are several challenges for companies, small and large, new and well-established. One of them is that of survival, due to the rapid change in business models driven by digital.

In a data-driven strategy, exploitation imposes a whole series of requirements to be able to implement it.

The second is not only to maintain, but also to increase competitiveness in the face of new players that are building their infrastructures based on the Big Data and Cloud Computing paradigm. These new companies are much more agile because of their ability to immediately adopt new technologies, while existing ones have to face the cost of reconversion and recycling, which affects both the technological infrastructure and the training of human resources.


Big Data to the rescue

Facing this situation means designing a data-driven strategy that is capable of exploiting the large volume of information generated by customers.


Big Data arose from the moment when the technology became available to squeeze data in real time. The origin lies in the exponential increase in computing capacity: much more powerful computers at much lower prices. In computer jargon, this behavior is due to the well-known Moore's law, according to which computing capacity doubles every 2 years for the same cost of computing resources. This has been happening for fifty years, and we know that it will continue for at least ten more.


This means that in the last two decades the capacity of computers and laptops has multiplied by more than 1000 times without the need to increase the economic investment, which has finally given the SME and small business sector the opportunity to compete at the level of the big ones.


The reality is that a large part of our business fabric is at an early stage in the development of a data-driven strategy, which is conditioning its competitiveness, especially in the global market. The emergence of the new generation of companies derived from the startup model is the one that is driving the rapid renewal of the business fabric. It is a model that allows rapid growth with a small economic investment. And this is not only because of the use of technology, but also because they have placed the value of data at the center of business strategy.


This is a lesson that pre-existing companies can and should apply to reinvent themselves and create new business opportunities.

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