Although data-driven digital transformation projects involve the risk of failure, they can be successfully concluded with the right process management. Therefore, the business should learn what it can gain with a data-driven system and feel the need for it.
So, we should first understand what Data-Driven Systems are or are not. Data-Driven System can be defined as a collection of analysis systems that stores data in all processes of the business included in this system and transforms it into meaningful information that the business needs in the decision-making process (using third-party data sources).
As can be understood from its definition, a Data-Driven System consists of the combination of one or multiple systems. Data-Driven Systems do not make the decisions for you but offer capabilities that will enable you to compare/analyze various scenarios in the decision-making process.
Data-Driven Systems can be integrated into all business processes and can be used as a model for Company Management. The business must be ready/willing to the process of making a decision by analyzing, and it should perceive its "environment" well to adopt this system.
Before the industrial revolution, it was enough for a business owner to be successful in understanding the needs of only the immediate "environment" it operated. The said environment here represents an area of no more than a few hundred km². If there is a demand for shoes in this region and you can produce shoes, it will be enough for you to be successful. There is no pressure on you due to the new model, competitor, or price.
After the industrial revolution, the "environment" concept expanded from a few hundred km² to several thousand km² with the development of transportation. It was no longer enough just to know the demands of your town. You also had to ask yourself the question of what the neighboring town demanded and worried if a competitor in the neighboring town produced more novel, better, or cheaper shoes than you.
Over time, the environment has evolved from town to city, from city to country, and today to the whole world. While a shoe manufacturer produced only one model of shoes in its lifetime before the industrial revolution, shoe manufacturers have to design shoes for a few seasons, carry out research for them, find resources for research and production, and perhaps create new markets to survive among the competitors.
Before the industrial revolution, the shoe manufacturer knew everything about his profession and could handle all his trade by keeping a ledger. But today, everything has been changing rapidly. A business that wants to survive in today's world needs to be aware of the whole world and be able to act dynamically in the face of changes.
In the internet age, businesses may sometimes have more information about their own businesses than the most important companies in their sectors. They can be instantly informed about what the biggest companies in their sectors do in the market, mergers, new products, or investments thanks to social media or other news sources.
By combining this wide data network with their own data, some businesses can have much better analysis processes and decision-making mechanisms.
In order to survive in the shrunken new world order, being content with only the data of your business will unfortunately not be sufficient for long-term success. You should compare your data with the data of your close competitors, even with your entire industry, make simulations about the results of different scenarios, and store the results of the decisions you make at the end of all these analyses in your corporate memory.
Data-Driven Systems will provide you with these opportunities. If you have not begun yet, it is time to start a data-driven change process in your business to survive in this world where those who can turn data into information get stronger.
