Nowadays I often see managers talking about Business Intelligence, Data mining and big data like the best thing in the world, and when they open their laptops, they still manage companies in their excel sheets and refer to big data as an excel file with 10MB and Business Intelligence as being creating charts with lots of colors. When I look at them and hear their strategies for information management in their companies I imagine a blind person trying to solve the rubiks cube.
The lack of decision support systems knowledge by many contemporary managers makes them believe that the way they support their decision is most accurate, however there are nowadays many computerized decision support systems with distinct characteristics that oblige these same managers to know which is the best solution for their companies.
The emergence of systems and technologies such as Business Intelligence and Data Mining brought new ways to provide relevant information for decision-makers and new techniques of knowledge discovery. These systems will collect and structure data generated by the organization, in its normal operational activities, like electronic invoices generated in a normal sale, and transform it into management information such as aggregated sales summaries that can be analyzed in several perspectives, like the aggregated sales summaries by store, by date or even by product. They allow managers to analyze their companies in the perspective they want and in the granularity they expect because you can look at the data into more detail like the sales summary by store or have an overview on the sales summary by country. And then comes data mining, allowing managers to make predictions on their business like for instance predict the sales for the next year based on the sales of the last 5 years of activity. More even, data mining allow you to apply techniques that make customer clustering one click away, so that you can manage your marketing actions by customer profile.
These same systems provide organizations with new business models based on information generated by the operational activities of the organization itself, making decision making a custom operation and not something based on the average companies behavior. Your company is not like any other, the people are different, the markets are different and all of that must be taken in consideration.
Although these new technologies for data analysis are a better response to data collecting and management, they not only involve the professionals of information technology but also forces managers to learn a new culture of organizational decision based on the facts. when the volume of data stored by organizations is so large that managers no longer know what to do with maybe its time to learn new skills and management styles to align the business with their decisions.