From data management to knowledge management
You might be wondering what the difference is between knowledge management and data management. Nowadays business information, through which knowledge is later generated, is mostly based on data. However, data is not information and information is not knowledge.
Data is the material used to produce knowledge. If data is not supported by management processes such as data management and data governance, and business intelligence processes such as data analysis or corporate reporting, it will never become knowledge.
While years ago companies based their data strategy on data collection, the focus has now shifted to the production of intelligence through data. Why? The quality of business decisions no longer depends on the quantity of data, but on how it is leveraged.
This is why companies are focusing on knowledge management, because data management only means managing data. Your data is well managed. Good. But are you doing with it?
What is the use of managing data if you are not leveraging its use? What is the use of data if we do not transform it into knowledge?
Let’s think about it this way. No one doubts that the success of a business depends on the talent of its employees. Companies need talent to operate. Well, employees’ talent produces, among other things, knowledge. If this knowledge, once generated, is thrown away, it is obviously of no use.
Knowledge management is the strategy that allows companies to not throw their employees’ knowledge away. A good knowledge management strategy leads to better business results, as it fosters continuous learning, collaboration and informed decision making at all levels of the organization. Knowledge leverage is also useful for optimizing business processes, operations and routines.
Data management is part of knowledge management, but managing knowledge is a step further.
Knowledge management does not end with databases, data integration or an ETL process. Knowledge management is a global strategy that starts with data collection and ends with data-driven decision making, through corporate information systems and data analysis, BI and data visualization tools such as Power BI.
How to transform data into knowledge?
Transforming data into information and information into knowledge requires a process that involves multiple disciplines. At Bismart we are experts in the implementation and development of all the micro-processes, sciences and operations necessary to transform data into business value.
The importance of knowledge management
As for the importance of knowledge management, data speaks for itself. Despite the fact that companies are producing more data than ever before, most companies are still not data-driven. Specifically, according to recent research, 62.2% of companies have not yet managed to implement a data-driven culture.
Companies have data. In fact, they have the data they need. But more than half of them are not taking advantage of it.
Data analysts spend 50-80% of their working hours preparing data before they can start transform it into knowledge. This leads us to think that, in many corporations, not even the part of managing data properly is covered, let alone knowledge management.
In a nutshell
Data management is the first step and knowledge management is the strategy that companies need to leverage the collective intelligence they produce and transform it into operational efficiency, better decisions and profitable long-term strategies.