What is knowledge management and why are so many companies opting for this approach? Learn how to transform your data into knowledge.
The increasing adoption of hybrid work has accelerated the digitization of business operations, as well as the relevance of the execution of management processes that encourage effectiveness to face new challenges. In this context, businesses are focusing on knowledge management.
The visible impact of Covid-19 on work routines has materialized in the adoption of a hybrid work model that, in turn, has forced organizations around the world to take a step towards the digitization of processes, routines and tasks. Productivity, collaborative work and access to information are positioned as cornerstones in this new scenario.
In the aftermath of the pandemic, technology has definitely stormed into companies without waiting in the hall, jumping over all barriers and forcing companies to optimize their processes through integration and automation.
Digitization and hybrid work have also increased the amount of data produced by companies, now growing a 40% per year. In addition to having more data assets, data is also being generated in more formats than before and stored in more places. Data is now being transformed by more employees and stored in multiple data warehouses as well as documents such as Excel, Word, PowerPoint, PDF, digital platforms, etc.
In most cases these files are unstructured, which makes them difficult to access and reuse, which devaluates their value and quality.
In a previous article in this blog we reflected on the relationship between the quality of business decisions and data quality, reiterating the importance of data management. However, the speed at which business digitalization is advancing leaves us in a scenario in which companies' approach is evolving from data management to knowledge management.
What is knowledge management (KM)?
While the name being fairly self-explanatory, let's take IBM's definition to delve a little deeper into the role of knowledge management (KM) in the business environment: "Knowledge management (KM) is the process of identifying, organizing, storing and disseminating information within an organization. When knowledge is not easily accessible within an organization, it can be incredibly costly to a business as valuable time is spent seeking out relevant information versus completing outcome-focused tasks."
As stated, knowledge management is linked to profitability and revenue. Knowledge is the basis of any activity and, in the business ecosystem, the generation and use of knowledge is a must for growth. Without knowledge, managers cannot make the right decisions and, therefore, they will not be able to guide the business towards expansion.
Knowledge management is a strategy for leveraging the generation of collective intelligence to optimize the company's operational efficiency.
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.