With an ever increasing volume of available information, how can one keep up and make use of it?
Information simply has to be accessible – gathering, managing and utilizing information is an inevitable part of running any modern business.
However, terms information, data and knowledge are often used interchangeably, thus, apart from being confused about each phrase, there is oftentimes much confusion around the definitions of BI and KM. This calls for quick explanation.
So, what is Business Intelligence (BI)?
Generally, BI is considered to be a set of tools and techniques applied to gather data and transform it into information that can be used in business analysis for the purposes of business development.
Every company gathers, collects, or to say more accurately, deals with a large amounts of data, including various business documents, emails, newspaper articles, web pages, reports, contracts, technical journals and reviews, spreadsheets, graphs and charts and other relevant sources of business data.
BI technologies usually deal with large amounts of unstructured data via the use of data warehousing and online analytical processing (OLAP).
All these data needs to be organized and validated – prepared for business analytics.
“BI is about providing the right data at the right time to the right people so that they can take the right decisions.” (Nic Smith)
And, what is Knowledge Management (KM)?
Knowledge Management can be defined in many ways as it spans many multi-disciplinary approaches – content management, collaboration, the science of organizational behavior, analyses like observation of trends and appearance of anomalies, clustering, classification, summarization, taxonomy building and so on.
This is probably one of the widely quoted definitions (Davenport, 1994), yet simple and to the point:
“Knowledge management is the process of capturing, distributing, and effectively using knowledge.”
KM refers to a set of techniques used to capture, share, and use the information available in order to achieve business objectives and to aid in business decision making based on business analytics.
There has been immense growth in the domain of knowledge management in the last decade and new applications and solutions that empower knowledge sharing and knowledge management have appeared.
Similarities and Differences between BI and KM
Confusion between these two technologies comes from the fact that they deal with many similar processes.
Both business intelligence and knowledge management capture, collect, organize, analyze and aggregate data in order to find the best solutions regarding business decision making processes.
Business intelligence goes as far back as the 19th century and the beginnings of entrepreneurship. and it has been developing steadily over many years.
BI enables organizations to integrate data across the enterprise, unlock the information and empower knowledge worker to make better (and faster) decisions – it focuses on explicit knowledge.
However, KM deals with the creation of new knowledge and the dispersion of existing knowledge throughout an organization – it encompasses both tacit and explicit knowledge, thus, we can say that KM can influence the very nature of business intelligence.
In very simple terms, knowledge management has developed as a way to make sense of the information collected via business intelligence and utilize it in the best possible way in business expansion.
“Knowledge management will never work until corporations realize it’s not about how you capture knowledge but how you create and leverage it.” Etienne Wenger
We could say that knowledge management draws on business intelligence in order to produce new knowledge, organize it into knowledge networks and utilize it for achieving specific goals.
But, these concepts promote decision-making, learning, and understanding:
“KM and BI, while differing, need to be considered together as necessarily integrated and mutually critical components in the management of intellectual capital.”
KM and BI use data to develop knowledge in order to empower better decision making.
In the knowledge-based economy, BI and KM are utilized to solve information glut and knowledge sharing, and although different, they interrelate.
Both information management technologies are developing and growing as it’s clear that there is an ever increasing need of businesses for useful information on which to base their decision making.
Techniques used in both BI and KM will eventually blend and merge in order to provide the best possible results, and even inspire new developments and avenues in information management technology.
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