Week One Topic Note
Welcome to Week 1
As we begin our discussion of Business Intelligence BI , we need to distinguish between an organization’s data, information, and knowledge. These three terms should not be used interchangeably, although they often are. We can then begin to understand what Business Intelligence (BI) is all about with a definition of BI, and an explanation of what it is and how it differs from other information technologies. We can then look at the factors that drive the importance of BI, and begin to look at how BI can impact an organization and its performance relative to other industry peers.
Definition of Business Intelligence
Sabherwal (2011) defines business intelligence as “providing decision makers with valuable information and knowledge by leveraging a variety of sources of data as well as structured and unstructured information”. As far back as people can remember, organizations (public as well as private) have been deluged with data. Older forms of data collection have been supplanted by new tools and techniques, in part due to the tremendous advancements of new technologies. These technologies have created huge opportunities in industries such as Healthcare, Defense, Telecommunications, and Government to mine and analyze this data for competitive advantage. Decreases in the costs of technology have made the large scale collection, analysis and storage of data affordable for organizations of all sizes.
In the competitive landscape that companies face, the organizations that have the greatest advantage will be those that leverage this new data to inform decisions on strategy, business processes, and operations. These tools and processes are collectively known as Business Intelligence (BI).
BI is the collection of ways that a business will make use of information to make their business decisions. BI is a broad term because it covers a wide range of applications, technologies, practices, processes and competencies that are used that help a company make informed decisions. BI technology, practices and applications are designed to gather and store data, analyze the data (create information) and then organize and compile the data (create knowledge) so that business decisions can be made based upon this new knowledge.
Business intelligence includes data mining (processing the raw data into information), querying the information and then the ability to produce reports based on this newly found knowledge. You do not have to be a big corporation to use business intelligence, as any company can benefit by using BI tools. Business Intelligence is only as good as the underlying data on which it is based. For this reason, companies are wise to have a Data Governance program in place to assure quality and integrity throughout the data lifecycle.
Turning Data into Information
We know from the Foundations of Data Science and Analytics course that the term “data” can be defined as “a collected set of raw and unprocessed items of information” (Bateman, 2014). The words “data” and “information” are often used as if they were synonyms. For our purposes, they have very different meanings. Based on this, we can look at data as a raw material; one from which you can create information.
Information “is a set of processed data items that collectively provides descriptive attributes about a person, place, or thing”. (Bateman, 2014) It can therefore be said that information is the result of combining, comparing, and performing calculations on raw data.
To summarize the example used in the Foundations Course:
Student Enrollment Data is input into the Student Registration System. From this we can create a Class Roll (information). We can also produce reports of average scores and other documents or Information.
So we’ll think of data as raw materials, observable and recordable facts that are often found in operational systems. Data has value to end users when it is organized and presented as information.
Turning Information into Knowledge
There have been many books written on how companies can take the information they have gleaned from their vast stores of data, and turn this information into actionable knowledge. This is really the key focus of Business Intelligence. For our purposes, we can assume that successful companies use their inherent systems, experiences, and preferences to select content and material that they have collected, now called information, and add their unique analysis, interpretations, and presentations to that content and material, creating value without having to create new material themselves. This is the generation of knowledge. This knowledge is a corporate asset, and can help to distinguish the company in the marketplace, whatever that may be. The challenge is deciding which of all that information is actually valuable, and extracting that value. That’s where a company’s unique combination of experience and skill becomes important. Because each company is different, the same information can be used differently, and will be as valuable in the marketplace as the marketplace will decide it to be. This is the basis for competitive advantage, which is what Business Intelligence is designed to deliver.
Factors that Drive Business Intelligence
Beyond the need or desire for competitive advantage, BI is driven by internal and external factors. In our Week 1 reading, Sabherwal (2011) mentions a few. Further research will I am sure turn up more, depending on the industry selected.
External factors driving organizations towards BI include market volatility (markets with quickly changing customer demands and/or quickly changing goods), and legal requirements (some companies are under restrictions by law to be able to deliver certain sorts of reports to external entities).
Internal factors driving organizations towards BI include large volumes of data, information overload, or the need for a “single version of the truth” (many times companies find that different reports that supposedly show the same information show different results). The size of the organization can also drive the need for change, as larger organizations can usually better justify the expense of developing a BI process.
The Value of Business Intelligence
Business Intelligence capabilities help organizations manage and access both structured and unstructured data, providing the ability to empower decision makers, improve organizational effectiveness, and enable IT efficiency.
Business Intelligence has the ability to create, access, and share information, which allows users to discover and manage various aspects of the business, easily find and work with structured and unstructured information, and share information with others.
Business Intelligence helps to improve organizational effectiveness, by allowing access to the right information when it is needed. Users should be able to manage and define organizational resources by aligning to key metrics and strategy with a single version of the truth, provide access to the right information to the right people at the right time, and enable users to find the right information across all data sources and content types.
Business Intelligence depends on the ability to create and maintain an infrastructure to effectively drive the information to all users, ensuring performance and increased reliability of system management tools and features.
Business Intelligence solutions provide managers
the ability to more effectively use the large volumes of gathered data and
information, making decisions that incorporate important factors based on both
structured and unstructured sources of information.
References:
Sabherwal, L. (2011). Business intelligence: Practices, technologies, and management, New York, NY: Wiley and Son
Bateman, L. (2014). “Foundations of Data Science and Analytics”, Topic Note One, MA., Brandeis University.
Business Intelligence BI and Knowledge Management are management concepts which are quite similar in that both of them capture, collect, organize, analyze and aggregate data. The similarity of the two has led to confusion by many. A survey by OTR consultancy established that even consultants (60 percent) do not understand the difference between the two. (Hameed, 2004) This paper looks at the fundamental difference between Business Intelligence BI and Knowledge Management.
Differences between Business Intelligence and Knowledge Management
First, Business Intelligence BI is the process by which data is turned into information which is then used in the business analysis to develop the business. This process is facilitated by several collaborative and analytical applications and tools which collect the information into one warehouse. On the other hand, Knowledge Management is a step by step process that finds, selects, organizes, distils and presents information in ways that improve the working experience of the employees. In essence, KM technologies and application search through a firm’s spreadsheets, databases, reports, journals and web documents to give value to the information contained in them. This difference shows that for BI works with the assumption that there exists a data warehouse, KM, on the other hand, does not make this assumption. (Eckerson, 1991)
Moreover, Business Intelligence deals with specific data. It utilizes already available information to make better decisions. As such, it does not create any new information; rather it gathers already available information which it utilizes in decision making. This is different from Knowledge Management, which focuses on the creation of new information which is then dispersed to all employees in an organization. (Herschel & Jones, 2005)
Further, Business Intelligence technologies and software do not integrate non-quantitative or non-relational data in its warehouses. The modeling, reporting function, and analysis applications solely rely on numeric data stored in the warehouse. This is in contrast to Knowledge Management, which utilizes both quantitative and qualitative data. Qualitative data here includes the knowledge possessed by the employees of a company. This gives KM an edge over BI since at any given time, 80% of the information in a given business entity is qualitative data. There exists too much verbal and documented information which is useful but since it has not been turned into quantitative data is not utilized during decision making. (Herschel R. , 2008)
Conclusion
In conclusion, differentiating Business Intelligence from Knowledge Management KM is not easy since their core functions are always overlapping. The success of any business entity lies in the way that the management and employees can best integrate the two concepts to achieve the goals and objectives of the firm.
References
Eckerson, W. (1991, February 1). BI vs. Knowledge Management. Retrieved May 18, 2016, from Information Managaement: http://www.information-management.com/issues/19990201/177-1.html
Hameed, I. (2004). Knowledge management and business intelligence: what is the difference? Retrieved 2016, from onlinebusiness: http://onlinebusiness.about.com/
Herschel, R. (2008, June 10). Knowledge Management and Business Intelligence. Retrieved May 18, 2016, from BeyeNETWORK: http://www.b-eye-network.com/view/7621
Herschel, R., & Jones, N. (2005). Knowledge management and business intelligence: the importance of integration. Journal of Knowledge Management, 9(4), 45-55.