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TopIntroduction
There has been very little written in recent years about Chief Knowledge Officers (CKOs). A Web search for the term can elicit a definition of the term and much less frequently, a job description at a particular organization.
Margaret Rouse (2008) provides this definition of a CKO at techtarget.com:
Chief Knowledge Officer (CKO) is a corporate title for the person responsible for overseeing knowledge management within an organization. The CKO position is related to, but broader than, the CIO position. The CKO's job is to ensure that the company profits from the effective use of knowledge resources. Investments in knowledge may include employees, processes and intellectual property; a CKO can help an organization maximize the return on investment (ROI) on those investments.
The FBI’s Web site provides an illustration of a CKO’s job responsibilities:
The CKO’s focus is on how people, systems, and technologies exchange data, information, and content to meet the Bureau’s goals and objectives. The Knowledge Office collaborates with other FBI components to maintain a knowledge management program that creates, captures, and shares timely, reliable, and actionable knowledge. As CKO, he specializes in cultural and business process change management and is responsible for a number of technological and collaborative improvements, programs, and platforms to share knowledge and expertise. (FBI, 2013)
If Web search results are any indication, the viability and visibility of CKOs has diminished over time. Academic research about the concept seems passé and there appears to be little indication in surveying today’s literature that the concept is still promoted as an essential organizational component for sharing information and expanding intellectual capital.
This seems unfortunate to me because there is now probably more need for a CKO than ever before. Today there are two critical issues that organizations must address: Big Data and business intelligence (BI). Big Data is a term that is used to describe the fact that the amount of data in our world has been exploding, and analyzing large data sets—so-called big data—will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus (McKinsey Global Institute, 2011). Business intelligence (BI) is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and organizational performance (Gartner IT Glossary, 2013). With the rise of BI and Big Data, there are urgent and critical organizational needs for intellectual brainpower with honed analytical skills, swift decision-making capabilities, and effective and strategic data management. All of these activities are related to knowledge creation. As a result, the position of CKO only has to be recast in the context of BI to understand its utility and value for today’s organizations. To understand why this needs to be done, we should understand the relationship of BI and knowledge management and how the former contributes to the latter.
TopBackground
Many confuse knowledge management (KM) with business intelligence (BI). According to a survey by OTR consultancy (http://www.otr-ict.com/solutions/consultancy.html), 60% of consultants did not understand the difference between the two terms To clarify the disparity, Herschel and Jones (2005) state that business intelligence is any technology that is used by organizations to gather and analyze data to improve decision-making. In business intelligence, they assert, information is often defined as the discovery and explanation of hidden, inherent, and decision-relevant contexts in large amounts of business and economic data.
Alternatively, KM is the systematic process of finding, selecting, organizing, distilling and presenting information in a way that improves an employee's comprehension in a specific area of interest. Knowledge management is said to help an organization to gain insight and understanding from its own experience. Specific knowledge management activities help focus the organization on acquiring, storing and utilizing knowledge for such things as problem solving, dynamic learning, strategic planning and decision making.
Key Terms in this Chapter
Tacit Knowledge: Knowledge that is not codified and difficult to diffuse. It is hard to verbalize because it is expressed through action-based skills and cannot be reduced to rules and recipes.
Business Intelligence (BI): A business management term which refers to applications and technologies which are used to gather, provide access to, and analyze data and information about their company operations.
Data Mining: Sometimes called data or knowledge discovery, data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified.
Intellectual Capital: The value of a company or organization's employee knowledge, business training and any proprietary data or information that may provide the company with a competitive advantage. Intellectual capital is considered an asset, and can broadly be defined as the collection of all informational resources a company has at its disposal that can be used to drive profits, gain new customers, create new products, or otherwise improve the business.
Explicit Knowledge: Knowledge that can be expressed formally using a system of symbols, and can therefore be easily communicated or diffused. It is either object based or rule based.
Big Data: A business management term that refers to applications and technologies that are used to gather, provide access to, and analyze data and information about their company operations.
Knowledge Management: A program for managing a firm’s intellectual capital by systematically capturing, storing, sharing, and disseminating the firm’s explicit and tacit knowledge.