Knowledge and Its Attributes by Clyde W. Holsapple

1. Knowledge and Its Attributesby Clyde W. Holsapple Presented by Eric Havens, Sanusha Matthews, and Mike Copciac

2. Asking Webster • Knowledge- the range of one’s information or understanding • Information- knowledge obtained from investigation, study, or instruction..also defined as facts, data. • Data-factual information used as a basis for discussion • So that leaves us with: Knowledge is a range of information, information is knowledge, information is data, and data is information. Useful definitions?

3. Knowledge as Usable Representations A representation is an arrangement in time/space Ex. words in a conversation, diagrams, photographs, etc. Newell says knowledge cannot so easily be seen, only imagined as the result of interpretive processes operating on symbolic expressions. This suggests that knowledge doesn’t exist outside of the processor that perceives or has a representation that it finds to be usable.

4. Knowledge as a Progression of States • Variations in the usability of a representation(depending on processor, task, environment, etc) • Six states of Knowledge proposed by Van Lohuizen 1)Decision 2)Judgement 3)Insight 4)Structured Information 5)Information 6)Data

5. Fundamental notions with Knowledge as a Progression of States 1)States of Knowledge exist 2) These states form a progression from the lowest level, where usability is marginal or potenitla to higher levels where usability is clearer or more immediate. 3) Knowledge States are subject to change through various kinds of processes

6. Production Perspective • Views knowledge as existing in stocks and flows. • Stock-an inventory of knowledge available to one or more processors • Two main types of flows: • Knowledge transferrable from one stock to another • Knowledge flow from a stock into itself Old Knowledge New Knowledge ∑x n

7. Knowledge Versus Information Perspective • Views knowledge as a state in its own right, as something beyond information. • The states used earlier (data, information, etc) are viewed as precursors to knowledge. Data is turned into information and information is turned into knowledge.

8. A note on the various perspectives • These perspectives aren’t exhaustive, but can help us be familiar with some of the more common ones. • Also, it may be obvious that certain authors are taken a given perspective while sometimes it may not be so apparent.

9. Knowledge and technology • 1990s rise of knowledge management as a prominent field of practice, research, and study coincided with tremendous advances in computing and communication technology. • There are two extreme for the relationship between technology and knowledge management • Knowledge management has nothing to do with technology • Knowledge management is all about technology

10. Technology is incidental • Knowledge is defined as uniquely human, which exist in the context of human interpretation and processing. Technology has no role at all in knowledge management. • But if technology is eliminated, then knowledge management has the following loses • Knowledge would flow via face to face meetings, physical bulletin boards, hardcopy reports and memos, surface mail, fax telephone conversation, and so forth; but groupware, email, electronic forums, computer mediated communications, workflow systems, and computer supported cooperative work would be of little relevance to knowledge work.

11. Technology is incidental • Knowledge repositories would include pieces of paper, briefing books, filing cabinets, traditional libraries, and memories; but digital documents, databases, web pages, and software libraries would not have a role in KM. • Knowledge generation would be performed by human mind power, with the aid of pencil and paper; but solvers or spreadsheets for deriving forecast, expectations, and analyses would be out-of-bounds; rule sets, case bases, and reference engines for deriving advice would be out-of-bounds; data mining, text mining, and automated pattern recognition for knowledge discovery would be out-of-bounds. • Technological means for acquiring and selecting knowledge-search engines, web crawlers, intelligent agents- would be of little importance to knowledge workers.

12. Technology is everything • Another view is encompassing the lower states of information and data or seeing computer based processors as capable of interpretation and processing • However if humans are eliminated then knowledge management has the following loses. • Knowledge management could not have predated the advent of computer based technology, but this would ignore the long history of organizations struggling to achieve value from knowledge assets. • Technology would become an end in and of itself, without attention to its consequences. • Technology vendors would become the primary sources for KM solutions.

13. Technology is everything • Technology would become the starting point and driver of KM initiatives, instead of basing KM efforts on human traits and capabilities, coupled with organizational objectives. • KM initiatives would concentrate on explicit knowledge, leaving the tacit mode of knowledge largely unattended. • People would be seen as supporting the technology, instead of technology enabling, supplementing, complementing, or amplifying human knowledge processing abilities.

14. Middle path • Another path of knowledge management can be concerned with including people, technology, organization and the fits among them • We can focus on the representation that computer based processors can utilize in accomplishing various task. The specifics on such processors and how they can be devised, improved and managed to support and facilitate the human dimension of knowledge management

15. Computer based technology as a servant of knowledge management • One way the CBT has transformed life and organization is by transforming how knowledge work is done. CBT is concerned with digital means of representation and processing knowledge • CBT has transformed how individuals and organization accomplish knowledge works by amplifying complimenting leveraging and improving human knowledge handling capabilities. • CBT progressed from data processing systems(1950-1960) to management information system(1960-1970) to decision support system(1970-1990) to organizational computing system(1980-1990) to ubiquitous computing(1990)

16. Computer based technology as a servant of knowledge management • Technology from a knowledge perceptive triumphs in its ability to connect more people in more ways than ever before, example email, intranet, discussion forums, chat rooms etc. • CBT is increasingly becoming all about knowledge management • CBT researchers are knowledge management researchers whether they recognize it or not. • There are opportunities for research that improves on current CBT for • Enabling and facilitating knowledge flows among knowledge processors(human and computer based)

17. Computer based technology as a servant of knowledge management • Supporting and performing knowledge manipulation tasks . • Assisting in the measurement, control, coordination, and leadership of knowledge and knowledge processors. • Helping ensure that the right knowledge gets to the right processors in the right formats at the right times and at the right cost. • To advance the field of business computing, we need to better understand the users and usage of CBT in knowledge management. • What works and under what condition does it work? • What does not work and why? • What CBT advances and breakthroughs are needed? • How do we cultivate” good” fits between technological infrastructure on one hand and organizational infrastructure on the other hand in knowledge based organizations?

18. Computer based technology as a servant of knowledge management • To advance the business computing field, we need to study outcomes of using CBT in knowledge management • What are its competitive impacts? • How can CBT be used to implement a knowledge chain activity? • Or, in a more targeted vein, how can CBT be used to enhance productivity, agility, or reputation as a means for competitive advantage?

19. Knowledge Attributes • Each instance of knowledge has a point in space • Defines what type of processors can operate • Determines of processing that can be subjected to • Knowledge characteristics • Mode – Tacit vs. Explicit • Type – Descriptive vs. Procedure vs. Reasoning • Domain / Orientation – • Subject or broad domain • Relational or Relative or Self-knowledge orientation • Applicability / Management / Usage

20. Knowledge Attributes cont’d • Applicability / Management / Usage • Local or global applicability • Operational or Management or Strategic planning control • Professional or Improvement uses • Accessibility / Utility • Privately or publicly accessible – or in between • Levels of usefulness defines utility • Clarity • Meaning • Relevance • Importance

21. Knowledge Attributes cont’d • Validity / Proficiency / Source • Accuracy or consistency or confidence determines validity • Degree of expertise defines proficiency • Origin of knowledge • Temporal – attributes dependent on time • Immediacy, Age, Perishability, Volatility

22. Conclusion • Knowledge Management • Multidisciplinary field with substantial opportunity • Relatively new field with multiple viewpoints & perspectives • Attributes are all potential areas of research