1. Knowledge Work Systems
MIS 2000
Class 12
Knowledge Processes &
Knowledge Work Systems
Updated Oct. 2013

2. Outline Knowledge worker Knowledge & Knowledge Kinds
Knowledge Life Process
Knowledge Works Systems (KWS)
Organizational culture and knowledge (knowledge culture)
Summary

3. Knowledge and Occupations
Knowledge worker is a professional that intensely applies (uses) domain knowledge at work and/or generates it.
In contrast,
clerk mostly processes data (collection, formatting entering in forms or IS, running IS)
manager mostly interprets documents (infers information from documents)
Manipulate/
process data
Interprets documents and
analysis to draw
information
Apply knowledge on solving biz problem
Produce biz documents
Create analysis,
research
Clerk
Manager
Professional

4. Knowledge
KNOWLEDGE
CONCEPTS,
RELATIONS
PROCEDURES
CAUSE-EFFECT is
Knowledge refers to understanding what something is, why something is, and how to do something:
- What: concepts, concepts’ relationships, taxonomies
- Know-how (procedures): How-to do something,
analysis/synthesis, how to generate new knowledge
- Why: understanding cause-effect relationships (special relationship)
Knowledge acquisition is
incremental (what comes in
layers, & why is learned with
imperfect accuracy).
Learner may start with know-how
and understand what/why later.
Knowledge is never complete,
or 100% correct, can be
incoherent and controversial
(messy).

5. Three Knowledge Taxonomies
Source view:* Theoretical (science, theories) vs.
Experiential knowledge (practical, personal, via doing)
Communication view:**
Explicit
Can be communicated
Definitions, taxonomies, theories,
procedures, cases
Tacit
Difficult to communicate
Experiential, analysis & synthesis skills
Mgt. goal to extract it
*Theoretical vs. Experiential knowledge:
Theoretical knowledge you get for the most part in the school. Experiential knowledge you learn on the job
by solving work problems and learning from others who have relevant experience. Theoretical knowledge is easier
to represent in information systems and pre- electronic storage (books, etc.) than experiential knowledge because
the former is expressed in more formalized vocabulary (text, drawings, formulas), that is, it is more codified.
Explicit vs. Tacit knowledge:
Most of theoretical knowledge is explicit, while most of experiential knowledge is tacit. A person may learn
theoretical knowledge and then adjust it and blend personal experiential knowledge into a form that is
very subjective and even unique. This becomes tacit knowledge as the person uses it intuitively, without
thinking about its content or use procedures. In developing KWS, a major challenge is to uncover tacit knowledge (e.g., Expert Systems). Interest of management is to transform tacit knowledge into explicit, which may collide
with interest of knowledge owners (employees).
***Human Capital vs. Structural Capital
Human Capital: Knowledge in employees’ mind, memory.
Structural Capital:
Knowledge representations in documents and IS (patents, problem
solving descriptions – different documents than reports; Accenture
case)
Proprietary organizational methods
Knowledge embedded in various technologies, production floor design, and in products
Human capital includes both explicit and tacit knowledge, as well as theoretical and experiential knowledge. Group
effects are important – what do people know, or how do people do job as employees of a particular company or its unit.
In companies that manage well knowledge, a good part of structural capital is represented in KWS. Management challenge is to integrate human capital with structural.
Economic view: Human Capital (in people) vs.
Structural Capital (in things) *

6. Knowledge Life Process
Knowledge life process refers to a sequence of activities from knowledge generation to discarding.* The process in an infinite loop.
*Also known as knowledge management.
Generating of knowledge happens in every organization, as individual learning (via problem solving or acquisition of theoretical knowledge) or team-based learning (e.g., in project teams working on new problems or developing a new product).
Larger organizations that depend on new knowledge have specialized units for generating new knowledge—Research & Development (R+D) departments; examples are pharmaceutical, petro-chemical, automobile, aircraft, and various engineering industries (mechanical, electrical, nano-technology, etc.). KWS can solve new problems and store solutions for future use. This resembles the learning process.
Codifying of knowledge means representing knowledge in forms that communicates to others. This could be in forms of text (patent descriptions, problem solving procedures), numerical figures (analysis of market trends), formulas (engineering documents, scientific discoveries), graphics (business analysis), video (problem solving procedures), etc.
Validation means checking for quality of knowledge, such as accuracy, usefulness, and the relationships with previous knowledge and organizational goals. For example, when scotch tape was discovered at 3M, validation showed that the concept of new glue could results in a useful product, although it did not fit with the traditional line of the company's strong adhesives.
Once created, representations of knowledge need to be stored. This is a classical role for knowledge work systems (KWS), like Document Management System or Wikis today. Storage characteristics depend on the form of knowledge codification (e.g., textual descriptions cannot be appropriately stored in a relational database but in a full-text database).
Sharing of knowledge refers to diffusion of knowledge and learning by organizational members. This step usually increases the value of new knowledge for a company. Disseminating knowledge documents to designated persons is a common method. Textual expression of knowledge can also be broadcast, as by blogs. Another method is by managing access to KWS - designated persons are given access privileges. Next method is corporate instruction, which can take place in specialized instructional facilities (learning centers). Finally, teamwork is a very good methods of learning by doing and communicating intensely between knowledgeable persons and learners.
Utilizing of knowledge is the process of implementing knowledge at work. For example, an engineer uses a newly invented procedure to
solve a problem at hand. Through this process an organization draws economic value from new knowledge.
The Evaluate Knowledge step is as important as its generation. From time to time, knowledge used at work needs to be evaluated and then a decision with regard to updates or discarding is to be made. Obsolete knowledge can lead to mistakes and loss in business. Think of problems that Nokia and RIM, cell phone producers, have in 2010s because they did not update their market and product knowledge.
Successful companies can become victims of their own success because they do not update and discard knowledge that once led them
to success. After the evaluation step, professionals and management in charge decide whether existing knowledge is to be used,
updated (upgraded) or entirely discarded.

7. Knowledge Work Systems (KWS)
Generate
Codify
& Store
Share
Update
Document Management System
yes
Communication System
Case Based Reasoning System (CBRS)
Expert System (ES)
Artificial Neural Network System (ANNS)
KWS in support to knowledge sub-processes:
- Generate: KWS help people in creating knowledge
- Codify: KWS codify or people do it
- Store: classical role for KWS is to store representations of
knowledge
- Share: deployment of KWS for disseminating of knowledge
- Update: modify based on what is newly learned

8. KWS: Document Management System
Document Management System (DMS)* = Repository of documents that codify knowledge in some way. In typology of GSS, DMS is called File Sharing System.
The simplest kind of KWS, consisting of multi-format storage and a searchable index.**
Used in corporate learning centers, and by individuals and groups in their regular job.
Examples: Lotus Notes (was one of first in the market), SharePoint, wikis, open source.
Technically: full text databases with retrieval tools (SharePoint), and functions for group-authoring (wikis).
Content of documenting systems is shared among people authorized to access them (e.g., consulting firms).
*Sometimes also called Content Management System since some software products have
functions for organizing and indexing documents named that way. But the term can be confusing
because software for filling in Web pages is also called Content Management.
**Document storage is organized (e.g., in categories of documents) and indexed for easy search (e.g., content descriptors like key words, problems for which knowledge is generated and applied to, dates, etc.).

9. KWS: Case-Based Reasoning System
(descriptions of problems,
prob. solving processes, and solutions
User
Interface
Index
Case-Based Reasoning (CBR): Represents knowledge as cases – descriptions of problems with solutions (like in law).
Procedure of using CBR system involves user’s input of keywords and the system’s search for the best fit between the input and documents that may help in solving the user’s problem. New knowledge may also result from using CBR system.*
CBS systems are used in help desks, conflict resolution, professional problem solving that cannot be reduced to if-then rules, instructional systems (teaching how to do something – procedural knowledge).
*Procedure of using CBR system:
User inputs keywords describing a problem
CBS matches input with the index terms
CBS searches the Case Base for similar problems; the closest fitting case is the preliminary solution
User modifies case with new details and stores it back in case base (new knowledge acquired, old knowledge updated).
Step 2 is critical and it is performed by the Index module of the system. This module is more powerful than an index used in Document Management Systems. It does not perform just matching of inputted words and index terms (full and partial matching), but it can also make decisions on a similarity of these two (so
called similarity matrix).
Note that step 4 implies new learning.
Mhmmm… an interesting case, indeed!

10. Creates decision trees out of
Expert System
User
Interface
Inference Engine
Creates decision trees out of
rules in K-Base and
user’s input
Knowledge Base
If-then rules
representing
expert knowledge
KWS that codifies the expertise of people in the form of if-then rules.
Benefit: Expert knowledge shared with non-experts.
Used in account auditing, medical diagnosing, troubleshooting of machinery, health care (Medical underwriting system at Blue Cross), financial industry (CLUES system for loan underwriting), oil & mining
More on expert systems...

11. Artificial Neural Network (ANN) System
ANN System simulates human brain’s cells (neurons) and connections
Connection patterns get created, which allows ANN System to make some inferences.
The inferences are represented in form of graphics, numerical figures, text, etc. This resembles human knowledge
ANN with 3 layers of “neurons”
APPLE
COMP-
UTER
FRUIT
Hidden layer strengthens its connections with APPLE and COMPUTER and not between
COMPUTER and FRUIT.
COMP.
Artificial Neural Network (ANN) System simulates human brain: computer’s memory locations resemble brain cells (neurons), and connections among the memory locations resemble connections among neurons (synapses). The memory cells store pieces of relevant content that represent a whole. For example, one cell stores the word “apple, ” another “fruit,” and the third “company”.
ANN System can learn on is own or be trained to establish appropriate connections when processing inputted text (“apple ” and “fruit” versus “apple” and “company”). ANN System is able to “understand” if a piece of text is about apple fruit or Apple company. In addition to processing text, application of ANN are in recognizing various patterns as in traffic control, machinery functioning, financial markets, physical objects (visual functions of robots), and state of health/illness.
ANN software is used today even in computers for home users, such as tablet PCs (writing recognition) and laptops (speech recognition). For example, a computer can recognize letter “A” even if it is not written completely.

12. Organizational Culture and Knowledge
It is important that cultural beliefs and behaviors facilitate activities included in the knowledge life process.
Beliefs and behaviors related to knowledge at Accenture:
Beliefs & practices on generation & sharing of knowledge: Knowledge should be continually created through consulting practice and shared broadly.
Beliefs on role of knowledge in business: knowledge should contribute directly to profit objectives.
Assumptions about purpose KWS*: To enable storing and efficient access to knowledge content.
*Accenture is a large, global consulting company that supports its operations via a document management system called Knowledge Exchange System (KES). KES is supposed to serve as “organizational memory” of the knowledge created and used by Accenture consultants. Also, to enable quality knowledge-intensive work (use of the existing, creation of new knowledge) of the consultants.
Organization members are active contributors and users of KES.
It is also maintained at Accenture, that KWS should be changed when knowledge processes do not deliver expected value in terms of sharing knowledge among consultants. At one point in the company history, there were many locations at which new knowledge was created. Sharing of this knowledge was increasingly difficult because of the standards for knowledge codification were missing (different indexing schemes used by different consultants before recording new knowledge in the old KWS.

13. Knowledge Culture
Knowledge Culture – organizational culture that systematically supports the entire knowledge management cycle. May not exist in every company or it can exist in various degrees.
May be facilitated by teams. Important in knowledge creation and particularly sharing. Sharing via collaboration (between equals) and apprenticeship (master and student relationship).
Examples: Accenture, 3M, Microsoft, Apple

14. Summary
Knowledge worker is a professional that intensely applies/generates knowledge at work.
Knowledge refers to understanding what something is, why something is, and how to do something. Develops gradually and is never perfect.
Knowledge kinds: Theoretical & practical; explicit & implicit; memorized & materialized.
Knowledge mgt. process is cyclical and includes generation, codifying/storing, sharing, utilizing, & updating/discarding.
Knowledge works systems (KWS) studied are Artificial Neural Network, Document Management System, Expert System, & Case-Based Reasoning System. They support different phases of knowledge process (slide 7).
Any company should pay attention to managing knowledge. Knowledge culture exists in a company that systematically supports entire knowledge management process (e.g., Accenture).