Knowledge Management Introduction

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Knowledge Management: From Concept to Decision

ThoughtPrinter^Ž Gisting Tool

tewLabs' challenge: to capture the informal, collaborative process; to extract Intellectual-Capital (I.C.) Data Sets from document work products; to identify the thought stream of the contributor; to reconfigure thought streams and Knowledge Units to the user's point-of-view; to create knowledge as a dynamic commodity with usefulness in more than one way; to provide intuitive options for users to create relevance that the back-end architect cannot imagine; to create synergistic exchange; to model honest, creative dissonance; to create compromise with multiple perspectives; to gist thought.

What We can do for Your Company Now:

Overview of the Technology
Objectives
Sample Statement of Work

Overview of the Technology: tewLabs' Knowledge Management

(U.S. Patent No. 5,721,938)

Text search in its current stage of development, operates from the Latin paradigm of single words having single meanings. For English with multiple meanings of words, the current engines produce a frustratingly high return of searched words but not the relevant meaning that the user seeks. Moving past the word-centric paradigm, tewLabs uses fixed-word order to gist for thought-centric language strings adding to and deepening, not eliminating, existing data storage mechanisms and engines.

The gisting process allows the user to organize data into chunks of thought while simultaneously determining both "what is a thought" and where in the thought a word occurs. The substantive relevance of "where," i.e., the placement, greatly affects meaning which, however, only the user can determine.

For example, "Russia invaded Hungary" has different import from "Hungary invaded Russia." The human being, the user, decides or "gists" the meaning. In other words, the key question is "relevant to what?" Tapping into the relational data base of English, the user becomes the architect of thought, girding data sets into new or newly related information strings. The user creates the appropriate relevance tailored to a vertical market (or lay reader) beyond assigned word attributes, canned phrases or pre-determined weighted criteria.

The engine offers the user options, beyond his or her own immediate or preferred perspective, to think about and decide what affect a word, a context pattern, or an information string creates, based upon where it is placed in the thought stream.

Currently in the field, broad categories exist for vertical markets wherein potential combinations of thought have prescribed limits which cannot anticipate every possible use. Despite the benefit of specificity for a vertical market, this delimited approach has created inadvertent problems in the Knowledge-Management area. tewLabs' engine proposes the mechanism to anticipate unlimited choices of combined meanings for the user to choose. To do so, tewLabs' engine provides 1) back-end triggers and algorithms for word order, and 2) front-end intuitive data sorting within the architecture of the binary structure of thought. In other words, tewLabs' engine has identified the architectural elements common to thought while assigning the architectural combinations for meanings, prompted by dialogue triggers and binary placements, to the user.

tewLabs' engine offers an economy for streamlining the collaborative flow of informal Knowledge Management by object-sorting linguistic context strings. It further enhances how the data base deals with categorizing words with a further level of syntactic analysis. The user can limit the retrieval of a given word's meaning, not just literal return of the word. Further, the user can also govern the flow and substantive meaning of words in their context.

As a Fifth Generation Language, tewLabs' engine provides both high-level natural-language sorting as well as perspective options to the user with low-level machine language efficiency, portability, and legacy-system bridging. With efficient routing to relevant language strings in data-base text repositories, tewLabs proposes capturing the Intellectual Capital warehoused as tagged data or indexed categories. Thereby the harnessed power of warehoused data can transmute ephemeral and currently illusive processes into commodities. The informal collaborative process captured becomes Intellectual Capital. The captured Intellectual Capital becomes a pathway for future decisions with reusable Intellectual Capital Data Strings.

Achievable Objectives:

Utilize tewLabs' patented system to identify organizational communications styles as those styles influence the type of information gathered
Identify all of the ThoughtPrint^Ž patterns for anyone who inputs information into warehouse data or the collective data gathered
Identify communications barriers which prevent the most efficient exchange of information
Provide tools to gist thought beyond tagged terms and topical indexing
Prompt multiple points-of-view and alternate perspectives beyond pre-determined criteria, weighted analysis and scoring in a pre-scripted environment
Provide unlimited relational knowledge-units to engender intuitive data insights, usefulness, and efficiency, from either a detailed or an image perspective
To harness usefulness for otherwise unconnected data and to provide "50,000-foot snapshots" for metasystematic bridges

Intellectual Capital Data Sets (I.C. Data Sets)

Read and store the context default of all work-product document sentencing
Divide each work product into context word strings with tewLabs' patented context identification software
Use the context recognition tools to prevent communication barriers
Use the defaulted four context-pattern snapshots of each document for seeking housed substantive meaning beyond vocabulary word-tagging and indexed phrases
Create the process for creative problem-solving for any communications search
Activate living tools from the thought process to recognize, understand, and bridge varying points-of-view
Design intuitive dialogue triggers as the pathway for accessing multiple perspectives
Gain the ability to think in more than one way by adapting to varying contexts
Enhance existing data sets, query sets, indexed topical data bases, and data warehousing with an access tool which quantifies the thinking process beyond scripts

Knowledge Units

Identify the context strings in English word-order, providing the I.C. Data Sets within a document work product or the thought processes of the document authors
Use these I.C. Data Sets to assess the knowledge gathered and inputted in work products
Encourage users to flip the I.C. Data Sets into alternative knowledge strings, prompted by context usefulness
Prompt the user beyond "one and the same" pre-scripted criteria and sequence of operations which do not change under all encountered circumstances
Provide the user the means to choose or create a different sequence of actions, as required, to meet unforeseeable circumstances
Create back-end entry flexibility where the same constants, parameters and variables can be altered by the front-end user in any sequence relevant to that user
Create objectivity for maximum usefulness of knowledge streams
Create the ability to "bring the context into the deciding moments" as concepts become concrete direction
Enhance each individual's contribution to the decision-making process, the product, and the collaboration
Collect the historical stream of the informal collaborative process, as it occurs, to store in a permanently useful, retrievable set of Knowledge Units with the ability for multiple relational combinations
Help collaborators create action plans based on such knowledge-unit streams

Actualizing the Informal Collaborative Process

Model a positive, creative dissonance to draw upon multiple divergent points-of-view
Create living tools for seeking multiple perspectives and business solutions which guarantee mutual respect and open-mindedness throughout teams and networks
Create on-going dialogues to mine current mindsets as a treasury of divergent insights
Provide flexible tools for creating new mindsets
Utilize the divergent processes of thought in the organization for a dynamic and on-going approach to change management which real people can use immediately and intuitively
Create the dynamic for a wholesome organization which utilizes a set of tools to actualize empathy and rapport on a daily basis as a business tool
Gather research data, both "hard" and measurable "soft" perceptual data
Identify metrics useful to measure progress with these objectives
Provide leadership with the data to better actualize the Intellectual Capital mined by this process

Using Warehouse Data and Customer Service Business Applications

Use dialogue triggers as the means for opposing viewpoints to reach compromise or negotiated truce
Provide tools to perceive how a product impacts the client
Create a model which becomes an on-going process for creative problem-solving which significantly shortens the collaborative process while simultaneously maximizing the captured collaborative idea formation
Create living tools to recognize, understand, invite, and co-ordinate varying points-of-view
Design the I.C. Data Sets and Knowledge Units for permanent future access and usefulness for any unforeseen future project
Prevent duplication of efforts
Create ubiquitous global access to cross-organization ideas and information
Reduce collected data to four simple context vaults
Promote synergy with honest, creative dissonance
Uncover hidden Intellectual Capital

Sample Statement of Work

Phase I: Problem Assessment

Identify thought patterns for a given Work Group

Match the ThoughtPrint^Ž inventories to work-product writing: identify common Intellectual-Capital Data Sets

Map assessed ThoughtPrints^Ž with thought patterns in the work products for the organization

Identify strategies to reduce communications barriers on-line and organizationally

Capture Intellectual-Capital strengths within any grouped division of the company

Coordinate identified strengths and needed strategies

Phase II: Solutions

Assess Sample documents from a data base to illustrate I.C. Data Sets

Compare assessment to topical indexing and word tagging repositories

Bridge legacy systems and integrate ThoughtPrinter^Ž as a knowledge management tool

Find what context pattern contains most heavily weighted word tagging and indexing retrieval

Phase III

Extracting Intellectual Capital

Model prototype for feedback

Compare query sets to results gathered from Phases I and II

Identify added value for indexing data in context patterns

Add dialogue triggers and intuitive context relationships to query sets

Phase IV

Bridging Legacy Systems

Test Prototype

Capture the informal, collaborative evolution from idea to design

Phase V

Implementation and Portability

Identify contingencies, "what-ifs," next steps

Measure accumulated change