Download Towards an understanding of KM tools and portals: From research to

Towards an understanding of KM tools and portals: From research to applications*
Eric Tsui
Computer Sciences Corporation & University of Technology, Sydney
Abstract
With a plethora of KM tools and portals products on the market, it is increasing necessary to define a
framework to categorise, better appreciate the power of these tools and to relate them to common types of
KM applications. This article defines such a framework. By identifying the dominant fields of KM and
Artificial Intelligence (AI) research, it is possible to develop a broader perspective of the applicable
technologies available for KM. Criteria for the evaluation of tools and portals as well as future challenges are
also outlined.
Knowledge Management Research
People have disparate interpretations of the term Knowledge Management. While there is still no one
universally accepted definition for KM, the general consensus is that to tackle knowledge management well,
contributions from, among others, diversified areas spanning management, human resources, decision
science, marketing, artificial intelligence and knowledge modelling are needed. By tracking relevant academic
publications in these fields, three dominant streams of research into Knowledge Management can be
identified:
The first stream focusses primarily on research into the theory of knowledge, the knowledge of the firm,
organisational culture, measurement of intellectual capital and learning organisations. These researchers tackle
the theoretical aspects of knowledge management, develop models for valuing intellectual capital. Some
researchers even challenge Nonaka and Takeuchi’s framework for the socialisation and externalisation of
knowledge.
The second stream is represented by the work on corporate memories (aka organisational memory and
organisational memory information systems) for enhanced decision making. A corporate memory embraces
all forms of institutional knowledge, whether formally encoded within the current information systems, or
tacit (informal) knowledge used by individuals in professional practice. This group has a strong focus on
knowledge sharing and on practical applications of knowledge management in a corporate-wide perspective.
The third stream, with a strong contribution from computer scientists and artificial intelligence (AI)
researchers in particular, tackles the areas of intelligent agents, ontologies (taxonomies), data mining,
knowledge modelling, and computer-mediated collaborations.
Categorisation of KM tools
Especially so for the third stream, all the above research have, spawned the development of tools for
supporting various knowledge processes e.g. capturing, encoding, organising, searching, distributing and
measuring. The product of using these tools (and more) to develop an application is a (technical) KM system.
Generally speaking, a KM system is any computer system that integrates various knowledge processes in one
or more organistions to solve specific business problems. In a wider sense, the objectives of developing and
deploying a KM system are
1. Capture, create and share knowledge assets
*
Published in Knowledge Management, Vol. 4, No. 2, October, 2000.
2.
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Locate relevant information knowledge
Provide an environment for knowledge exchange
Connect people with relevant interest and/or skills
Facilitate intelligent problem solving
One can perceive from the above objectives that, the field of AI, among other areas, has a strong influence
on the evolution of KM tools (hence applications). After nearly three decades of research, many of the
relatively more mature techniques in AI have been packaged into commercial products. (One should also
note that back in the 80s and 90s, large organisations invested considerably into the development of expert
systems. These systems are usually problem solving in nature and are highly focussed in a restricted domain.
As a result, a great deal of decision-making knowledge has been acquired and represented in rules and/or
decision tables.) The following categorisation of KM tools, challenges and their respective trend are
increasingly becoming evident in the market:
Intelligent Search - By far, the majority of tools offer search capabilities. Search can range from simple
keyword match, attribute-based input to context-sensitive search (i.e. taking into consideration what the user’s
interest, role type, and the very activities he or she is conducting just prior to issuing the search). Some tools
also make extensive use of a word taxonomy or an ontology (which can either be manually created or
automatically discovered with user guidance) to navigate the search space so that results are contained and are
highly aligned to the user's need(s). More sophisticated tools are emerging and these will, progressively,
incorporate collaborative filtering techniques. That is, one can issue a goal statement (instead of keywords) to
the search engine that translates the goal to a list of specific search probes. Collaborative filtering also allow
search patterns, ideas and results to be shared (& reused) among a group of interested parties. One of the
challenges in conducting searches is to properly synergise the result gathered from inside as well as external to
an organisation.
Process Modelling & Mind Mapping - These tools provide a visual environment for ideas to be captured
and shared. Business processes can also be defined and modelled. Such tools greatly the conceptualisation of
procedural and factual knowledge. However, nearly all the tools in this category are stand-alone products.
There are two key challenges to future tools in this category. Firstly, the ability to automate the conversion of
the defined business processes to operable business objects for simulation allowing versatile questions to be
posed. Secondly, set operations (e.g. join, expand, contract, superimpose, conflict resolution etc.) of concept
maps need to be defined. For instance, there is no reason why email messages, which is mostly text in nature,
cannot be replaced in future by concept or knowledge maps so that knowledge workers can define and
communicate visual information in synchronisation with a pre-defined corporate framework.
Case-Based Reasoning (CBR) - CBR is an AI technique that enables past cases (i.e. problems and
solutions), with appropriate modifications, to be reused for unseen cases. Many CBR systems have been
developed for the help desk, software development and CRM applications. With the increasing popularity of
Customer Knowledge Management, CBR tools will remain a dominant AI technique in the KM arena. On
the research side, the relationship and synergy between CBR and Organisational Memory are actively being
studied.
Data & Text Mining - This category of tools, which enables meaningful patterns and associations of data
(words & phrases) to be identified from one or more large databases, has been around for more than a
decade. They form part of a KM solution as many developers and researchers consider data & text mining to
be a type of "micro" knowledge strategies (as opposed to Knowledge Program Management as a suite of
"macro" knowledge strategies) for an organisation. Data & text mining systems are being used extensively in
business intelligence, direct marketing and customer relationship management applications. As most
organisations only have a small group of data miners, it is doubtful that data & text mining tools, though
undoubtedly will remain a strong technical component, will be accessed via a enterprise wide corporate portal.
In the near future, such tools will be gradually aligned with other tools to support key tasks in the above types
of applications (e.g. from data gathering to data mining, encoding of business rules, capturing of decision
making criteria, matching of customer profiles to product services, campaign management and the
incorporation of feedback).
Web Crawler - These are Web-based tools that facilitate intelligent searching with extensive use of meta-data
and indexing. Data is not limited to texts and numerals but often in multimedia i.e. voice, graphics, video etc.
A common characteristics of Web crawler tools is the ability to place "hooks" on numerous locations on the
Web, monitor the content and activities on these pages and notify the user once there is change of content at
those locations. Among others applications, such tools are especially suited for performing research on the
Web and gathering competitive intelligence.
Groupware - The two most dominant platforms are Intranet and Lotus Notes. Detail compare and contrast
of these two platforms has been widely reported and is not the focus of this article. While the intranet
concept is extremely popular, generally more economical and compatible with nearly all of the tools on the
market, Raven, the latest entrant from Lotus, has a very unique feature. By tracking user interest (and
expertise), Raven assists in the location of relevant information as well as connecting certain employees in an
organisation. Intelligent features like this and others will continue to be introduced by product vendors to
gain differentiation and competitive advantage over their competitors.
Measurement & Reporting - Some organisations tackle KM with a strong human resources focus and
device criteria to measure the benefits of their KM program. Tools are now available to measure, track and
report on the value of intellectual capital (i.e. non-financial assets) in an organisation. Most noticeably, these
tools are based on the Balanced Scorecard method or the Intellectual Asset Monitor (ICM). Tools on tracking
and reporting professional development, online self-paced learning, and performance reviews for employees
are also available.
The above categorisation of tools is functional and techniques-based. Other categorisations also exist. For
example, the Delphi Goup's classification of KM tools extends to cover Enterprise Resource Planning (ERP),
Electronic Document Management (EDM) and Information & Aggregration tools. IDC separates KM
software into two groups: Infrastructure and access software. KM infrastructure software is the base or
platform upon which KM solutions are deployed. Access software operates on the KM infrastructure to
provide (groups of) individuals with access to (internal and external) knowledge repositories. Through
fundamental research, Computer Sciences Corporation (CSC) has developed the KM Spectrum which maps
KM systems into the following six categories:
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Transactional
Analytical
Asset Management
Process
Innovation & Creation
Developmental (i.e. learning)
As a general observation of the KM tools on the market, they are powerful & fast in search and dissemination
of knowledge (i.e. documents and links). Some tools can cope with multi-modal information and most tools
can handle files stored in various formats and in a range of platforms. Tools are especially appealing to
technical users and, on many occasions, have spearheaded the early adoption of a technical KM system in an
organisation. However, this can also be a disadvantage for two reasons. Firstly, organisations should always
define its KM strategies (or principles) before any tool is adopted (even though a particular tool is considered
to be a good "technical fit" to the problem on hand). Secondly, as in all acquisitions, organisations should
always critically assess the "buy versus build" proposition. Other shortfalls in KM tools are
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Can be tedious to configure - integration with legacy systems and operational databases has been reported
as a key implementation issue
No one tool supports the full spectrum of KM processes
Poor in structuring knowledge & virtually nothing in understanding - most tools can only generate
indices to facilitate subsequent retrieval. As an intelligent system, information or knowledge needs to be
processed and understood. Natural language understanding techniques have yet to be incorporated into
the commercial tools.
No support for knowledge reuse - Another consequence of the above reason is that knowledge cannot be
re-organised and re-applied to a different problem. This capability, if available, is a key contributor to
product and process innovation.
One of the key arguments for the last three shortfalls is that efforts should be directed towards developing
advanced search engines rather than focus on trying to understand and classify knowledge in documents.
Two justifications are that corporate knowledge management is different from personal knowledge
management (where human tends to classify things and store them with a view to locate them easily) and that
one cannot predict the future usage of a piece of information hence it is pointless to think about creating an
index for it without knowing how it will be used in the future. On the second point, artificial intelligence has
long shown that indexing, representing and searching knowledge are intrinsically related. Furthermore, to be
effective, an index has to be purposeful, general and predictive.
Irrespective of the "buy versus build" decision, here are some useful criteria to apply when performing an
overall evaluation of a KM tool:
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Power of the search engine (e.g. intelligent search, collaborative filtering, efficiency)
Flexibility and ease in browsing & availability of visualisation tools
Automatic classification (using a taxonomy/ontology) of documents
Collaboration & Personalisation features
Active collection & distribution of knowledge (i.e. knowledge pump)
Repository for Document Management
Ability to handle multiple file formats, media & technical platforms
Cater for Personal KM as well as Corporate KM
Capture operational statistics & provide analytical tools
Extent & ease of accessing external sources
Portals
While KM tools have been around for years, it is the concept of an Enterprise Information Portal (EIP) that
has gained immense popularity among business leaders in the last 12 months. Portals are seen as a one-stop
entry point for staff, customers and partners to access and share information, to perform transaction(s), and
to carry out specific work tasks. Portals are popular primarily because of the advance in e-Business models
(e.g. cyber-stores, vertical integrators, net markets, volume procurement etc.) and Customer Relationship
Management (CRM) (e.g. customer knowledge management, measurement of relationship capital and direct
marketing). E-Business has also impacted KM by gradually transitioning it from an internal focus (i.e. a
corporate program) to an external focus (i.e. addressing the flow of knowledge between/among suppliers and
customers). As a result, many KM tool vendors have re-positioned their product offerings to align with portal
market (e.g. commerce/trading, information, procurement, collaboration and learning portals). However, it is
important to understand that the fundamental technologies underpinning the composition and hosting of
portals remain predominantly the same.
Based on the above discussion on KM tools and taking into consideration of the forecasts by the Delphi
Group and Gartner Group on portals, one can anticipate the following stages in increased sophistication in
future portals:
Stage 1
Simple search mechanism & standard (static) page delivery
Information dissemination point
Stage 2
Core content with pre-defined variations in page delivery
Expanding set of interactive & informative facilities
Centralised search facility for organisational content
Engagement of common business processes
Stage 3
Advanced search facilities and seamless integration of search results (external & internal)
Simple expertise locater
Online Knowledge Communities
Customers can initiate & check transactions
Ability to perform transactions with suppliers and partners
Stage 4
Extensive and dynamic personalisation of content for individuals
Active collection and distribution of knowledge
Full integration with e-Business systems
Decision support and problem solving capabilities
Some of the technical challenges to future portals are Web-access to enterprise application systems, automatic
categorisation of all corporate resources and assets, intelligent & multiple search strategies (e.g. interactive &
offline search, sharing of search cues and results), and real-time user profiling and personalisation strategies.
Developing KM Applications
Though not definitive, there are two major approaches to developing KM applications – process and product. A
process-based approach (or ‘personalisation’) treats KM as a social communication process. The emphasis is on
the deployment of an environment/framework (whether technical or not) to foster better exchange of
knowledge among staff and other participants. On the other hand, a product-based approach (or ‘codification’)
focusses on the collection, storage and distribution of institutional knowledge for reuse. Ideally speaking,
under the product-based approach, organisational knowledge is retained by a corporate memory (CM) and
the memory is an active one (i.e. both in collection and distribution). A review of the reported KM
applications has identified the following “tools of trade” (or ‘gadgets’) adopted by organisations embracing
KM:
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Cultural change
Knowledge Maps
Ontologies/Taxonomies
Corporate Memory
Expertise directory (aka People finder system)
Online learning & performance tracking system
Groupware (supporting online discussions and workflow e.g. Lotus Notes, Intranets)
Authoring & content management tool
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Specialised (Web-oriented) search & categorisation tools
Data Mining system
Information repositories e.g. Documents databases, Electronic Document Management Systems (EDMS)
Readers should note that the above tools are not mutually exclusive and organisations often adopt a
combination of the above to tackle a particular problem. With the above framework of KM tools and portals,
one can develop a better appreciation of how these tools and capabilities benefit various KM applications. To
conclude this article, five common KM applications are outlined with their respective KM supporting
“components”: (Cultural issues and integration to legacy systems are undoubtedly key parts of any KM
program hence they are not repeated below. Readers should treat the following as a preliminary guide rather
than a ‘blueprint’ to deploy a KM program.)
Application
Product Development
Process improvement
e-Project Management
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Mergers & Acquisitions
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Expertise location
Communications
Project planning &
reporting templates
Experience sharing
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Assemble a strong &
credible integration team
Make key personnel
decisions swiftly
Standardised method to
access information & assess
value of the acquired
organisation
Communications
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Expertise location
Staff development
E-learning
Performance review
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Human Resources
Key challenges
Consolidate & share best
practices
Strategic Research
Competitive analyses
Expertise location
Collaborations & workflow
Benchmarking
Technical KM components
 Best practice database
 Search
 People finder system
 Corporate memory
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Knowledge Maps
Measurement & tracking
system
Knowledge Communities
People finder system
Best practice, tools,
methodology and lessons
learnt databases
CBR system to retrieve past
project artifacts
Knowledge Communities
People finder system
Knowledge Communities
Best practice, methodology
and lessons learnt databases
Search
Due-diligence work
products
Measurement & reporting
system
People finder system
Staff competency database
Online learning system
Measurement & tracking
system
It is hoped that this article provides the reader with a framework to better understand the types and origin of
the KM tools on the market as they are still the very technologies underpinning the immensely popular
concept of portals. If the latest product offerings by the tool vendors are a guide, then many vendors are now
offering the above tools and more to develop portals to cater for major activities in KM, e-Business and CRM
applications.
Biography
Eric Tsui is Chief Research Officer, Asia Pacific of Computer Sciences Corporation and an honorary
associate of the University of Technology, Sydney. He can be contacted at [email protected] and
[email protected]