Knowledge Management Systems (Chapter 8)
Saturday, May 12, 2018
ECONOMICS OF KM SYSTEMS
ECONOMICS OF KM SYSTEMS
Early development consideration of KM
systems by senior management need to take into account the overall costs of
implementing and maintaining these systems.
These can be divided into costs
related to implementing a KM system including overheads, and salary costs of
employees with designated KM functions.
The implementation costs of KM
systems include the following, (Maier 2001) à
- Hardware – internet broadband
connections and mobile technology such as mobile phones, laptops and Bluetooth wireless
technology
- Software – use off-the-shelf
solutions with significant customisation
- Training and education – continual
communication about benefits of new system as well as structured training
programme for all levels on use of KM system
- Literature, conferences,
consulting and proactive participation in KM activities – KM budget to spend on
literature, funding KM research programmes, attending conferences and employing
consultants.
- Organization of KM events –
announcing and communicating KM initiative and facilitating ‘communities of
practice’
- KM overload – to coordinate KM
initative
- KM systems administration – to protect
system from hackers
- KM staff – salaries
CUSTOMER RELATIONSHIP MANAGEMENT SYSTEMS (CRMS)
CUSTOMER RELATIONSHIP MANAGEMENT SYSTEMS (CRMS)
CRMS are firmly rooted in front-office
integration and revolve principally around marketing.
The motivation is to integrate
technology and business processes to meet customer requirements at any given
moment.
Customer relationship strategy is
about cementing long-term, collaborative relationships with customers based on
trust (Crosby 2002).
More about enhancing the customers’
lifetime value to the firm instead of short term revenue gains from the
customer.
As a competition have increased, the
market segmentation was started to focus towards customer-centric orientations
instead of focusing on customer segmentation.
Customer-centric orientation was
about a relationship with the customers and treating each customer individually
and uniquely. It was one-to-one marketing.
Besides that, there are also some
problems that may occur in CRM. However, to overcome some of these problems, a CRM
development plan based on a project lifecycle is outlined below (Bose 2002):-
1. Planning
2. Research
3. Systems analysis
4. Design
5. Construction
6. Implementation
7. Maintenance and documentation
8. Adaptation
EXECUTIVE INFORMATION SYSTEM (EIS) & WORKFLOW MANAGEMENT SYSTEMS (WMS)
EXECUTIVE INFORMATION SYSTEM (EIS)
EIS was
developed in the mid-1980s with a primary goal of enhancing the strategic
planning and control processes of executives through the provision of quality,
timely, accurate and accessible information (O’Brien 1991).
Provided a broad understanding of
company information by summarizing large quantities of data and allowed the
user to drill down to different levels of data to gain insight into the detail
of information.
One dilemma facing the high-quality
information requirements of EIS is the fact that data is often input using
unskilled and untrained operatives, which may lead to gross errors and
misleading analyses.
Careful consideration must be taken
to avoid dangers of ‘garbage in, garbage out’ syndrome and potential risk of
making the wrong decisions.
Research on the effective
implementation of EIS has found number of factors that linked with continuous
improvement that can increase the EIS -à
- Need
for a committed executive sponsor to drive project and provide feedback on the
product quality and expectation
- Need
for a pro-active operating sponsor, to act as market researcher with the
executives, confidence builder, product designer and operational line manager
- The
bringing together of business knowledge and IT skills through framework
- Coordinating
systems and processes lower in the organization with EIS to ensure alignment of
effort
- Visually attractive graphics
WORKFLOW MANAGEMENT SYSTEMS (WMS)
- One
of the ideal tools in business process re-engineering
- Part
of enterprise resource planning (ERP) and consider as the back-office
integration processes in organization.
- An
important function of WMS is the modelling of workflows. WMS can be seen as
repositories of an organization’s procedures and process.
- They
are predominantly suited to the efficient processing of a large number of
‘cases’ within a small number of predefined process.
- With
a separate workflow defined each case more likely to occur in future
developments of WMS
- Example
cases; customer orders, insurance claims, university application and tax
returns. However, each cases has a unique identity and a limited finite
lifetime.
- Task
in a WMS are logical units of work such as writing reports and assessing
candidates, and can be manual, semi-automatic or automatic.
- The
combination of a task and a case is termed a work item and the application of a
task on a case is seen as an activity. Besides that, there are number of ways
that a case can go through a process and this determines the nature and order
of the tasks to be performed.
- This routing of a case may be à
-
Sequential
-
Parallel
-
Selective
There are traditional and formal analysis of processes is use of ‘PETRI
NETS’ – enables processes to be described graphically and is composed of places
and transition.
This to ensure precise definitions of processes and prevent ambiguities.
Circle – places indicate states within a
process
Rectangle – transition may denote different
activities between states
*Places and transitions often linked
together using arcs shown by the arrows
Besides that, to
develop standards with the multitude of WMS, the Workflow Management Coalition
(WFMC) was set up to define terminology and provide standards for exchange of
data between different systems. The WFCM has produced a workflow reference
model as a general description of architecture in WMS.
In addition, there are
different aspects of WMS:
1. Workflow
enactment service
2. Process
definition tools
3. Workflow
client application
4. Invoked
application
5. Administration
and monitoring tool
There are 2 methods of developing WMS using
business process re-engineering (BPR) or rapid application development (RAD).
1. BPR – aims to discover the most
efficient and effective business processes without resource to existing
processes.
However, BPR lifestyle is initiated by senior management and
contains 4 phases:
1. Diagnosis
2. Redesign
3.
Reconstruction
4. Operations
2. RAD – uses more evolutionary method
for developing WMS and has a strong emphasis on user participation.
The RAD
approach comprises 4 phases
1. Requirements
planning phase
2. User design
phase
3. Construction
phase
4. Delivery
phase
GROUP SUPPORT SYSTEM (GSS)
GROUP SUPPORT SYSTEM (GSS)
Teamwork is part of most
organizations in one form or another. In response to global and competitive
pressures, organizations are increasingly having their activities
geographically dispersed and using internet technologies to communicate over
long distances. Distance and time differences globally are less of barrier
nowadays with a variety of technologies employed such as e-mail, video conferencing,
mobile phones and co-authoring systems. Besides that, the important feature is
the development of appropriate technologies to facilitate collaboration and
cooperation in groups and teams.
There are 5 basic team processes supported by GSS;-
1. Communication
2. Knowledge sharing and learning
3. Cooperation
4. Coordination
5. Social Interaction/Social encounters
Experience has shown that the success
of GSS relies on more than technology. There a are several noteworthy
guidelines to improve the effectiveness of GSS (Andriessen 2003) à
- If possible, start a group with face-to-face meetings\
- Learn about each other’s backgrounds through “yellow pages”
- Prepare and structure synchronous meeting well,
- Use video links where possible to develop trust and cohesion
- Provide regular information on progress and milestones
- Pay attention to training and intercultural differences
Even though DSS provide a forum for
knowledge sharing, learning and enhanced problem solving, they can also pose
certain challenges for groups. For example;
- ‘free-riders’ relying on others to do all work
- Risk decisions
- Compromised solutions of low quality
- Information overload
DECISION SUPPORT SYSTEM (DSS)
DECISION SUPPORT SYSTEM (DSS)
DSS combine data analysis and
sophisticated models to support non-routine decision making. This is useful in
helping the managers make decisions on ill-defined problems in rapidly changing
environments. They provide the user with an interactive interface and bring
together analyses and models to make sense of existing internal and external
data.
There are several major capabilities
of DSS (Turban and Aronson 2001);
- Provide support in semi-structured and unstructured situations
- Support several sequential and interdependent decisions
- Support intelligence, design, choice and implementation phases of decision making
- Support a variety of styles and processes
- Are adaptive and flexible over time
- Are user-friendly with strong graphical capabilities
- Improve accuracy, timeliness and quality of decision making
- Have substantial modelling capability to allow experimentation with different strategies under different scenarios.
There are multitude of DSS on offer
in the marketplace. Besides that, there are also two distinction would be to
separate them into MODEL-DRIVEN DSS & DATA DRIVEN DSS.
Below is Model-Driven DSS provide a
range of statistical, financial, forecasting and management science models that
may be applied at strategic, tactical or operational levels.
The DSS may contain between a few and
several hundred models encompassing:-
- Strategic Models – tend to help high-level strategic planning processes within organization
- Tactical Models - assist in allocating and controlling organizational resources such as capital budgeting and human resource planning
- Operational Models – help to support day-to-day decision making, such as loans approval and quality control processes.
- Analytical Models- cover methods of analysis such as statistical models or specific financial models.
Besides that, in contrast – Data
Driven DSS : are more focused on examining patterns and relationships in large
amounts of data. They used Knowledge evaluation tools such as online analytical
processing (OLAP), to provide multidimensional analyses and data mining
techniques looking at à
- Associations: are occurrences linked to a single event
- Sequence: are events linked over time
- Classification: recognizes pattern in certain groups such as loyal or fraudulent customers
- Clustering techniques: can help to determine different groupings of certain customers where the classification don’t necessarily exist.
- Forecasting techniques: can help to predict values for certain variables
- Data mining techniques: vary
considerably in the variety of approaches adopted, from fuzzy logic to neural
networks. There are different industrial sectors illustrate typical analyses
that data mining techniques may help to uncover: - Banking industry
- Retail and Marketing
- Insurance
In order to purchase a DSS, an
organization need to decide between custom-made
solutions or off-the-shelf
solutions.
- Off-the-shelf solutions - are the lower costs, flexibility and application of many
business problems in the same sectors
- Custom-made solutions – allow the organization to differentiate themselves from a competitors and use a more sophisticated approach based on different configuration. There are 7 classification;-
1. Text-oriented DSS – using technologies such as Web-Based documents, hyperlinks and
intelligent agents
2. Database-oriented DSS – featuring strong report generation and query-searching
capabilities
3. Spreadsheet-oriented DSS – such as Excel which uses statistical and financial models and
techniques
4. Solver-oriented DSS – functions or
procedures used for optimizing certain variables such as the optimal ordering
quantities of certain resources based on historical data
5. Rule-oriented DSS – often expert
systems linked to procedural and inferential (reasoning) rules such as
evacuation of a tall building in case of fire in certain parts of it
6. Compound DSS – containing two or more
aspects of the above five classification
7. Intelligent DSS – similar to rule-oriented
DSS that can learn using agent technology and machine learning techniques
DOCUMENT MANAGEMENT SYSTEMS (DMS)
DOCUMENT MANAGEMENT
SYSTEMS (DMS)
Organizations tend to publish a variety of
documents for internal consumption or for external sources such as suppliers,
customers, and shareholders.
The volume of these documents to increase
substantially each year and an urgent need to manage them adequately for
efficient storage and retrieval.
DMS have developed to address these problems and
have typically employed the intranet as an electronic medium rather than
conventional document printing and circulation methods.
The primary driving forces have been the cost
savings compared with conventional publication and distribution methods,
together with the dynamics nature of intranets.
Documents can be published and updated on the
internet when needed and become available instantly to all interested users
(Frazee 1996).
Types of documents; policy and procedure
manuals, corporate phone directors, online help, HR guidelines, sales and
marketing literature, customer data, price lists and press release.
The
‘value-adding facilities of DMS may include:-
- Control to ensure only one user modifies a document at a time
- Audit trail to monitor changes in a document over time
- Security processes to control user access to documents
- Organization of documents into related groups and folders
- Identification and retrieval of documents according to text they contain (free-text searching)
- Recording information associated with the document as Meta data such as author. Creation date and title
- Ability to route the documents from one user to another in a controlled fashion based on the workflow
- Converting paper documents into electronic format by scanning
- Organizing documents into groups to enable them to be distributed to target audiences
The process of
implementing a DMS can be divided into number of phases, as shown in this table
below:-
Some of the
typical remaining organizational challenges presented by DMS have included;
- Privacy
- Currency of information
- Performance
- Security
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