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Lesson#10
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Support Systems
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Support Systems
Seeing the benefits of MIS for middle level managers,
Computerised systems have been devised for other
employees in the organization to help them complete their work
efficiently and effectively.
10.1 Support systems can be classified into two categories
•
Office automation
systems
•
Decision support systems
10.1.1 Office Automation Systems
Office automation system includes formal and informal electronic
systems primarily concerned with the
communication of information to and from persons both inside and
outside the firm. It supports data
workers in an organization.
For Instance
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Word processing
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Desktop publishing
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Imaging & Web publishing
•
Electronic calendars –
manager’s appt. calendars
•
Email
•
Audio & video
conferencing – establishing communication between geographically dispersed
persons.
10.1.2 Decision Support Systems
Before moving forward with the concept of decision support
system, we would take a look at the definition
of MIS
“An integrated man-machine system for providing information to
support the operations, management and
decision making functions in an organization.”
(
Prof. Gordon Davis
University of Minnesota)
Four Criteria for designing models and systems to support
management decisions making were laid down
by J.D.C. Little. These were
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Robustness
•
Ease of Control
•
Simplicity
•
Completeness of relevant
detail
Decision Support Systems was defined by Bill Inmon, father of
data warehouse, as
“a system used to support managerial decisions. Usually DSS
involves the analysis of many units of data
in a heuristic fashion. As a rule, DSS processing does not
involve the update of data”
Heuristic simply means a particular technique of directing one’s
attention in learning, discovery or problem
solving. It assists in non-routine decision making process due
to powerful analytical abilities.
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For Instance
For any scenario all the related factors with their ranges of
variability are entered into DSS, which helps
guide managers for any new scenario that emerges. DSS can
stimulate innovation in decision making by
helping managers to existing decision making procedures.
An example of Decision Support System
An outfit store maintains ready made garments and stitched
clothes for various classes of society. Due to
fluctuating changes in fashion trends, pre-seasonal planning
becomes critical.
•
A Planning and
forecasting software can be used by management to
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Measure customer
reactions to re-pricing
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When to initiate
clearance sales for old stock
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Deciding about discount
percentages
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When to order new stock
for the season
10.2 Functionalities of MIS and DSS
Sr. No. MIS DSS
1 Provides information on
monitoring and controlling the
business.
Helps in non routine decision making.
2 Fixed and regular reports are
generated from data kept in
TPS.
Users are not linked with the structured
information flows.
3 Report formats are predefined. Greater emphasis on models,
display
graphics & ad hoc queries.
4 User is part of the system DSS is a small part of users’
actions.
5 Controlled by IT Dept. Directly used by middle level managers
Table 10.1
10.3 Types of DSS
DSS, may either be
•
Model Driven DSS
•
Data Driven DSS
10.3.1 Model Driven DSS
Model driven DSS uses following techniques
• What-If
analysis
Attempt to check the impact of a change in the assumptions
(input data) on the
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proposed solution
e.g. What will happen to the market share if the advertising
budget increases by 5 % or
10%?
• Goal Seek
Analysis
Attempt to find the value of the inputs necessary to achieve a
desired level of output. It
uses “backward” solution approach
e.g. a DSS solution yielded a profit of $2M. What will be the
necessary sales volume to
generate a profit of $2.2M?
These are primarily stand alone systems isolated from major
organizational information systems (finance,
manufacturing, HR, etc). They are developed by end users and are
not reliant on central information
systems control. These systems combine
•
Use of a strong model,
and
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Good user interface to
maximise model utility
They are not usually data intensive, hat is very large data
bases are usually not need for model-driven DSS.
They use data and parameters usually provided by decision makers
to aid in analyzing a situation.
10.3.2 Data Driven DSS
As opposed to model driven DSS, these systems use large pools of
data found in major organizational
systems. They help to extract information from the large
quantities of data stored. These systems rely on
Data Warehouses created from Transaction Processing systems.
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They use following
techniques for data analysis
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Online analytical
processing, and
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Data mining
Components of DSS
There are two major components
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DSS data base – is a
collection of current and historical data from internal external sources. It can
be a
massive data warehouse.
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Decision Support
Software system – is the set of software tools used for data analysis. For
instance
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Online analytical
processing (OLAP) tools
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Data mining tools
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Models
Data Warehouse
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A data warehouse is a
logical collection of information.
•
It is gathered from many
different operational databases used to create business intelligence that
supports business analysis activities and decision-making tasks.
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It is primarily, a
record of an enterprise's past transactional and operational information, stored
in a
database designed to favour efficient data analysis and
reporting.
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The term data warehouse
generally refers to the combination of many different databases across an
entire enterprise.
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Data warehouses contain
a wide variety of data that present a coherent picture of business conditions at
a single point in time.
•
Data warehouses are
generally batch updated at the end of the day, week or some period. Its contents
are typically historical and static and may also contain
numerous summaries. |
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