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Support Systems

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
Word processing
Desktop publishing
Imaging & Web publishing
Electronic calendars – manager’s appt. calendars
Audio & video conferencing – establishing communication between geographically dispersed

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
Ease of Control
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.

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
Measure customer reactions to re-pricing
When to initiate clearance sales for old stock
Deciding about discount percentages
When to order new stock for the season

10.2 Functionalities of MIS and DSS
1 Provides information on
monitoring and controlling the
Helps in non routine decision making.
2 Fixed and regular reports are
generated from data kept in
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
proposed solution
e.g. What will happen to the market share if the advertising budget increases by 5 % or
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
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.
They use following techniques for data analysis
Online analytical processing, and
Data mining

Components of DSS
There are two major components
DSS data base – is a collection of current and historical data from internal external sources. It can be a
massive data warehouse.
Decision Support Software system – is the set of software tools used for data analysis. For instance
Online analytical processing (OLAP) tools
Data mining tools

Data Warehouse
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.
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.
The term data warehouse generally refers to the combination of many different databases across an
entire enterprise.
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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