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CS507 - Information Systems - Lecture Handout 10

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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.

Support systems can be classified into two categories

  • Office automation systems
  • Decision support systems

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
  • Email
  • Audio & video conferencing – establishing communication between geographically dispersed persons.

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

  • 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.

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

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

Types of DSS

DSS, may either be

  • Model Driven DSS
  • Data Driven DSS

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 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
  • 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.

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
    • Models

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.