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8/2/2019 MIS-UNIT-IV

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MANAGEMENT INFORMATION SYSTEMS

AND DSSUNIT-IV

DISHA TECHNICAL CAMPUS


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FIVE ELEMENTS OF USABLE MIS

Timelines

Relevance

Accuracy

Consistency

Completeness


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DEVELOP MENT OF MIS

Approach to Management Information System (MIS) Design

A classical systems and software engineering approach isrecommended to assure the development of a managementinformation system that is fully responsive to a clients performance

objectives and resource constraints. This approach includes thefollowing major components:


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DESIGNING PHASE

The Business application system demands designing of systems suitable to theapplication in project. While designing MIS, a general approach has to be followedto cater to the needs of different organizations as per their functions and decisionsmaking requirements.

The major steps involved in the design are the following:

Identifying Information needs at all levels of Management:

Listing objectives of MIS and anticipated benefits:

a) What is the purpose of the system?

b) Why is it needed?

c) What is it expected to do?

d) Who are the users and what are their objectives?

Identifying systems constraints.

Internal : The internal constraints are viewed in terms of:

a) Top management support.

b) Organization policy

c) Man power needs and availability

d) Cost and resources

e) Acceptance.


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External : The external constraint are mainly concerned with

a) Customer oriented

b) Government policy.

c) Competitor oriented

Determining Information needs and resources: The type of informationwhich is required at various times and for various purposes depends on twofactors:

a) Personal Managerial attitudes like knowledge of information systems,managerial style, perception of information needs, etc. of the individualmanager.

b) Organizational Environment like nature of the company, level ofmanagement, structure of the organization.

The sources of information may be categorized as follows:

Internal sources.

External sources.

DESIGNING PHASE Contd.


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Developing alternative conceptual design and selecting one: The

alternative concept of a system can be evaluated on the basis of the following.

a) Compare anticipated performance of the conceptual design with respect

to objective of the system developed earlier.

b) For quantified comparison amongst systems, prepare a preliminary cost-

effectiveness data for the system.

c) Examine the quality of database and information to be made available.

Study the number of operations, dispersions and duplication of files and

potential breakdown points.

d) Expands the conceptual designs in greater detail if none of these provide a

preferred design.

Preparing the conceptual design report: The conceptual design report is a

proposal prepared for the expenditure of funds and possible changes in the

organizational set-up.

DESIGNING PHASE Contd.


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DEVELOP MENT OF MIS

Systems implementation: It includes forms development, specification ofdata collection and entry procedures, development of editing and qualitycontrol procedures, software coding and testing, development of trainingmaterials and training, integration of the software components with othersystem components (e.g., personnel, communications, data transfer and

assembly, report preparation and distribution, feedback), and system-level testing.

Systems operation and support, which includes not only routine

operating procedures but also provision for on-going system financingand management, quality control, software maintenance and updating,personnel training, and system maintenance and improvement(including periodic review of system performance and diagnosis andcorrection of problems)


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Approaches of MIS Development

There are seven approaches, which are used for developing MIS:

1. Top down approaches: Here top management takes the lead in

formulating objectives, policies and plans and communicates

them down the line to middle and supervisory management

for translating them into reality.

2. Bottom up approaches: This approach consist of the following

steps:

i. Individual functional applications are planned separately consisting of

transaction processing, updating of files and simple reports.

ii. Files of various functional applications are integrated by means of

indexing and chaining into a database.

iii. Various functions are added to operate on the database at

management level.


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iv. Integration of models into a model base having a wide variety of analysis,decision and planning models.

v. Strategic planning data and planning models are added to the informationsystem.

3. Integrative Approach: This approach permits managers at all levelsto influence the design of the information system. Here evaluation,modification and approval of top management continues, till a final designis acceptable to all levels.

4. Traditional Approach: Here activities are performed in sequence.Each activity is undertaken only when the previous activity is completed.

5. Prototyping Approach: In order to avoid any possible delay,prototyping approach is used. The goal is to develop a small or pilotversion, called a prototype, which is built quickly and at lesser cost with

the intention of modifying it when need arises.


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6. End

User Development Approach: With the increasingavailability of low cost technology, end user development is popular in

many organizations. Here the end user is responsible for system

development.

7. Systematic Approach for development in small organizations:In a very small organization, no MIS professional will exist. They developsystems using the following steps:

a. Identify requirements.

b. Locate, evaluate and secure software development.

c. Locate, evaluate and secure hardware.d. Implement the systems.


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DSS CLASSIFICATIONS

Model-driven DSS

A model-driven DSS emphasizes access to and manipulationof financial, optimization and/or simulation models. Model-driven DSS use limited data and parameters provided by

decision makers to aid decision makers in analyzing asituation, but in general large data bases are not needed formodel-driven DSS.

Early versions of model-driven DSS were called model-

oriented DSS by Alter (1980), computationally oriented DSSby Bonczek, Holsapple and Whinston (1981) and laterspreadsheet-oriented and solver-oriented DSS by Holsappleand Whinston (1996).


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DSS CLASSIFICATIONS

Data-driven DSS

In general, a data-driven DSS emphasizes access to andmanipulation of a time-series of internal company data andsometimes external and real-time data. Simple file systemsaccessed by query and retrieval tools provide the most elementary

level of functionality.

Data warehouse systems that allow the manipulation of data bycomputerized tools tailored to a specific task and setting or by moregeneral tools and operators provide additional functionality.

Executive Information Systems are examples of data-driven DSS(Power, 2002). Initial examples of these systems were called data-oriented DSS, Analysis Information Systems (Alter, 1980) andretrieval-only DSS by Bonczek, Holsapple and Whinston (1981).


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DSS CLASSIFICATIONS

Communications-driven DSS

Communications-driven DSS use network and communications technologies tofacilitate decision-relevant collaboration and communication. In these systems,communication technologies are the dominant architectural component. Toolsused include groupware, video conferencing and computer-based bulletinboards (Power, 2002).

In the early 1980s, academic researchers developed a new category ofsoftware to support group decision-making called Group Decision SupportSystems abbreviated.

In 1989, Lotus introduced a groupware product called Notes and broadenedthe focus of GDSS to include enhancing communication, collaboration andcoordination among groups of people. Notes had its roots in a product calledPLATO Notes, written at the Computer-based Education Research Laboratory(CERL) at the University of Illinois in 1973 by David R. Woolley.

In general, groupware, bulletin boards, audio and videoconferencing are theprimary technologies for communications-driven decision support. In the pastfew years, voice and video delivered using the Internet protocol have greatlyexpanded the possibilities for synchronous communications-driven DSS.


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DSS CLASSIFICATIONS

Document-driven DSS

A document-driven DSS uses computer storage and processingtechnologies to provide document retrieval and analysis. Large documentdatabases may include scanned documents, hypertext documents, images,sounds and video.

Examples of documents that might be accessed by a document-drivenDSS are policies and procedures, product specifications, catalogs, andcorporate historical documents, including minutes of meetings andcorrespondence. A search engine is a primary decision-aiding toolassociated with a document-driven DSS (Power, 2002). These systems

have also been called text-oriented DSS (Holsapple and Whinston,1996).


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DSS CLASSIFICATIONS

Knowledge-driven DSS

Knowledge-driven DSS can suggest or recommend actions to managers.These DSS are person-computer systems with specialized problem-solvingexpertise. The "expertise" consists of knowledge about a particular domain,understanding of problems within that domain, and "skill" at solving some

of these problems. These systems have been called suggestion DSS (Alter, 1980) and

knowledge-based DSS.

In 1965, a Stanford University research team led by Edward Feigenbaumcreated the DENDRAL expert system. DENDRAL led to the development of

other rule-based reasoning programs including MYCIN, which helpedphysicians diagnose blood diseases based on sets of clinical symptoms.


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Alter concluded from his research (1980) that decision support systems could becategorized in terms of the generic operations that can be performed by such systems.These generic operations extend along a single dimension, ranging from extremely data-oriented to extremely model-oriented. Alter conducted a field study of 56 DSS that hecategorized into seven distinct types of DSS. His seven types include:

File drawer systemsthat provide access to data items.

Data analysis systemsthat support the manipulation of data by computerizedtools tailored to a specific task and setting or by more general tools and operators.

Analysis information systemsthat provide access to a series of decision-oriented databases and small models.

Accounting and financial modelsthat calculate the consequences of possibleactions.

Representational modelsthat estimate the consequences of actions on the basisof simulation models.

Optimization modelsthat provide guidelines for action by generating an optimalsolution consistent with a series of constraints.

Suggestion modelsthat perform the logical processing leading to a specific

suggested decision for a fairly structured or well-understood task.

DSS CLASSIFICATIONS (Alter)


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