MANAGEMENT INFORMATION SYSTEM

SECTION A
QUESTION 1
Answer.

Define MIS? What are the characteristics of MIS?

An organized approach to the study of the information needs of an
organizations management at every level in making operational, tactical
and strategic decisions. Its objective is to design and implement
procedures, processes, and routines that provide suitably detailed reports
in an accurate, consistent and timely manner.
In a management information system, modern, computerized systems continuously
gather relevant data, both from inside and outside an organization. This data is then
processed, integrated, and stored in a centralized database (or data warehouse) where it is
constantly updated and made available to all who have the authority to access it, in
a form that suits their purpose.
What are the characteristics of MIS?
Following are the characteristics of MIS:
It should be based on a long-term planning.
It should provide a holistic view of the dynamics and the structure of the
organization.
It should work as a complete and comprehensive system covering all interconnecting
sub-systems within the organization.
It should be planned in a top-down way, as the decision makers or the management
should actively take part and provide clear direction at the development stage of the
MIS.
It should be based on need of strategic, operational and tactical information of
managers of an organization.
It should also take care of exceptional situations by reporting such situations.

 It should be able to make forecasts and estimates, and generate advanced information,
thus providing a competitive advantage. Decision makers can take actions on the
basis of such predictions.
It should create linkage between all sub-systems within the organization, so that the
decision makers can take the right decision based on an integrated view.
It should allow easy flow of information through various sub-systems, thus avoiding
redundancy and duplicity of data. It should simplify the operations with as much
practicability as possible.
Although the MIS is an integrated, complete system, it should be made in such a
flexible way that it could be easily split into smaller sub-systems as and when
required.
A central database is the backbone of a well-built MIS.
Characteristics of Computerized MIS
Following are the characteristics of a well-designed computerized MIS:
It should be able to process data accurately and with high speed, using various
techniques like operations research, simulation and heuristics.
It should be able to collect, organize, manipulate, and update large amount of raw
data of both related and unrelated nature, coming from various internal and external
sources at different periods of time.
It should provide real time information on on-going events without any delay.
It should support various output formats and follow latest rules and regulations in
practice.
It should provide organized and relevant information for all levels of management:
strategic, operational, and tactical.
It should aim at extreme flexibility in data storage and retrieval.

SECTION A
QUESTION 2
Answer

Explain strategic MIS categories in detail. Give relevant examples.

Strategic MIS is concerned with formulating policies and long term goals. People who make
big decisions for the entire company belong to this level. The information needed at this level
should be a comprehensive, summarised report of the statistics and standing of a company.
The information at this level is a summary of information gathered at tactical level, whose
objective is to meet the goals set by the strategic level. It should present trends over a period
of time that is quarter, a semester or a year. Examples of strategic level management
information systems are Executive Information Systems, Expert System, Executive Support
System, Decision Support Systems, .. These systems present the enterprise wide
performance of the company for executive analysis and decision making.
Below the diagram shows the major types of management information system including
strategic level system as illustrated by Prof. Nishant K. Rai.

Strategic Information System

A Strategic Information System (SIS) is a system to manage information
and assist in strategic decision making. A strategic information system
has been defined as, "The information system to support or change
enterprise's strategy."
A SIS is a type of Information System that is aligned with business
strategy and structure. The alignment increases the capability to respond
faster to environmental changes and thus creates a competitive
advantage. An early example was the favourable position afforded
American and United Airlines by their reservation systems, Sabre and
Apollo. For many years these two systems ensured that the two carriers'
flights appeared on the first screens observed by travel agents, thus
increasing their bookings relative to competitors. A major source of
controversy
surrounding SIS is their sustainability.
SISs are different from other comparable systems as:
They change the way the firm competes.
They have an external (outward looking) focus.
They are associated with higher project risk.
They are innovative (and not easily copied).
Executive Information System
Executive Information Systems are strategic-level information systems that are found at the
top of the Pyramid. They help executives and senior managers analyse the environment in
which the organization operates, to identify long-term trends, and to plan appropriate courses
of action. The information in such systems is often weakly structured and comes from both
internal and external sources. Executive Information System are designed to be operated
directly by executives without the need for intermediaries and easily tailored to the
preferences of the individual using them.
Functions of an EIS
EIS organizes and presents data and information from both external data sources and internal
MIS or TPS in order to support and extend the inherent capabilities of senior executives.
Functions of an EIS in terms of data processing requirements
Inputs

Processing

Outputs

External data

Summarising

Summary reports

Internal files

Simulation

Forecasts

Pre-defined models

Drilling down

Graphs/plots

Some examples of EIS

Executive Information Systems tend to be highly individualized and are often custom made
for a particular client group; however, a number of off-the-shelf EIS packages do exist and
many enterprise level systems offer a customizable EIS module.
The role of EIS

Are concerned with ease of use

Are concerned with predicting the future
Are effectiveness orieted
Are highly flexible
Support unstructured decisions
Use internal and external data sources
Used only at the most senior management levels

Executive Support System

Executive support systems are intended to be used by the senior managers directly to
provide support to non-programmed decisions in strategic management.
These information are often external, unstructured and even uncertain. Exact scope and
context of such information is often not known beforehand.
This information is intelligence based:
Market intelligence
Investment intelligence
Technology intelligence
The following are some examples of intelligent information, which is often the source of an
Executive support system:

Market reports
Confidential information about the competitors
Government policies
Speculative information like market conditions
Technical reports from consultants
Financial reports and information
External data bases
Technology reports like patents

Expert System
Expert systems are computer applications that combine computer equipment, software, and
specialized information to imitate expert human reasoning and advice. Prof. Edward
Feigenbaum from Stanford University, a famous researcher on ES defines ES as: "an
intelligent computer programme that uses knowledge and reasoning procedures to solve
difficult problems that need certain expertise to solve the problems. As a branch of artificial
intelligence, expert systems provide discipline-specific advice and explanation to their users.
While artificial intelligence is a broad field covering many aspects of computer-generated
thought, expert systems are more narrowly focused. Typically, expert systems function best
with specific activities or problems and a discrete database of digitized facts, rules, cases, and
models. Expert systems are used widely in commercial and industrial settings, including
medicine, finance, manufacturing, and sales. Some of the examples of expert system
applications are: An Expert System that helps bank managers in making decisions on granting loans. An Expert System that advises bank managers in giving housing loans.
An Expert System that advises insurance companies on the risks involved in insuring
a customer or a company.
An Expert System that helps banks decides on whether a customer is entitled for a
credit card or not.
As a software program, the expert system integrates a searching and sorting program with a
knowledge database. The specific searching and sorting program for an expert system is
known as the inference engine. The inference engine contains all the systematic processing
rules and logic associated with the problem or task at hand. Mathematical probabilities
often serve as the basis for many expert systems. The second component, the knowledge
database, stores necessary factual, procedural, and experiential information representing
expert knowledge. Through a procedure known as knowledge transfer, expertise (or those
skills and knowledge that sustain a much better than average performance) passes from
human expert to knowledge engineer. The knowledge engineer actually creates and structures
the knowledge database by completing certain logical, physical, and psychosocial tasks. For
this reason, expert systems are often referred to as knowledge-based information systems. By
widely distributing human expertise through expert systems, businesses can realize benefits
in consistency, accuracy, and reliability in problem-solving activities.

An expert system is usually designed to have the following characteristics: The Highest Level of Expertise. This characteristic is most useful. This expertise in an
ES comes from the knowledge and problem solving steps provided by the best experts
in their own domains. This will lead towards efficiency, accuracy and imaginative
problem solving.
Right on Time Reaction. An Expert System must function and interact in a very
reasonable period of time with the user. The total time must be less than the time
taken by an expert to solve the same problem.
Accepting Incorrect Reasoning. This type of application is used when the information
used for the solution is unclear, vague or cannot be obtained and not in a domain that
is very clear.
Good Reliability. The expert system must be reliable and it must be improbable for
the system to make a mistake.
Easily Understood. The Expert System must be able to explain the reasoning steps
during the execution or the inference process for the user to better understand what is
happening. An ES must be able to explain why such actions are taken the same way
an expert would explain the decision he made.
Advantages
Consistency. One of the advantages of an ES is that the results given are consistent.
This might be due to the fact that there are no elements such as exhaustion and
emotions as experienced by humans.
Hazardous Working Environment. Through an ES, we can avoid exposing ourselves
to a toxic or radioactive environment. An ES can take over the place of an expert to
handle problems in a high-risk area such as a nuclear power plant.
Ability to Solve Complex and Difficult Problems. A very difficult problem
encountered by an organisation, if not taken seriously, can cause an adverse impact
such as losses or cancellation of a business deal. Sometimes, the problems need to be
attended to quickly. The problems can become more complicated when individuals or
experts involved in solving them are absent or cannot be contacted. Thus, an ES
serves as an alternative to experts.
Combination of Knowledge and Expertise from Various Sources. ( Rich knowledge
base) This component contains the accumulated knowledge and acquired or
transferred expertise from many experts. Thus, an ES is sometimes more superior
than an expert because its knowledge and expertise have come from many sources.
Training Tool for Trainees. An ES can be used by trainees to learn about the
knowledge-based system. Trainee who uses an ES would be able to observe how an
expert solves a problem.

Disadvantages

 Not Widely Used. ES is not widely used in business firms or organisations. Due to
limited usage, firms are still in doubt about the capability and, most definitely, the
high cost involved in investing in an ES.
Difficult to Use. Using an ES is very difficult and learning and mastering it requires a
long time. This discourages managers from using ES. In one aspect, developing an
ES that is user-friendly is the biggest challenge for ES developer.
Limited Scope. This is the most obvious weakness in an ES, its scope is very limited
to its field only. In the development aspect, the ES built is best developed because of
its high accuracy. However, usage-wise decision makers face constantly changing
problems which involve different fields that are inter-related.
Probable Decision Error. The main source of the knowledge is experts. Humans make
mistakes. If the experts input wrong information into the Expert system, this will
have a negative impact on the results produced.
Difficult to Maintain. The information in ES must be constantly updated to solve new
problems. Every new problem that occurs needs new knowledge and expertise. This
means that there must be an on-going relationship between the domain experts and
the ES developer. This situation requires the domain experts update the source of
knowledge and expertise to suit the current situation.
Costly Development. The cost to consult a group of experts is not cheap, what if ES
was built traditionally without involving the use of an Expert System shell? On the
other hand, programming cost is high because the artificial intelligence technique is
difficult to master and needs a very skilful programmer.
Legal and Ethical Dilemma. We must be responsible for our actions and decisions.
An expert has to take responsibility for the information he or she provides. . The
difficult question here is who should shoulder the responsibility if a decision
suggested by ES results in a negative outcome.

Strategic Support System (SSS)

Decision Support System

A Decision Support System can be seen as a knowledge based system, used by senior
managers, which facilitates the creation of knowledge and allow its integration into the
organization. These systems are often used to analyze existing structured information and
allow managers to project the potential effects of their decisions into the future. Such systems
are usually interactive and are used to solve ill structured problems. They offer access to
databases, analytical tools, allow "what if" simulations, and may support the exchange of
information within the organization.
Functions of a DSS
DSS manipulate and build upon the information from a MIS and/or TPS to generate insights
and new information.

Functions of a DSS in terms of data processing requirements

Inputs
Internal transactions
Internal files
External information?

Processing
Modelling
Simulation
Analysis
Summarising

Some examples of DSS

Group Decision Support Systems (GDSS)

Computer Supported Co-operative work (CSCW)
Logistics systems
Financial Planning systems
Spreadsheet Models?

The role of DSS

Support ill- structured or semi-structured decisions

Have analytical and/or modelling capacity
Used by more senior managerial levels
Are concerned with predicting the future
Are effectiveness oriented?

Outputs
Summary reports
Forecasts
Graphs/ Plots