Management Information System
Short Notes
1.Open and closed system
An open system is one that interacts with its environment and thus exchanges information,
material, or energy with the environment, including random and undefined inputs. Open
systems are adaptive in nature as they tend to react with the environment in such a way
organizing', in the sense that they change their continued existence.Such systems are ‘self
organizing’, because they change their organization in response to changing conditions. A
closed system is one, which doesn’t interact with its environment. Such systems, in business
world, are rare. Thus the systems that are relatively isolated from the environment but not
completely closed are termed closed systems.
2.Non-Programmed Decision
Non-programmed decisions are unique. They are often ill-structured, one-shot decisions.
Traditionally they have been handled by techniques such as judgment, intuition, and
creativity.
More recently decision makers have turned to heuristic problem-solving approaches in
which logic; common sense and trial and error are used to deal with problems that are too
large or too complex to be solved through quantitative or computerized approaches.
In fact, many management training programs on decision-making are designed to help
managers think through problems using a logical, non-programmed approach. In this way
they learn how to deal with extraordinary, unexpected, and unique problems.
3. Artificial intelligence system
Artificial Intelligence can be under – stood as the technology playing a very major part in the
application of the computers to the areas or the fields, which requires the basic knowledge,
the perception, the reasoning, the understanding and the cognitive abilities. By having all
this, it really becomes possible to distinguish the human behaviour from the machines like
the computers etc. Artificial Intelligence actually is the science and the engineering involving
the making of the intelligent machines and one major point to be remembered here is that
the Artificial Intelligence is related a great deal to the similar task of making use of the
computers in order to understand the human intelligence. Human intelligence is also
referred to as the natural intelligence and the below explained comparison between the
Natural Intelligence and the Artificial Intelligence helps a great deal in understanding the
concept of both the Artificial Intelligence and the Natural Intelligence and the basic
differences that occur between them.
4.Black box
idea that consumer decision processes are not completely understandable or predictable.
The black box concept attempts to mark the pattern followed by consumers when making
purchasing decisions. The concept lists the components involved in the reception of
marketing messages and the influences they have on consumers, taking into account
external forces and consumers’ personal characteristics. The factors considered in the black
box concept are environmental, such as economic conditions; personal, such as the ideas
that guide the consumer’s desire for a product; and the buyer’s responses, such as the
process by which the consumer makes a decision about a particular brand or quantity of a
product. Although the black box concept is used as a model to demonstrate the influence of
the marketing mix in concert with other external variables, no one can actually pinpoint the
definitive formula that results in the consumer’s decision; hence the name, black box.
5.Control system model
6. Break Even Analysis
Break-even analysis entails the calculation and examination of the margin of safety for an
entity based on the revenues collected and associated costs. Analysing different price
levels relating to various levels of demand, an entity uses break-even analysis to determine
what level of sales are needed to cover total fixed costs. A demand-side analysis would give
a seller greater insight regarding selling capabilities.Break-even analysis is useful in the
determination of the level of production or in a targeted desired sales mix. The analysis is
for management’s use only as the metric and calculations are often not required to be
disclosed to external sources such as investors, regulators or financial institutions. Break-
even analysis looks at the level of fixed costs relative to the profit earned by each additional
unit produced and sold.
7.Decoupling of Subsystem
In information system design, emphasis is placed on the decoupling of subsystems, so that
each subsystem is as independent as possible. This enhances the adaptability of the system by
permitting isolation of the impact of potential changes on the system. In other words , the
more decoupled (or loosely coupled) the system, the easier it is to modify a subsystem
without affecting the rest of the system. Ease of the maintenance and assurance of the error
free code are important goals of design.
Decoupling can be achieved by defining subsystem so that each performs a single complete
function; thus , connections between subsystems are minimized. For instance , in order entry,
credit checking is done in only one subsystem and credit information is only required by that
module . Another method of decoupling is minimizing the degree of interconnection. This
means the number of assumptions a module needs to make about the internal workings of
another module should be minimized.
8. ABC Analysis
An analysis of a range of items that have different levels of significance and should be
handled or controlled differently. It is a form of pareto analysis in which the items (such
activities, customers, documents, inventory, items, sales territories) are grouped into three
categories (A, B and C) in order of their estimated importance. ‘A’ items are very important,
‘B’ items are important, ‘C’ items are marginally important.
For example, the best customers who yield highest revenue are given ‘A’ rating are usually
serviced by the sales manager, and receive most attention. ‘B’ and ‘C’ customers warrant
progressively less attention and are serviced accordingly.
LONG QUESTIONS
1 . What role MIS play in decision making under certainty, risk and uncertainty with suitable
example?
Decision making under certainty
A condition of certainty exists when the decision-maker knows with reasonable certainty
what the alternatives are, what conditions are associated with each alternative, and the
outcome of each alternative. Under conditions of certainty, accurate, measurable, and
reliable information on which to base decisions is available.
The cause and effect relationships are known and the future is highly predictable under
conditions of certainty. Such conditions exist in case of routine and repetitive decisions
concerning the day-to-day operations of the business.
Decision making under risk
When a manager lacks perfect information or whenever an information asymmetry exists,
risk arises. Under a state of risk, the decision maker has incomplete information about
available alternatives but has a good idea of the probability of outcomes for each
alternative.
While making decisions under a state of risk, managers must determine the probability
associated with each alternative on the basis of the available information and his
experience.
Decision making under uncertainty
Most significant decisions made in today’s complex environment are formulated under a
state of uncertainty. Conditions of uncertainty exist when the future environment is
unpredictable and everything is in a state of flux. The decision-maker is not aware of all
available alternatives, the risks associated with each, and the consequences of each
alternative or their probabilities.
The manager does not possess complete information about the alternatives and whatever
information is available, may not be completely reliable. In the face of such uncertainty,
managers need to make certain assumptions about the situation in order to provide a
reasonable framework for decision-making. They have to depend upon their judgment and
experience for making decisions.
2 . Explain Herbert A Simon model of decision making process?
Herbert Simon made key contributions to enhance our understanding of the decision-
making process. In fact, he pioneered the field of decision support systems. According to
(Simon 1960) and his later work with (Newell 1972), decision-making is a process with
distinct stages. He suggested for the first time the decision-making model of human beings.
His model of decision-making has three stages:
• Intelligence which deals with the problem identification and the data collection on the
problem.
• Design which deals with the generation of alternative solutions to the problem at hand.
• Choice which is selecting the 'best' solution from amongst the alternative solutions using
some criterion.
The figure given below depicts Simon's decision-making model clearly.
Intelligence Phase
This is the first step towards the decision-making process. In this step the decision-maker
identifies/detects the problem or opportunity. A problem in the managerial context is
detecting anything that is not according to the plan, rule or standard. An example of problem
is the detection of sudden very high attrition for the present month by a HR manager among
workers. Opportunity seeking on the other hand is the identification of a promising
circumstance that might lead to better results. An example of identification of opportunity is-
a marketing manager gets to know that two of his competitors will shut down operations
(demand being constant) for some reason in the next three months, this means that he will
be able to sell more in the market.
Thus, we see that either in the case of a problem or for the purpose of opportunity seeking
the decision-making process is initiated and the first stage is the clear understanding of the
stimulus that triggers this process. So if a problem/opportunity triggers this process then the
first stage deals with the complete understanding of the problem/opportunity. Intelligence
phase of decision-making process involves:
Problem Searching: For searching the problem, the reality or actual is compared to some
standards. Differences are measured & the differences are evaluated to determine whether
there is any problem or not.
Problem Formulation: When the problem is identified, there is always a risk of solving the
wrong problem. In problem formulation, establishing relations with some problem solved
earlier or an analogy proves quite useful.
Design Phase
Design is the process of designing solution outlines for the problem. Alternative solutions are
designed to solve the same problem. Each alternative solution is evaluated after gathering
data about the solution. The evaluation is done on the basic of criteria to identify the positive
and negative aspects of each solution. Quantitative tools and models are used to arrive at
these solutions. At this stage the solutions are only outlines of actual solutions and are meant
for analysis of their suitability alone. A lot of creativity and innovation is required to design
solutions.
Choice Phase
It is the stage in which the possible solutions are compared against one another to find out
the most suitable solution. The 'best' solution may be identified using quantitative tools like
decision tree analysis or qualitative tools like the six thinking hats technique, force field
analysis, etc.
This is not as easy as it sounds because each solution presents a scenario and the problem
itself may have multiple objectives making the choice process a very difficult one. Also
uncertainty about the outcomes and scenarios make the choice of a single solution difficult.
3 .Explain the role of Feedback in the system ?
