Management Information System (MIS):

The concept of Management Information System (MIS) has evolved significantly over time,
becoming a necessity for all organizations. Initially, MIS focused on processing organizational data
and presenting it in routine reports. This evolved to a distinction between data and information,
where information became understood as the product of data analysis, making the system more
individual-oriented and designed to provoke a decision, action, or investigation. Later, the concept of
need-based exception reporting and the DATABASE concept emerged, allowing users to access and
process data according to their specific needs.

In its current understanding, MIS is a system that manages databases, provides computing
facilities, and offers various decision-making tools to the end-user. It places high regard on an
individual's ability to utilize information and draws on theories, principles, and concepts from various
academic disciplines, including Management Science, Management Accounting, Operations
Research, Organizational Behavior, Engineering, Computer Science, Psychology, and Human
Behavior, to enhance its effectiveness and utility. The foundation of MIS lies in the principles and
practices of management, incorporating concepts of management control and acknowledging the
manager as a human information processor.

For an MIS to be effective, it requires systematic planning and design, which involves analyzing the
business, management views and policies, organizational culture, and management style. It heavily
relies on systems theory to manage complex input and output flows and uses communication
theories to ensure information transmission with minimal noise or distortion. MIS is a dynamic
concept, constantly reviewed and modified to meet changing corporate information needs, and it
interacts continuously with both internal and external business environments to provide corrective
mechanisms. It supports business management through various phases of growth by providing
crucial information, especially concerning critical success factors.

The sources offer several definitions for MIS, all converging on the central idea that MIS is a system to
support the decision-making function in an organization. Some definitions include:

• A system that provides information support for decision-making in the organization.

• An integrated system of man and machine for providing information to support operations,
management, and decision-making.

• A system based on the database of the organization for providing information to its people.

• A Computer-based Information System.

Today, MIS is primarily understood as a computerized business processing system that generates
information for people in the organization to meet their decision-making needs and achieve
corporate objectives.

Role of Information System (MIS)

The role of MIS within an organization is likened to that of a heart in the human body, where
information is the "blood" and MIS is the "heart". It ensures that appropriate data is collected from
various sources, processed, and distributed to all necessary destinations. MIS is designed to fulfill the
information needs of individuals, groups, managers, and top management alike. It achieves this by
offering a variety of systems, such as Query Systems, Analysis Systems, Modeling Systems, and
Decision Support Systems (DSS).

Specifically, MIS plays a crucial role in:

• Strategic Planning.

• Management Control.

• Operational Control.

• Transaction Processing.

It assists different levels of personnel:

• Clerical personnel use MIS for transaction processing and data queries.

• Junior management benefits from operational data for planning, scheduling, control, and
decision-making at the operations level.

• Middle management utilizes MIS for short-term planning, target setting, and controlling
business functions.

• Top management is supported by MIS in goal setting, strategic planning, and the
implementation of business plans.

Ultimately, MIS acts as an information generator, a communication facilitator, a problem

identifier, and a direct aid in the decision-making process, making its role vital across
management, administration, and operations.

Nature and Scope of MIS

The nature of MIS is inherently dynamic, requiring constant review and modification to align with the
changing corporate information needs. It is a prescribed product design for each organization,
meaning that MIS design will differ between two organizations even if they are in the same
business, due to differences in people, management styles, and organizational culture.

The scope of MIS has significantly expanded, moving beyond a traditional "digital firm perspective" to
encompass a "global digital enterprise perspective" due to globalization. This broader scope
means:

• Organizational processes are ICT (Information and Communication Technology) driven,

often crossing organizational boundaries.

• Technology resources now extensively include mobile computing, cloud computing, portals,
and social networking.

• Human Resources are expected to be smart users of technology.

 • The 5th edition of the "Management Information Systems" text introduces new topics reflecting
this expanded scope, such as:

o Organization model for business excellence.

o Business performance management.

o Information security engineering and Security Risk Management.

o Strategic management of business for performance achievement.

o Knowledge management for strategic management of business.

o Business Intelligence (BI), tools & technology, and Intelligent DSSs.

o Managing global enterprise beyond e-business.

o Service Oriented Architecture (SOA), Cybersecurity, and WEB2.0.

The book posits an MIS model that features a superstructure of Knowledge Management Systems,
BI-based scenario building systems for decision-making, and Strategic Performance Measuring
Systems for performance control. This comprehensive scope leads to several impacts of MIS on an
organization:

• Improved functional management: Marketing, finance, production, and personnel become

more efficient, with easier tracking and monitoring of targets.

• Enhanced understanding of the business: A disciplined information reporting system creates

a structured database and knowledge base, leading to a common understanding of terms and
events across the organization.

• Streamlined operations and professionalism: MIS systematizes business operations,

enforcing discipline and fostering professionalism.

• Alignment with corporate goals: By providing relevant information, MIS helps direct the entire
organization towards its corporate objectives.

• Reduction in clerical overhead: Automation of clerical work frees human minds for more
valuable tasks, reducing significant time spent on recording, searching, processing, and
communicating.

• Creation of an information-based work culture.

• Empowerment of users: Enables better decision-making by increasing manipulative

capability with information available on desktops.

• Strategic Advantage: MIS can be used as a strategic weapon to counter business threats,
enhance competitiveness, and achieve organizational transformation through integration. It
also promotes a seamless organization by removing communication barriers.

Information Concepts
Information is defined as data that has been processed into a form meaningful to the recipient
and holds real or perceived value for current or prospective actions or decisions. In contrast, data
is considered raw material, while information is the finished product. For an entity to be considered
information, it must be effectively transferred from a "source" to a "destination" without loss of
content, akin to a communication model where MIS acts as the transmitter.

Types of Information
Information can be classified in various ways based on its nature, application, and user:

• Action Information: Information that prompts a direct decision or action, often requiring
timely and accurate reporting.

• No-action/Knowledge-oriented Information: Information that updates one's knowledge

level, even if it doesn't lead to immediate action or reduce uncertainty.

• Recurring Information: Generated at regular, fixed intervals (e.g., monthly, quarterly) to track
trends and make comparisons.

• Ad hoc Information: Requested on a non-routine, as-needed basis.

• Internal Information: Data sourced from within the organization.

• External Information: Data sourced from outside the organization. The mix of internal and
external information varies by management level; top management relies more on external
information, while operational and middle management focus on internal data.

• Planning Information: Includes standards, norms, and specifications used for planning any
activity (e.g., time standards, design standards).

• Control Information: Reports the status of an activity through a feedback mechanism,

highlighting deviations from goals to induce decisions or actions.

• Knowledge (as an Information Set): A collection of information (e.g., from library reports,
research studies) that builds a knowledge base for decision-making. While not directly linked
to a specific decision, it is perceived as an organizational strength. Modern MIS now integrates
Knowledge Management Systems (KMS) to provide this vital support.

• Organizational Information: Required by multiple personnel, departments, and divisions

across the organization (e.g., employee attendance, product details, turnover). It is advisable
to store this data in a database for various users to generate their respective information
needs.

• Database Information: Has multiple uses and applications, stored for multiple users, and
may require security or access control.

• Functional/Operational Information: Used in the daily operations of a business (e.g., sales

statistics, production figures). This is typically detailed, current, and relates to a small time
span.
 • Decision Support Information: Information primarily used by middle and top management to
aid in decision-making, model building, and problem-solving, without necessarily acting as a
direct input to a formula. It can justify a decision or aid in making one (e.g., non-moving
inventory reports for disposal decisions).

Information Quality and Dimensions

The quality of information is paramount as it directly impacts decision-making and organizational
performance. It is measured by the motivation it provides for action and its contribution to
effective decision-making. High-quality information creates a managerial impact, leading to
attention, decision, and action.

Information quality is assessed across four key dimensions:

• Utility: Subjective to the individual manager in terms of form, time, and access.

• Satisfaction: The degree to which the decision maker is satisfied with the information
determines its quality.

• Error: Errors can arise from incorrect data measurement, collection methods, failure to follow
procedures, data loss, poor validation, or deliberate falsification. Erroneous information is a
serious problem because the decision maker might be unaware of it.

• Bias/Impartiality: Impartial information is collected without preconceived views, prejudices,

or specific motives.

• Validity: The information meets the specific purpose of decision-making for which it was
collected.

Beyond these dimensions, other attributes of information include its accuracy (how closely it
represents a situation), form of presentation (qualitative/quantitative, numeric/graphic,
summarized/detailed), frequency of reporting, scope of reporting (entities, area, range), time scale
(past, current, future), and relevance to decision making.

Ensuring information quality involves proper systems analysis, suitable information system
design, continuous maintenance, and regular audit checks. The quality of inputs to the MIS must
be controlled for factors such as impartiality, validity, reliability, consistency, and age.

Value of Information
Information possesses a perceived value primarily in its utility for decision-making. "Perfect
information" would completely eliminate uncertainty or risk, though this is considered a myth. The
value of information is only realized by those who have the capability to use it in a decision.
Experienced managers may need less information, as their experience already reduces uncertainty. In
MIS, the concept of information value is used to determine if the benefit of additional information
justifies its collection; its value is generally lower for operational and middle management decisions,
but very high for strategic and tactical decisions at higher management levels. Beyond monetary
value, information also has value as a strength in promoting management functions, such as
motivating futuristic thinking, confirming beliefs, or reinforcing appropriate decision-making
processes.

General Model of Human as an Information Processor

A manager or decision maker functions as an information processor, using sensory receptors (like
eyes and ears) to acquire information, which is then transmitted to the brain for processing and
storage. This processing leads to a response, which could be a decision, an action, or a recognition of
an event for future use.

Key aspects of human information processing include:

• Filtering: Managers selectively accept inputs that their mental ability can manage. This filtering
can be based on a frame of reference (e.g., knowledge, experience), universally accepted
decision procedures, or by focusing only on important factors. Filtering blocks unwanted or
inconsistent data. Inexperienced managers might inadvertently omit or distort data through
this process, leading to incorrect inferences.

• Individual Differences: Managers differ in their cognitive style, which is their unique method
of perceiving, organizing, and processing data based on their frame of reference, confidence in
decision procedures, and available time. These differences are influenced by managerial
ability, skills, and tools. Research shows that factors such as locus of control, personal
dogmatism, risk propensity, tolerance for ambiguity, manipulative intelligence, and
decision-making experience and management style contribute to these individual
differences.

An effective MIS design must accommodate these individual styles and provide information in a
manner that supports them fully. Ideally, the design should cater to knowledgeable, frequent users,
while providing support for novices to acquire the necessary skills.

System Related Concepts, Elements of a System, and

Types of System
A system is defined as a set of elements arranged in an orderly manner to accomplish an
objective. It is not a random arrangement but is governed by logic, rules, regulations, principles, and
policies, all influenced by the system's objectives.

Elements of a System
Any system, regardless of its field, typically comprises three basic, orderly arranged parts:

1. Input: Data or resources received by the system (e.g., raw materials, financial transactions,
instructions).

2. Process: The transformation mechanism that converts inputs into outputs (e.g.,
manufacturing, data processing, accounting principles).
 3. Output: The desired results that achieve the system's objectives (e.g., finished goods,
information, profits).

Beyond these core parts, systems operate within an environment that can influence their design and
performance. A system also has defined boundaries that establish its scope and coverage, which are
crucial for clearly explaining its components and their arrangement.

A critical element of a system is control, which can be internal or external. Control mechanisms are
based on feedback (positive or negative) that compares the actual output with a standard or norm. If
deviations occur, the control system initiates actions on the input or process to restore equilibrium.
The MIS model incorporates this control feature for quality assurance, with the manager or
decision maker acting as the corrective unit.

Types of Systems
Systems can be classified in various ways:

• Subsystems: A larger system can be decomposed into smaller, logically ordered subsystems.
This decomposition can be serial (output of one is input to the next) or matrix-based (multiple
inputs/outputs across subsystems). Breaking a system into a hierarchical structure aids
structured analysis.

• Deterministic System: A system where inputs, processes, and outputs are known with
certainty, allowing for predictable outcomes (e.g., an accounting system).

• Probabilistic System: A system where outputs can only be predicted in probabilistic terms,
and its behavior is not fully predictable (e.g., a demand forecasting system).

• Open System: Interacts continuously with its internal and external environment and is self-
organizing to meet changing information needs. MIS, by nature, is an open system.

• Closed System: Operates in a known environment with a predetermined set of decision

alternatives and their outcomes. The manager has a model or rule to generate, test, and rank
alternatives. MIS strives to transform open systems into closed ones by providing
comprehensive information support.

Classes of Systems within MIS

MIS encompasses various classes of systems, each serving distinct purposes:

• Data Processing System (DPS): Designed to capture, collect, or enter raw data, process it to
ensure completeness, correctness, and validity, and then organize it for further processing. An
example is an employee's daily attendance system for payroll.

• Transaction Processing System (TPS): Handles interactions or "transactions" between

parties, using data files and records to process and update various other records. Paying
monthly salaries is an example of a transaction in a payroll system.
 • Application Processing System (APS): Built upon DPS and TPS, it uses their outputs to
execute specific applications (e.g., billing customers). It produces documents, reports, or
results for further processing in business functions.

• Business Function Processing System (BPS): Focuses on aiding business functions and
supporting management decision-making within a function's scope. It generates MIS reports
for areas like sales, production, or materials management, integrating outputs from relevant
APS and TPS.

• Integrated Information Processing System (IPS): Sits at the top, drawing inputs from DPS,
TPS, APS, and BPS. It applies information processing rules to support top management in
planning, budgeting, and strategic control (e.g., project planning, capital budgeting). IPS is
further used for Executive Information Systems (EIS), data warehousing, data mining, and
knowledge processing systems.

Role and Importance of Management: Introduction,

Levels and Functions of Management
Management is a process that involves a series of steps: planning, organizing, staffing,
coordinating, directing, and controlling. While all steps are necessary, control is particularly
crucial for ensuring that planned activities align with actual activities to achieve stated goals.
Management experts view these steps as a "Management Control System," emphasizing the necessity
of effective control for objective achievement.

Levels and Functions of Management

The information requirements and the way MIS supports management vary significantly across
different hierarchical levels:

• Top Management:

o Functions: Primarily involved in goal setting, strategic planning, and evolving

business plans and their implementation. Their decisions are often characterized by
total uncertainty due to insufficient knowledge of the external environment and long-
term forecasting difficulties.

o Information Needs: Requires key information of a higher degree of accuracy, often

strategic in nature. They need information that provides insight into trends, patterns,
causes, and effects for strategic analysis and decision-making. This information is
largely external and highly summarized.

o MIS Support: MIS aids top management in strategic management of business, focusing
on strategy formulation, implementation, monitoring, and evaluation. It uses
knowledge-based systems, Business Intelligence (BI), Data Warehousing, Data
Mining, and Executive Information Systems (EIS) to provide the necessary support.

• Middle Management:
 o Functions: Responsible for short-term planning, target setting, and controlling
business functions. Their decisions are typically made under risk due to partial or
probabilistic knowledge of events.

o Information Needs: Requires a mix of internal and external information, often

analytical. Needs "knowledge information" that cuts across functional boundaries and
shows trends over time, forcing action.

o MIS Support: MIS provides operational data for planning, scheduling, and control. It
offers Decision Support Systems (DSS) for problem-solving, model building, and aid in
determining actions like economic order quantity.

• Junior Management / Operational Management (including Supervisory):

o Functions: Deals with operational data for planning, scheduling, and control, and
makes decisions at the operations level to correct out-of-control situations. Their
decisions are often under certainty as they have good knowledge of events and
predetermined alternatives.

o Information Needs: Requires detailed, current, and mostly internal information,

usually in a fixed format, to assess activity status and make day-to-day decisions.

o MIS Support: MIS helps clerical personnel with transaction processing and basic
queries. For junior management, MIS can be designed to make and even execute
programmed decisions based on rules.

Structure and Classification of MIS, Components of MIS,

Framework for Understanding MIS
Structure and Classification of MIS
The conceptual view of MIS is often represented as a pyramid, symbolizing its hierarchical nature
and progression from data to actionable insights. The physical view of MIS is an assembly of several
subsystems built upon databases within the organization. These subsystems perform various tasks,
from data collection and transaction processing to analysis and information storage. They can operate
at a functional level or a corporate level, providing information for both departmental and corporate
management.

A general model of MIS arranges data processing and information systems in an orderly manner to
support management in achieving business objectives. This model inherently involves crossing the
boundaries of the organization to draw data from external sources. It operates on the principle of
feedback and control, specifically using the "control by exception" method, where significant
deviations are highlighted for managerial attention. MIS is designed as an open system, continuously
interacting with its environment and self-organizing to adapt to changing information needs.

The elements of MIS typically include:

 • Computer hardware.

• Communication channels.

• Software and software tools.

• A development plan.

• A well-defined, measurable objective consistent with the organization's business objectives.

In the contemporary business environment, modern MIS is structured as a superstructure built upon
Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer
Relationship Management (CRM) systems. These underlying systems act as sources of real-time
operational information. The MIS superstructure itself includes advanced components such as:

• Data warehousing and data mining systems.

• Executive Information Systems (EIS).

• Online Analytical Processing (OLAP) and query processing tools.

• Decision Support Systems (DSS).

• Knowledge Management Systems (KMS).

Framework for Understanding MIS: Robert Anthony's

Hierarchy of Management Activity (Implicitly Covered)
While the source doesn't explicitly name "Robert Anthony's hierarchy," it clearly outlines how
information requirements and the role of MIS align with different levels of management within an
organization:

• Top Management (Strategic Level): Focuses on goal setting, strategic planning, and overall
business direction. Information needs at this level are strategic, highly summarized, and
often external, dealing with future trends and long-term uncertainty. MIS supports them with
knowledge-based systems, Business Intelligence, and Executive Information Systems.

• Middle Management (Tactical/Management Control Level): Concerned with short-term

planning, target setting, and controlling business functions. Their decisions often involve
risk, requiring analytical information that blends internal and external data. MIS provides
Decision Support Systems and analytical reports to aid in these tasks.

• Lower Management (Operational Control/Transaction Processing Level): Involved in day-

to-day operations, transaction processing, planning, scheduling, and control at a micro-
level. Their decisions are typically under certainty and often programmed. Information needs
are detailed, current, and largely internal, often provided in fixed formats. MIS supports them
with Transaction Processing Systems (TPS) and automated rule-based decision-making.
Decision-Making Concept
A decision is fundamentally defined as the choice made from several available options by a
decision maker to achieve a specific objective in a given situation. In the context of business,
decisions are those made to achieve the organization's objectives within its operational environment.

Key characteristics of business decision-making include:

• Sequential nature.

• High complexity due to inherent risks and trade-offs.

• Influence by personal values of the decision maker.

• Made within institutional settings and the broader business environment.

The process of decision-making demands creativity, imagination, a deep understanding of human

behavior, and foresight to predict post-decision implications, along with a willingness to face them.
While decisions aim to solve a problem, they can also give rise to new problems over time. The
concept of a "rational decision" implies that the decision maker can explain their choice with logic
and reason, considering the objectivity and circumstances under which the decision was made.
Rationality is best ensured when the decision-making process is carried out systematically.

Types of Decisions
Decisions can be categorized based on the degree of knowledge the manager possesses about the
outcomes or future events:

• Decision-Making under Certainty: Occurs when the manager has full and precise
knowledge of the event or outcome. This situation is common in operations management,
where events are predictable and decision alternatives are often predetermined.

• Decision-Making under Risk: Applies when the manager has partial or probabilistic
knowledge of outcomes. This is typical at the middle management level, where forecasting is
challenging but not entirely unknown.

• Decision-Making under Uncertainty: Characterized by a complete lack of knowledge about

outcomes. This situation is most common at the top management level, due to insufficient
knowledge of the external environment and difficulties in long-term business forecasting.

A well-designed MIS aims to transform decision-making situations from uncertainty to risk, and
further to certainty, by providing more information.

Decisions are also classified by their structure:

• Programmed (Structured) Decisions: These decisions are rule-based and can be made using
a predefined method or guidelines. They are suitable for computerization, as inputs,
processing methodology, analysis, and decision choices are predetermined. MIS can be
designed to make and even execute these decisions, and their effectiveness can be
 continuously analyzed and refined. Programmed decisions can be delegated to lower
management levels.

• Non-programmed (Unstructured) Decisions: These decisions cannot be made using a fixed

rule or model and are often infrequent but involve significant stakes. They typically require the
user to go through the entire decision-making cycle (like Herbert Simon's model) each time. For
non-programmed decisions, MIS provides decision support systems rather than direct
solutions, helping identify problems and offering relevant information.

Methods of Choosing Among Alternatives

Decision-making involves evaluating various alternatives. MIS and decision support systems leverage
several methods and tools for this purpose:

• Optimization Techniques: These are mathematical models used in situations where the
decision-making environment is "closed" and deterministic. Examples include Linear
Programming, Integer Programming, Dynamic Programming, Queuing Models, Inventory
Models, and Capital Budgeting Models. They aim to optimize the use of resources under
specific constraints, for instance, balancing inventory carrying costs with ordering costs.

• "What If" Analysis: This method tests the decision alternative for functional relationships
between the factors considered in the problem. It allows the decision maker to explore how
changes in one variable affect the outcome.

• Sensitivity Analysis: Used to test the validity of a solution under variable conditions, such as
changed assumptions or relaxed constraints. It helps assess the criticality of a factor based
on its impact on the solution.

• Goal Seeking Analysis: Instead of fixing the output and seeing inputs, this method aims to
achieve an optimum value for a goal after satisfying all operating constraints. It helps identify
critical constraints and ways to improve the solution to reach the highest possible goal.

• Payoff Analysis: Used in competitive analysis, providing analysis based on potential gains,
regrets, and utility.

Role of MIS in Decision Making

MIS plays a dominant and vital role in supporting decision-making across all levels of
management. Its objective is to provide information that effectively aids decision-making, ensuring
business goals are achieved efficiently.

Key aspects of MIS's role in decision-making include:

• Support for the Management Process: MIS supports every step of management—planning,
organizing, staffing, directing, coordinating, and control—by aiding the decisions required at
each stage.

• Implementation of Simon's Model: MIS provides a conceptual design aligned with Herbert
Simon's three phases of decision-making:
 1. Intelligence Phase: MIS collects, scans, processes, and presents data, highlighting
problem situations by identifying significant deviations between actual and expected
results.

2. Design Phase: The system provides models that enable managers to generate and test
different decision alternatives and assess their implementation feasibility.

3. Choice Phase: MIS assists in evolving selection criteria and applying them to
alternatives to choose the best option. Ideally, an MIS is designed to make decisions for
the manager.

• Handling Programmed Decisions: MIS serves as an excellent tool for programmed decisions,
where it can be designed to make and even execute rule-based decisions, transferring this
responsibility from the decision maker to the system.

• Support for Non-programmed Decisions: For non-programmed decisions, MIS provides

decision support systems to handle the variability and complexity involved, offering
generalized decision-making models.

• System Flexibility: The design of MIS accounts for both closed (deterministic, rule-based) and
open (flexible, dynamic) decision-making systems, ensuring appropriate support for varying
conditions.

• Integration of Analytical Tools: MIS can directly incorporate decision-making methods and
Operations Research (OR) models for optimization, as well as payoff analysis for competitive
scenarios.

• Addressing Human Factors: MIS design considers organizational and behavioral aspects of
decision-making, including human limitations like risk aversion and uncertainty avoidance,
and supports organizational learning.

• Enhanced Capability: By providing adequate information support, MIS improves a manager's

risk perception and helps to transform decision-making scenarios from uncertainty to risk
to certainty. This enhances the collective effectiveness and productivity of the organization's
people.

Simon's Model of Decision Making

Herbert Simon's model describes the core process of decision-making in three fundamental
phases. MIS development often follows this model as its conceptual design:

1. Intelligence Phase: In this initial phase, raw data is collected, processed, and examined.
The primary objective is to identify a problem that requires a decision. MIS supports this by
scanning, checking, editing, sorting, merging, computing, and summarizing data, drawing the
manager's attention to problematic situations by highlighting deviations from expectations or
targets.

2. Design Phase: Once a problem is identified, the manager invents, develops, and analyzes
different decision alternatives. This phase involves testing the feasibility of implementing
 these alternatives and assessing the potential value of their outcomes. The manager
essentially builds a model of the problem situation to generate and evaluate solutions.

3. Choice Phase: In this final phase, the manager selects one alternative from those developed
in the design phase, based on predetermined selection criteria such as maximizing profit,
minimizing cost, or achieving the highest utility. If a satisfactory decision is not reached, the
process can iterate back to the intelligence phase to gather more data, refine the model, or
adjust criteria.

An ideal MIS is envisioned to seamlessly guide the manager through these phases, or even make the
decision automatically, particularly for well-defined problems.

Structured and Unstructured Decisions

Decision-making situations can be broadly categorized based on their complexity and the availability
of predefined processes:

• Programmed (Structured) Decisions: These are decisions that can be based on a rule, a
specific method, or a set of guidelines. Because the inputs, processing methodology,
analysis, and choice of decision-making are predetermined, these decisions are suitable for
computerization. In such cases, the MIS itself can be designed to make and even execute the
decision (e.g., reordering inventory when stock levels reach a certain point). The effectiveness
of the rules can be continually analyzed and modified, and such decisions can be delegated to
lower management levels.

• Non-programmed (Unstructured) Decisions: These are decisions that cannot be made

using a predefined rule or a fixed model. They are typically infrequent but involve larger
stakes, and thus cannot be easily delegated to lower levels. For these complex situations, the
MIS cannot provide a direct solution but rather offers decision support systems (DSS). DSS
help in identifying the problem and providing relevant information to assist the decision maker
in navigating the situation through a process akin to Simon's iterative model.

Development of MIS: Stages in the Development of MIS,

System Development Approaches
The development of MIS is a systematic process aimed at transforming user needs into effective
software solutions. A long-range MIS plan is essential for success, providing direction and aligning
with the organization's broader business plans.

Stages in the Development of MIS

The system development cycle for a new MIS application generally consists of five major stages:

1. Definition of the System and its Objective: This initial stage involves clearly defining the
system, its elements, boundaries, and scope, and setting objectives that are consistent with
business goals. This ensures clarity for both users and designers.
 2. Development of the System: This is a multi-step phase encompassing:

o System Analysis: Understanding existing business systems, identifying problems, and

defining information requirements as support for decision-making. It also involves
examining the technical, economic, and operational feasibility of the system.

o Conceptual Design: A post-feasibility understanding of the system's process.

o Initial Prototype: A critical step where a basic system is developed to ensure it meets
core information needs and to refine requirements.

o Structured Break-up: Decomposing the system into smaller, hierarchical subsystems

or processes.

o Detailed Design: Designing outputs, inputs, processing logic, procedures, flow

charting, documentation, database architecture, and application development.

o Module Development: Breaking the system into logical program modules (e.g., data
entry, validation, processing, reporting) and developing them.

o Testing: Developing and executing test data and cases (white box and black box testing)
to confirm the design's satisfaction and suggest modifications.

3. Installation of the System: Involves installing the system on hardware and conducting
thorough operational testing before exposing it to users in a live mode.

4. Operations of the System: The system is put into live use to support business operations.

5. Review and Evaluation: Post-implementation, the system is periodically reviewed through

audits and change management systems to ensure quality and address necessary
modifications. This phase is crucial for long-term system utility.

System Development Approaches

Several methodologies are employed for MIS development:

• Waterfall Model: A traditional, sequential software development method where each phase
must be completed before the next begins (requirements, design, implementation, verification,
maintenance). It is generally suitable for stable systems where requirements are well-defined
from the outset.

• Prototyping Approach: Used for complex systems, this involves progressively determining
information needs and developing a methodology. A small-scale prototype is built and tested
to identify problem areas and inadequacies, which are then addressed through iterative
refinement. This approach emphasizes user interaction and adapting to changing needs.

• Iterative Enhancement Model: While not explicitly detailed as a standalone model, the
iterative nature is inherent in prototyping and the spiral model, implying continuous refinement
and improvement based on feedback.
 • Spiral Model: This development model is good for evolving and continuously changing
systems. It integrates elements of prototyping and sequential development, with cycles of
planning, risk analysis, engineering, and evaluation [286, Fig. 8.20]. Boehm's model is
mentioned in the context of expert systems and development stages.

Other significant approaches include:

• Structured Systems Analysis and Design (SSAD): A traditional method (e.g., by Ross,
Yourdon) that deals with functions and data separately. It develops conceptual, logical, and
graphical models using symbols like Data Flow Diagrams (DFDs). While easy to understand,
SSAD systems can be difficult to maintain if data formats change, as functionality is rigidly tied
to data definition.

• Object-Oriented Analysis (OOA) and Object-Oriented Systems Analysis and Design

(OOSAD): A modern methodology that views functions and data together as an object. It
models business operations into objects, where an object class can handle various related
items (e.g., an 'ORDER' object class for all types of orders). OOSAD uses a "use case driven"
approach, identifying "actors" (users) and "use cases" (transactions). It involves building multi-
layered architectures (Business, View/User Interface, Access Layers) and utilizes the Unified
Modeling Language (UML) for specifying, visualizing, constructing, and documenting software
systems through various diagrams (class, sequence, collaboration, state chart, activity).
OOSAD is considered more flexible and easier to maintain than SSAD.

Applications of Information Systems in Functional Areas

Information systems are applied extensively across an organization's functional areas, with a typical
system starting with Online Transaction Processing (OLTP), using Relational Database Management
Systems (RDBMS), and supporting query and report generation. The focus of application development
is on accounting, querying, analysis, and control. When these functional systems are integrated, they
provide cross-functional information for business planning at middle management and strategic
planning at top management levels.

1. Marketing MIS:

o Scope: Covers identifying consumer needs, product concept evolution, product design,
market positioning, and sales strategies.

o Applications: Market research, consumer surveys, advertising, sales promotion

campaigns, product stocking, and developing dealer/distributor networks.

o Accounting: Builds basic data for statutory compliance and operations updates,
covering sales, product family, sales value, taxes, dealers, customers, market
segments, and returns.

o Query: Supports inquiries on customers, products, prices, stock, sales, and cumulative
sales statistics, including order pending status and stock allocation.

o Decision Analysis: Supports rule-based decisions like pricing, stock allocation, order
acceptance, discounts, and commission. It also aids complex strategic decisions such
 as price changes, new product introductions, packaging, and distribution channel
changes, which have long-term effects on marketing performance.

o Reports: Generates functional information (e.g., sales analysis, order tracking,

competition analysis) for various levels, often in summarized, fixed formats, classified
by factors like customer, product, market segment, and geographic zones.

2. Financial MIS:

o Scope: Manages financial operations and provides financial status analysis for
decision-making.

o Accounting: Accounts for sales, purchases, salaries, inventory, expenses, capital

purchases, fixed deposits, shareholder funds, various taxes, consumption, budgets,
and fixed assets.

o Query: Processes inquiries on main and subsidiary accounts, locations, and

documents to show current status.

o Decision Analysis: Supports decisions on short-term working capital, sources of

finance, debtor/creditor analysis, credit term revisions, capital budgeting, and
investment selection. Applications include cash flow analysis, sources and uses of
funds, aging reports, budget analysis, ratio analysis, and cost analysis.

o Control: Exercises control based on exceptions found in business operations, such as

unutilized capacity, inventory turnover, delayed receivables, and cash flow deviations.

3. Production MIS:

o Scope: Accounts for and manages production quantity, quality, rejections, breakdown
incidents, labor complements, power/fuel consumption, machine/facility utilization,
and labor hours.

o Decision Analysis: Supports numerous long-term and short-term decisions, including

make-or-buy, make-or-subcontract, alternative material/process use, optimum
product/job mix, rescheduling and loading jobs, selection of production facilities, and
maintenance policies.

o Applications: Utilizes programming models, simulation techniques, Material

Requirement Planning (MRP) systems, Artificial Intelligence (AI), and knowledge-based
systems for continuous analysis and decision support.

o Control: Reports highlights (planned vs. actual) on critical production aspects, enabling
junior management to make quick decisions (e.g., extending production hours,
rescheduling jobs).

4. Personnel MIS:

o Scope: Manages human resources, with the primary objective of providing suitable
manpower and controlling personnel costs while increasing productivity.
 o Applications: Manpower planning, recruitment, performance appraisal, training and
development, payroll, employee welfare, and grievance handling.

o Information Categories: Includes employee information (profile, skills, history),

organizational structure, performance records, and cost analysis.

o Reports: Generates statutory reports (attendance, employee strength), analytical

reports (accident analysis, cost analysis), and action reports (recruitment, workload
acceptance, reorganization). Most application development in PM is standard and rule-
based.

Decision Support Systems (DSS)

A Decision Support System (DSS) is a special class of system used to support the process of
decision-making, rather than always providing the decision itself. DSS applications are a direct
application of Herbert Simon's model of decision-making (Intelligence, Design, and Choice). They
are particularly helpful in the intelligence phase for problem identification and in the design phase for
generating solutions.

Definition and Characteristics

• Definition: DSS refers to systems that aid in the decision-making process. They are designed
to support situations where managers require diverse information, and where information
demands might continuously change as a decision maker gains new insights.

• Characteristics:

o Typically developed jointly by users and system analysts.

o Draws principles from economics, science, engineering, and management tools.

o Utilizes data from internal information systems and external sources.

o Often developed as independent system subsets of the main Management

Information System.

o Commonly used to test decision alternatives and perform sensitivity analysis on

various problem parameters.

o A significant advantage is their ability to sensitize decisions and assess implications

on results or business performance.

o Focuses on critical business issues and can enable delegation of decision-making to

lower levels once tools and models are validated.

MIS versus DSS

While MIS broadly aims to satisfy organizational information needs, DSS fills a specific gap:
 • Sufficiency: Existing information systems and conventional MIS are often insufficient for
meeting all decision-making needs, especially for complex, one-off scenarios. Managers
may still need additional analysis and models that MIS doesn't natively provide.

• Beyond Reporting: While MIS focuses on generating periodic reports and exception reports
(e.g., on target achievement), DSS goes further by providing inquiry and analysis systems for
more complex decision-making.

• Capability Enhancement: The single largest benefit of DSS is that it elevates the decision
maker's capability to make rational decisions. It equips managers with the ability to:

o View complex scenarios, design models, develop alternatives, test solutions, and
conduct sensitivity analyses.

o Make better decisions due to quick analysis, modeling, and testing.

o Control the risk exposure inherent in decisions.

• Database Construction: DSS enables managers to construct databases for ad hoc queries,
reporting, analysis, viewing, and modeling data, thereby helping them execute Simon's
"Intelligence – Design – Choice" process.

• Integration: DSS can be an internal part of MIS, particularly for real-time, dynamic decision
needs where rules are embedded (e.g., automated order acceptance based on credit ratings).
However, complex, strategic decisions requiring multi-dimensional analysis with internal and
external data are often kept outside the main MIS design scope.

Tools and Models for Decision Support

DSS utilizes a variety of tools and models, often stemming from behavioral studies, management
science, and operations research:

• Types of DSS (Based on Function):

o Status Inquiry Systems: Provide basic information where knowing the status
automatically leads to a decision (e.g., stock levels).

o Data Analysis Systems: Perform comparative analysis using formulas or algorithms,

often unstructured (e.g., cash flow analysis, inventory analysis).

o Information Analysis Systems: Generate information reports, sometimes with

exceptions, for situation assessment (e.g., sales analysis, MRP systems).

o Accounting Systems: Track major business aspects, providing formal reports (e.g.,
cash, inventory, payroll).

o Model-Based Systems: Use simulation or optimization models for one-time or

infrequent decisions, providing general guidelines (e.g., product mix, job scheduling).
• Behavioral Models: Help understand relationships between business variables (e.g., trend
analysis, forecasting, statistical analysis, regression models). They can set alert points for
decision makers.

• Management Science Models: Developed from principles of business management,

accounting, and econometrics. These include budgetary systems, cost accounting systems,
capital budgeting, ABC analysis, MRP systems, production planning and control, and
manpower planning. They can be directly used in DSS design.

• Operations Research (OR) Models: Mathematical models representing real-life problems

through algebraic equations. Examples include models for minimum weight design, shortest
travel routes, optimum product mix, cost minimization, job assignment, and site
selection. Inventory Control Models (e.g., FOQ, ROL, Periodic Review, ABC Analysis) are also
significant OR applications.

• Spreadsheet Packages: Widely used for data structuring, analysis, and graphical
presentation, particularly for financial and sales-profit models.

• Procedural Models: Based on well-defined rules and procedures, where decisions are made
only if certain conditions are met (e.g., inventory reordering procedures).

• Group Decision Support Systems (GDSS): Designed for situations requiring group
participation in decision-making. They facilitate computer-based discussions, instant
anonymous voting, simultaneous user interaction, and automatic recording of information for
future analysis, building organizational memory. They support both structured and
unstructured problem-solving.

• Artificial Intelligence (AI) Systems: Intelligence supported by knowledge and reasoning

abilities. AI systems categorize into Expert Systems (knowledge-based), Natural Language
Systems, and Perception Systems. They apply software techniques to non-numeric data,
using symbolic processing, reasoning, and conceptual modeling for problems like
configuration, design, diagnosis, and forecasting.

• Knowledge-Based Expert Systems (KBES): A subset of AI, used for unstructured problem-
solving within a specific knowledge domain. KBES comprise a Knowledge Base (facts, rules,
judgments, experience), an Inference Mechanism (to interpret knowledge and make logical
deductions), and a User Control Mechanism. Knowledge can be represented using Semantic
Networks, Frames, and Rules (e.g., "If-Then" statements).

• DSS in E-enterprise: Applied in areas like Supply Chain Management (SCM) to optimize
costs (e.g., location decisions, inventory parameters, transportation modes), and Customer
Relationship Management (CRM) for customer-centric decisions (e.g., pricing, product
differentiation, payment options). They also form part of Executive Information Systems (EIS)
to support strategic management by providing insights into new and complex problems.

• Knowledge Management Systems (KMS): Seen as an extension of MIS, particularly when an

organization reaches maturity in its MIS usage and aims to become a "learning organization."
KMS initiatives are taken when business becomes knowledge-driven, beyond just information-
driven, supporting mission-critical applications and leveraging organizational competency.