Information Systems

What is an Information System?

• An Information System (IS) is a set of components that
work together to collect, process, store, and
disseminate information to support decision-making,
coordination, control, analysis, and visualization in an
organization.
 Components: people, HW, SW, Data, Procedures, networks…
 Collect raw data: internal & external sources, i.e Sales, customer
feedback, inventory levels, website clicks
 Process data into meaningful information
 Store data for easy retrieval, backup and auditing
 Disseminate information: reports, dashboards, notifications, emails
 Decision making (informed choices), Coordination (team work),
Control (monitoring performance & ensures goals are met)
 Types of systems
• Transaction Processing Systems (TPS) *Handle routine,
day-to-day operations -(Operational staff)
• Management Information Systems (MIS) *Summarize
data from TPS to aid middle management -(Professionals,
analysts) (Middle managers)
• Decision Support Systems (DSS) * Help in non-routine
decisions using analytical models (Professionals, analysts)
• Executive Information Systems (EIS) *Provide top-level
summaries for strategic decisions -(Senior executives)
• Enterprise Resource Planning (ERP) Systems *Integrate all
business functions in one system -(Entire organization)
 Why Study Information Systems?
• To Understand How Technology Supports
Organizations - you learn how systems are used to
manage data, automate tasks, and support
operations.
• To Improve Decision-Making - provides real-time,
accurate information that helps managers and
stakeholders make smart decisions.
• Information Systems knowledge opens doors to a
wide range of careers.
• IS helps automate repetitive tasks, reduce errors, and
save time - Organizations become more efficient and
competitive by using well-designed systems.
• To Support Innovation and Business Growth -
Companies use IS to create new products,
enter new markets, and improve customer
experiences.
• To Understand Data and Cybersecurity -
Studying IS equips you with knowledge on data
protection, privacy, and cybersecurity
measures.
• To Adapt to the Digital World - understanding
IS helps you stay relevant and competitive.
• To Bridge the Gap Between Business and IT
 The role of IS in business
• Support for Business Operations
– IS automates routine and repetitive tasks, such as
payroll, order processing, and inventory control.
– Reduces manual work, errors, and time delays.
• Decision Support
– IS provides timely, accurate, and relevant information
to managers.
– Helps with planning, forecasting, and solving complex
problems through Decision Support Systems (DSS).
• Enhancing Communication and Collaboration
– IS enables internal communication (emails,
messaging, video conferencing) and external
communication (with customers and suppliers).
– Promotes teamwork and coordination across
departments and locations.
• Improving Customer Service
– IS helps businesses respond quickly to customer
inquiries, track orders, and personalize services.
– Customer Relationship Management (CRM) systems
help build long-term customer loyalty.
• Facilitating E-Commerce and Online Business
– IS supports online buying and selling, digital payments,
product recommendations, and secure transactions.
– Enables businesses to reach global markets.
• Increasing Productivity and Efficiency
– IS reduces waste, speeds up processes, and lowers
operational costs.
– Workflow automation allows staff to focus on higher-
value tasks.
• Gaining Competitive Advantage
– Businesses use IS to innovate, differentiate their
products/services, and respond faster to market changes.
– Tools like Business Intelligence (BI) and data analytics help
predict trends and customer behavior.
 Data, information & Knowledge
• Data:
– Data refers to raw, unorganized facts or observations
that are typically collected or generated through
various processes.
– Data can take different forms, including numbers, text,
images, audio, and video.
– Examples of data include customer names,
transaction amounts, temperature readings, or stock
prices.
– Data, in its raw form, lacks context and meaning. It
needs to be processed and organized to become
useful information.
• Information:
– Information is data that has been processed,
organized, and presented in a meaningful context,
making it useful for decision-making or
understanding.
– Information provides answers to specific questions,
reveals patterns or trends, and helps users understand
relationships between different data points.
– Unlike data, which is often raw and unstructured,
information is structured and formatted for human
comprehension and utilization.
– Examples of information include sales reports,
financial statements, weather forecasts, or analysis of
customer demographics.
• Knowledge
– The application of information, combined with
experience, context, and understanding, to make
decisions or solve problems.
– For example, a bank officer uses past loan data and
customer history (information) to decide whether to
approve a new loan (knowledge in action).
– Knowledge is supported by knowledge management
systems, decision support systems (DSS), and expert
systems.
– These systems help convert organizational
experience and insights into actionable strategies.
 Business information processing
• Business information processing involves
various activities aimed at collecting,
storing, processing, analysing, and
disseminating information to support
business operations and decision-
making.
 Types of business information processing
• Data Collection:
– Gathering raw data from various sources, such
as transactions, sensors, surveys, social media,
or external databases.
– Data collection methods include manual entry,
automated data capture systems (e.g.,
barcode scanners), online forms, and APIs
(Application Programming Interfaces) for
accessing external data sources.
• Data Storage:
– Storing collected data in databases, data
warehouses, or other storage systems.
– Data storage involves organizing data in a
structured format to facilitate efficient
retrieval and analysis.
– Different storage technologies include
relational databases, NoSQL databases, cloud
storage, and file systems.
• Data Processing:
– Manipulating and transforming data to
extract useful information.
– Data processing activities include sorting,
filtering, aggregating, calculating,
summarizing, and joining data sets.
– Processing may involve both batch
processing (e.g., nightly data updates) and
real-time processing (e.g., processing
transactions as they occur).
• Data Analysis:
– Examining data to identify patterns, trends,
correlations, and insights.
– Data analysis techniques include descriptive
statistics, data visualization, predictive
modelling, machine learning, and data
mining.
– Analysis helps businesses understand their
performance, customer behaviour, market
trends, and opportunities for improvement.
• Information Generation:
– Generating meaningful information from
processed data to support decision-making.
– Information may take the form of reports,
dashboards, key performance indicators
(KPIs), alerts, and visualizations.
– Information is often tailored to specific user
roles and needs, providing relevant insights
for managers, executives, analysts, and other
stakeholders.
• Information Dissemination:
– Distributing processed information to
relevant stakeholders through various
channels.
– Dissemination methods include email
reports, web portals, mobile apps,
collaboration tools, and presentations.
– Timely and accurate dissemination ensures
that decision-makers have access to relevant
information when and where they need it.
• Information Security:
– Implementing measures to protect data and
information from unauthorized access,
alteration, or disclosure.
– Security measures include encryption, access
controls, authentication, audit trails, and
disaster recovery planning.
– Information security is critical for maintaining
the confidentiality, integrity, and availability of
business data and systems.
 Properties of good information
• Accuracy – Information should be correct and free
from errors to ensure reliable decision-making.
• Completeness – It should contain all necessary
details to avoid misinterpretation or incomplete
conclusions.
• Relevance – The information must be applicable to
the specific situation or purpose for which it is
needed.
• Timeliness – Information should be available when
needed, ensuring it is up to date and useful for
current decisions.
• Reliability – It should come from credible sources and
be consistent over time.
• Conciseness – Information should be presented in a
clear and concise manner without unnecessary
details.
• Accessibility – It should be easily available to
authorized users without excessive barriers.
• Cost-effectiveness – The value derived from the
information should outweigh the cost of obtaining it.
• Understandability – It should be presented in a
format that is easy to comprehend by the intended
users.
• Verifiability – It should be possible to confirm the
accuracy and credibility of the information through
evidence or sources.
 Management Information Systems (MIS)
• An MIS is a system that provides managers
with the necessary information to make
decisions about an organization's
operations.
• The MIS gathers data from various sources
and processes it to provide information
tailored to the managers' and their staff's
needs.
• While businesses use different types of systems,
they all share one common goal: to provide
managers with the information to make better
decisions.
• In today's fast-paced business environment,
having access to accurate and timely information
is critical for success.
• MIS allows managers to track performance
indicators, identify trends, and make informed
decisions about where to allocate resources.
Pyramid Diagram
• A typical organization is divided into operational,
middle, and upper level.
• The information requirements for users at each
level differ.
• Towards that end, there are number of
information systems that support each level in an
organization.
• Understanding the various levels of an
organization is essential to understand the
information required by the users who operate at
their respective levels.
 Operational management level
• The operational level is concerned with
performing day to day business transactions of
the organization.
• Examples of users at this level of management
include cashiers at a point of sale, bank tellers,
nurses in a hospital, customer care staff, etc.
• Users at this level use make structured
decisions. This means that they have defined
rules that guides them while making decisions.
 Tactical Management Level
• This organization level is dominated by middle-
level managers, heads of departments,
supervisors, etc.
• The users at this level usually oversee the
activities of the users at the operational
management level.
• Tactical users make semi-structured decisions.
The decisions are partly based on set guidelines
and judgmental calls.
 Strategic Management Level
• This is the most senior level in an
organization.
• The users at this level make unstructured
decisions.
• Senior level managers are concerned with
the long-term planning of the organization.
• They use information from tactical
managers and external data to guide them
when making unstructured decisions.
 Systems used at operational
management level
• Transaction Processing System (TPS)
are used to record day to day business
transactions of the organization.
The main objective of a transaction processing
system is to answer routine questions such as;
– How many printers were sold today?
– How much inventory do we have at hand?
– What is the outstanding due for John Doe?
 Examples of transaction processing
systems include;
• Point of Sale Systems – records daily sales
• Payroll systems – processing employees
salary, loans management, etc.
• Stock Control systems – keeping track of
inventory levels
• Airline booking systems – flights booking
management
 Systems used by tactical managers
• Management Information System (MIS)
to monitor the organization’s current
performance status.
The output from a transaction processing system
is used as input to a management information
system.
The MIS system analyzes the input with routine
algorithms i.e. aggregate, compare and
summarizes the results to produced reports that
tactical managers use to monitor, control and
predict future performance.
 Examples of management information
systems
• Sales management systems– they get input from
the point of sale system
• Budgeting systems – gives an overview of how
much money is spent within the organization for
the short and long terms.
• Human resource management system – overall
welfare of the employees, staff turnover, etc.
• Tactical managers are responsible for the semi-
structured decision.
• MIS systems provide the information needed
to make the structured decision and based on
the experience of the tactical managers, they
make judgement calls i.e. predict how much of
goods or inventory should be ordered for the
second quarter based on the sales of the first
quarter.
 Systems used by senior management
• Decision Support System (DSS)
They use input from internal systems
(transaction processing systems and
management information systems) and external
systems to make non-routine decisions.
The main objective of decision support systems
is to provide solutions to problems that are
unique and change frequently.
• Decision support systems answer questions
such as;
– What would be the impact of employees’
performance if we double the production lot at the
factory?
– What would happen to our sales if a new
competitor entered the market?
• Decision support systems use sophisticated
mathematical models, and statistical
techniques (probability, predictive modeling,
etc.) to provide solutions, and they are very
interactive.
Examples of decision support systems
include;
• Financial planning systems
it enables managers to evaluate alternative
ways of achieving goals.
The objective is to find the optimal way of
achieving the goal.
• Bank loan management systems
it is used to verify the credit of the loan
applicant and predict the likelihood of the
loan being recovered.
 Artificial Intelligence
• Artificial Intelligence (AI) has significantly
transformed Management Information Systems
(MIS) by improving decision-making processes
through:
Automation of Routine Decisions
– AI-powered MIS can automate repetitive and rule-
based decisions, allowing managers to focus on
more strategic and complex problems.
– For example, chatbots and robotic process
automation (RPA) handle customer service queries
and transaction processing.
Predictive Analytics for Strategic Planning
– AI enhances predictive analytics by analyzing large
datasets to forecast trends, risks, and opportunities.
– This helps organizations make data-driven strategic
decisions in areas like market trends, financial risks,
and supply chain optimization.
Enhanced Data Processing and Insights
– AI-driven MIS can process structured and
unstructured data from multiple sources, including
social media, IoT devices, and cloud-based platforms.
– This leads to more accurate insights for decision-
makers.
Real-time Decision Support
– AI enables real-time Decision Support Systems (DSS)
by continuously analyzing incoming data and providing
instant recommendations.
– For example, AI-powered fraud detection systems in
banking can prevent suspicious transactions.
Personalization and Customer-Centric Decisions
– AI in MIS helps businesses personalize services using
machine learning algorithms.
– For instance, e-commerce platforms use AI to
recommend products based on customer behavior.
Risk Management and Anomaly Detection
– AI can identify patterns and anomalies in business
operations, helping managers mitigate risks.
– This is useful in financial auditing, cybersecurity, and
operational efficiency.
AI-Driven Decision Intelligence
– AI combines big data, machine learning, and
deep learning to create Decision Intelligence
(DI)—a framework that enhances human
decision-making with AI-driven insights.