Information and information systems

Concept of Information System

An information system (IS) is a combination of:

People
Hardware (computers and other devices)
Software (programs and applications)
Communication networks (internet and other connections)
Data resources (information and databases)
Policies and procedures (rules and guidelines)

These parts work together to store, retrieve, change, and share information within an organization.

Information systems help to organize and analyze data.
Many organizations handle a lot of data. Data are basic facts or values.
The purpose of an information system is to turn raw data into useful information that can help in making decisions within an organization.

Components of Information Systems

An information system contains the following components:

Hardware: These are the physical parts of a computer system, such as processors, monitors, keyboards, and printers.
Software:
- There are two main types of software: system software and application software.
- System software: This includes the operating system, which manages the computer’s hardware, data, programs, and other resources. It also allows the user to control the computer, usually through a graphical user interface (GUI).
- Application software: These are programs designed to help users perform specific tasks, like MS Word and PowerPoint.
Telecommunications: This involves the technology used to connect different computer systems and devices to share information. Connections can be made using wired methods like coaxial cables and fiber optics, or wireless methods like microwaves and radio waves, which support mobile computing.
Databases (Data Resource): A database is a collection of organized data that can be easily accessed and managed. Examples include employee records and product catalogs.
Human resources and procedures (people): Skilled individuals are essential for any information system. These include technical staff, operations managers, business analysts, system analysts, designers, database administrators, programmers, computer security specialists, and computer operators.

Transaction Processing System (TPS)

Transaction processing systems (TPS) are types of operations support systems. TPS record and process data from business transactions. There are two types of transaction processing:

Batch processing
Real-time (or online) processing

Transactions are events that happen during business operations, like sales, purchases, deposits, withdrawals, refunds, and payments. Information about the customer, product, salesperson, and store must be collected and processed.

The Transaction Processing Cycle

Data Entry: The first step is collecting and storing business data. For example, transaction data may be collected by point-of-sale terminals using bar code scanners and credit card readers at a retail store.
Transaction Processing:
- In batch processing, data from different transactions are collected over time. These transactions are grouped into batches and processed together.
- In real-time (or online) processing, data are processed immediately after the transaction occurs. Examples include ATM transactions and point-of-sale (POS) systems.
Database Maintenance: TPS updates an organization’s databases to keep data correct and up-to-date. This reflects the changes from day-to-day business transactions. For example, credit sales will increase customer account balances and decrease inventory levels.
Document and Report Generation: TPS produces various documents and reports, such as purchase orders, paychecks, sales receipts, invoices, and customer statements.
Inquiry Processing: TPS allows users to make inquiries and receive responses using the Internet, intranets, extranets, and database query languages. For example, you might check the status of a sales order, the balance in an account, or the amount of stock in inventory.

Office Automation System (OAS)

Office automation refers to different computer systems and software used to collect, store, transfer, change, and use office information to complete tasks. Essentially, office automation helps manage data.

Office automation allows data to move without human intervention, reducing human involvement and error, and automating many critical processes. Here are some ways it meets the needs of the modern workplace:

Information storage: Stores information in files, documents, images, spreadsheets, and forms.
Real-time data exchange: Helps share reports between employees and customers and makes email exchanges easy.
Data management: Supports both long-term and short-term data management, including inventory management, financial planning, and marketing management.

Types of Office Automation

Finance and Budgeting: This type of automation tool helps plan financial and budgeting matters with more transparency.
Recruitment: Helps the HR team find the best talent without biases by setting criteria and requirements. It can automate job postings, assessments, candidate evaluations, and interview scheduling.
Security: Protects against digital threats like hacking, malware, and phishing. An OAS can handle cybersecurity risks and recommend needed security actions.
Cloud Infrastructure Automation: Manages cloud storage efficiently. An integrated OAS can automate cloud configuration and provision, saving time and resources.
Project Management: Helps managers delegate tasks, set deadlines, manage and track tasks, and analyze performance.
Procurement: Automates the procurement process, reducing unnecessary activities and maintaining healthy supplier relationships.
Document Processing: Creates and designs printable documents like reports and business proposals. Helps in going paperless.
Voice Automation: Includes answering machines and recorded greeting messages. Can communicate with multiple people efficiently.
Administrative Facilities: Acts as an office administrator, maintaining room temperature, lighting, office inventory, and security.

Using an OAS, an organization can benefit in many ways by optimizing daily office operations and processes in this fast-paced digital era.

Management Information System (MIS)

A Management Information System (MIS) helps top and middle management make informed decisions by analyzing available data and predicting scenarios. It's a computer-based system that provides information for decision-making within an organization.

Functions of MIS

Collecting data: Gathers information needed for decision-making.
Storing data: Keeps the collected data safe for later use.
Updating data: Makes sure the information is current and accurate.
Processing data into information: Converts data into usable insights.
Report generation: Creates reports summarizing the processed information.

Components of MIS

Data Capturing: Collects necessary data.
Data Storage: Stores collected data for easy access.
Data Processing: Turns data into meaningful information.
Information Reporting: Converts processed data into readable form.
Decision Support: Helps managers make decisions based on information.
Control Support: Assists in controlling business functions.
Modeling and Simulation: Shows potential outcomes of decisions.

Input And Output Of MIS

Inputs: MIS receives data from various sources, including company units, functions, and external sources.
Outputs: Provides different types of reports such as scheduled, key-indicator, demand, exception, and push reports, each serving specific purposes.

Types of Management Information Systems (MIS)

Process Control: This type of MIS collects data to create reports that evaluate the performance of systems and processes within an organization. It helps in monitoring and improving efficiency.
Management Reporting System: Generates reports that provide insights into the company's operations, helping management track progress and make informed decisions.
Inventory Control: Allows tracking of current inventory levels within a department or the entire company, aiding in inventory management and optimization.
Decision Support Systems: Gathers information from various sources, both internal and external, to assist team management in making effective and strategic business decisions.
Expert Systems: Utilizes Artificial Intelligence to simulate the judgment and expertise of individuals or organizations in specific fields, aiding in complex decision-making processes.
Executive Information System: Reports company data directly to top management in an easy-to-understand format, enabling quick insights and decision-making at the executive level.
Transaction Systems: Automates business processes and collects data on daily transactional activities, ensuring efficient and accurate record-keeping.
Accounting & Finance Systems: Tracks company assets, investments, and manages financial and accounting operations, ensuring financial stability and compliance.
Sales & Marketing Systems: Facilitates tracking of sales and marketing performance, providing insights into customer behavior and market trends.
HR Systems: Manages organizational information and oversees tasks like recruitment, payroll, and daily administration, ensuring compliance with company policies and standards.
School Information Management Systems: Assists educational institutions in managing daily activities such as attendance, payroll, and employee schedules, streamlining administrative tasks.
Local Databases: Provides information about residents in a specific locality, aiding in local data management and analysis for targeted initiatives.

Functions of Management Information Systems (MIS)

Provide Easy Access to Information: MIS allows easy access to marketing, financial, and operational information by strategically storing data in a central location accessible over a network.
Data Collection: Collects data from daily operations and external sources, fostering healthy relationships within the supply chain.
Performance Tracking: Tracks production and sales numbers, aiding in monitoring employee performance.
Foster Collaboration: Facilitates effective communication and collaboration among teams, ensuring access to necessary data for decision-making.
Company Projections: Offers trend analysis features to project business performance and assess the impact of potential changes.

Decision Support System (DSS)

A Decision Support System (DSS) is an information system that helps managers make effective decisions. It is used in planning and analyzing data in areas like production, finance, and marketing.

Key Functions of DSS:

Data Collection: Collects data from daily operations and external sources for analysis.
Data Storage: Stores collected data in a central database for easy retrieval and processing.
Data Updating: Updates data regularly to ensure accuracy and relevance for decision-making.
Data Processing into Information: Analyzes collected data to generate meaningful information for managers.
Report Generation: Generates reports based on processed data to aid in decision-making processes.

Components of DSS:

Data Management Component: Collects and stores information from organizational, external, and personal sources.
Model Management Component: Utilizes various models such as what-if analysis and statistical models for decision-making.
Knowledge Management Component: Manages knowledge databases and expert systems to provide insights and recommendations.
User Interface Management Component: Provides a user-friendly interface for managers to interact with the DSS and input commands.

Decision Making with DSS:

DSS is an application of Herbert Simon's model, consisting of three phases:

Intelligence: In this phase, specific problems are identified. For example, a business may experience low sales in a month. However, the origin of the problem is not clear, which could be due to sales strategies, product quality, etc. The DSS helps in identifying the root cause of the problem (Problem Definition).
Design: Once the problem is defined, the next step is to design its solutions. There can be multiple solutions to a problem, and the choice of an appropriate solution varies depending on the problem. Managers use inquiry, analysis, models, and accounting systems during this phase to develop potential solutions.
Choice: In the choice phase, managers select the best solution among the options generated in the design phase. This process may involve evaluating the feasibility, cost-effectiveness, and potential impact of each solution before making a decision.

Managers may iterate through these three steps multiple times until a satisfactory solution is found. The DSS supports this decision-making process by providing data analysis, modeling tools, and scenario planning capabilities.

Objectives of DSS:

Enhance manager's decision-making process effectiveness.
Support decision-making processes without replacing managerial judgment.
Improve directors' effectiveness in decision making.
Support managers at all levels of the organization.
Support individuals and groups in decision-making activities.
Support decision phases like intelligence, design, choice, and implementation.

Group Decision Support System (GDSS)

A Group Decision Support System (GDSS) is a specialized information system designed to facilitate decision-making in a group setting. Unlike traditional Decision Support Systems (DSS) meant for individual decision makers, GDSS caters to scenarios where multiple people are involved in the decision-making process.

Types of Group Configuration (GDSS Time/Place Models)

GDSS can operate in various configurations depending on the time and place of group members:

Same Time/Same Place: All members gather in one location, using a common network and display screen. Example: A project team meeting in a conference room.
Same Time/Different Place: Members are in different locations but connect via LAN or online tools. Example: A virtual meeting with team members working remotely.
Different Time/Same Place: Members meet at a common location but interact through teleconferencing or video conferencing. Example: Board members discussing strategies through video calls.
Different Time/Different Place: Members are dispersed geographically and communicate through long-distance networks. Example: Global teams collaborating on a project using online collaboration tools.

Features and Service Capabilities of GDSS

GDSS offers several features and capabilities to enhance group decision-making:

Supports Parallel Processing: Enables simultaneous processing of information by group members.
Empowers Participation: Encourages active participation and input from all group members.
Access to Tools and Techniques: Allows the use of various decision-making tools and models preferred by group members.
Access to External Information: Provides quick access to external data and resources for informed decision-making.
Computer-Based Discussions: Facilitates online discussions and exchanges similar to face-to-face meetings.
Instant Voting: Enables real-time and anonymous voting on decisions within the group.
Simultaneous Interaction: Supports multiple users interacting concurrently for efficient collaboration.
Information Recording: Automatically records all discussions and decisions for future reference and analysis.
Organization Memory: Develops a repository of organizational knowledge and decisions for ongoing use.

Examples of GDSS Applications

GDSS finds application in various business scenarios, including:

Leave Application Processing
Requisition Processing
Credit Rating Approval
Pricing Negotiations and Order Processing
Work Order Processing: Acknowledgment to Delivery and Billing
Group Interviewing of Candidates
Contract Document Processing for Multiple Signatories

Similarities Between DSS and GDSS

Decision Support Systems (DSS) and Group Decision Support Systems (GDSS) share several similarities in their capabilities:

Use of Models, Programs, and Algorithms: Both DSS and GDSS utilize stored models, programs, and algorithms to aid in decision-making processes.
Interactive "What-If" Capabilities: They offer interactive functionalities like "what-if" scenarios to explore different decision paths and outcomes.
Use of Internal and External Data: Both systems leverage internal and external data sources while ensuring data security and confidentiality.
Graphical Output: They provide graphical outputs such as scorecards or dashboards for visual representation of data and insights.
Communication Capabilities: Both DSS and GDSS enable communication with various stakeholders, facilitating collaboration and information sharing.
Business Analytics: They incorporate business analytics tools and techniques to analyze data, predict trends, and support decision-making processes.
AI-Based Expert Systems: Both systems can integrate AI-based expert systems to leverage expertise and automate decision-making tasks.

While DSS caters to individual decision makers, GDSS is tailored for group decision-making scenarios, but their underlying capabilities and functionalities align closely.

Difference Between GDSS and DSS

Purpose
- GDSS: Supports group decision-making processes.
- DSS: Supports individual decision-making processes.
Users
- GDSS: Used by teams or groups.
- DSS: Used by individuals.
Tools and Features
- GDSS: Includes tools for electronic brainstorming, voting, and group messaging.
- DSS: Includes tools for data analysis, simulations, and forecasting.
Focus
- GDSS: Improves the effectiveness of group meetings and discussions.
- DSS: Improves the quality of decisions made by individuals.
Application
- GDSS: Used in situations requiring consensus or collective input.
- DSS: Used for complex decision-making tasks requiring data analysis.

Expert System (ES)

Expert Systems (ES) are a type of artificial intelligence system that leverages knowledge and reasoning abilities to act as expert consultants in specific problem areas.

Overview of Expert Systems

Expert systems were one of the earliest applications of AI, developed in the 1970s. They capture knowledge from individual experts through interviews and represent it as sets of rules, usually in the form of IF-THEN rules.

These systems function as knowledge-based information systems, providing expert advice and decision support to end users in specialized problem areas.

Components of Expert Systems

Expert systems consist of two main components:

Knowledge Base: Contains facts about a specific subject area and heuristics (rules of thumb) that express expert reasoning procedures.
Software Resources: Include an inference engine that processes knowledge, makes associations, and provides recommended actions to users.

Applications of Expert Systems

Expert systems are used in various application categories:

Decision Management: Systems that make recommendations based on supplied criteria, such as loan portfolio analysis or employee performance evaluation.
Diagnostic/Troubleshooting: Systems that infer causes from symptoms, like medical diagnosis or software debugging.
Design/Configuration: Systems that assist in configuring equipment components or processes.
Selection/Classification: Systems that aid in product or process selection from complex alternatives.
Process Monitoring/Control: Systems that monitor and control procedures or processes, such as inventory control or production monitoring.

Benefits of Expert Systems (ES)

Expert Systems (ES) offer several advantages:

Increased Efficiency: ES can process large amounts of data quickly and provide accurate results, leading to improved decision-making efficiency.
Consistency: They apply rules consistently without being influenced by emotions or external factors, ensuring uniformity in decision-making.
24/7 Availability: ES can operate round the clock, providing access to expert advice and support at any time.
Knowledge Preservation: They capture and store expert knowledge, preventing loss of critical information due to personnel changes or retirements.
Risk Reduction: By applying expert knowledge and rules, ES can minimize errors and mitigate risks in decision-making processes.
Training Tool: ES can be used as a training tool for less experienced personnel, allowing them to learn from expert-level decision-making.

Limitations of Expert Systems (ES)

Despite their benefits, ES also have limitations:

Domain Specificity: ES are effective only within their defined domain and may struggle with tasks outside their expertise.
Initial Cost: Developing and implementing ES can be expensive due to the need for expert knowledge acquisition and system development.
Maintenance: Keeping ES updated and relevant requires continuous effort and resources.
Knowledge Limitation: ES may not handle new or unprecedented situations well, as they rely on predefined rules and knowledge.
Lack of Common Sense: They may lack common sense reasoning abilities, leading to occasional inaccuracies in decision-making.
Dependency: Over-reliance on ES without human oversight can lead to complacency and reduced critical thinking.

Executive Support System (ESS or EIS)

Executive Support Systems (ESS) or Executive Information Systems (EIS) are designed to provide critical information to top executives in a format that is easy to access and understand. These systems support strategic decision-making by presenting summarized data from across the organization, often using graphical displays and customizable reports. ESS and EIS are used interchangeably to describe systems that enable executives to monitor performance, analyze trends, and make informed decisions quickly.

Features of an ESS/EIS

Complete Overview: Combines information from across the organization for a holistic view.
Strategic Decisions: Supports long-term and strategic decision-making.
Customized Presentation: Presents information based on executives' preferences, often using graphical displays.
Exception Reporting: Highlights important trends and deviations from expected results.
Drill Down Capability: Allows executives to delve into details as needed.

Applications

ESS/EIS finds applications in various areas:

Manufacturing: Focuses on operational control and efficiency.
Marketing: Aids in sales forecasting, pricing strategies, and competition analysis.
Financial: Integrates planning, budgeting, and performance reporting for informed financial decisions.

Advantages of ESS/EIS

Easy to use for executives, requiring minimal computer expertise.
Provides timely and understandable company information.
Enhances decision-making efficiency and competitiveness.
Improves tracking, reporting, and office automation.
Reduces time spent on finding information and identifies performance trends early.

Disadvantages of ESS/EIS

Dependence on the system's functionality.
Potential for information overload for some managers.
Difficulties in quantifying benefits and high implementation costs.
System performance issues like slowness and data security concerns.
May not be cost-effective for smaller companies.

Infrequent Information Requirements of Executives

Top executives' information needs are dynamic and can't be precisely determined in advance. They rely on future-oriented, subjective, and informal information.

Operational Information

Relates to day-to-day operations and is used by executives to monitor and control operations.

Tactical Information

Helps executives allocate resources and control top-level plans, such as information about alternative funding sources.

Strategic Information

Used by executives to make choices among business options, define goals, initiate programs, and develop policies.