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Systems analysis

systems analysis, systems engineering, information technology, policy analysis, business management, educational reform, technology, requirements analysis, operations research

Systems analysis is a critical discipline used across various fields to understand, improve, and create systems. At its core, systems analysis is a structured approach to problem-solving and system development. It involves dissecting complex systems into smaller, manageable parts to understand their function and interactions. This understanding then informs the design and implementation of more efficient and effective systems.

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Systems Analysis: A Detailed Educational Resource

Introduction to Systems Analysis

Systems analysis is a critical discipline used across various fields to understand, improve, and create systems. At its core, systems analysis is a structured approach to problem-solving and system development. It involves dissecting complex systems into smaller, manageable parts to understand their function and interactions. This understanding then informs the design and implementation of more efficient and effective systems.

Definition of Systems Analysis: Systems analysis is “the process of studying a procedure or business to identify its goal and purposes and create systems and procedures that will efficiently achieve them.” It is also considered “a problem-solving technique that breaks a system down into its component pieces and analyses how well those parts work and interact to accomplish their purpose.”

In simpler terms, think of systems analysis as a doctor diagnosing a patient. Just as a doctor examines different parts of the body and their interactions to understand an illness, a systems analyst examines the components of a system (be it a business process, a computer system, or a policy) to understand how it works and identify areas for improvement.

Systems analysis is closely related to:

Furthermore, systems analysis is described as:

Formal Inquiry: “An explicit formal inquiry carried out to help a decision maker identify a better course of action and make a better decision than they might otherwise have made.”

This emphasizes the structured and methodical nature of systems analysis. It’s not just about intuition; it’s about applying a rigorous process to understand a system and inform decision-making.

Analysis and Synthesis: The Foundational Concepts

The terms “analysis” and “synthesis,” derived from Greek roots, are fundamental to understanding the systems analysis process.

Analysis: “The procedure by which we break down an intellectual or substantial whole into parts.” Synthesis: “The procedure by which we combine separate elements or components to form a coherent whole.”

Think of it as taking something apart to understand it (analysis) and then putting it back together, perhaps in a better way (synthesis). These concepts are not unique to systems analysis and are used across many disciplines like mathematics, logic, economics, and psychology.

In systems analysis, researchers and practitioners use methodology to analyze systems. This involves:

  1. Breaking down the system: Identifying the components and their functions (analysis).
  2. Understanding interactions: Examining how these components work together.
  3. Forming an overall picture: Developing a holistic understanding of the system (synthesis).

This overall picture allows for informed decisions about improving or creating new systems.

Applications of Systems Analysis

Systems analysis is not confined to a single domain. It’s a versatile tool applicable wherever systems are developed or improved. This includes:

Essentially, any field that deals with complex processes, organizations, or technologies can benefit from the structured approach of systems analysis.

Systems Analysis in Information Technology

In the realm of Information Technology (IT), systems analysis is a crucial phase in the development of computer-based information systems. It often precedes the creation or enhancement of databases and software applications.

Data Model: A representation of data structures and relationships within a system, often developed during systems analysis in IT projects. It serves as a blueprint for designing databases.

Systems analysis in IT helps to define:

Waterfall Model Approach to Systems Analysis

The Waterfall model, a traditional sequential software development approach, outlines specific steps for systems analysis in IT projects. These steps include:

  1. Feasibility Study: This initial stage determines if a project is viable from different perspectives.

    Feasibility Study: An evaluation to determine the viability of a project, considering economic, social, technological, and organizational factors.

    A feasibility study typically assesses:

    • Economic Feasibility: Is the project financially justifiable? Will the benefits outweigh the costs? For example, a company might analyze if the cost of developing a new customer relationship management (CRM) system will be offset by increased sales and improved customer retention.
    • Social Feasibility: Is the project socially acceptable? Will it have any negative social impacts? For instance, implementing a surveillance system might raise social concerns about privacy.
    • Technological Feasibility: Is the required technology available and mature enough to support the project? Can the development team handle the technical complexity? For example, attempting to build a highly complex AI system with limited AI expertise might be technologically infeasible.
    • Organizational Feasibility: Does the project align with the organization’s strategic goals and capabilities? Does the organization have the structure and resources to support the project? For example, implementing a large-scale enterprise resource planning (ERP) system requires significant organizational change management and commitment.

  2. Fact-Finding Measures: This step involves gathering information about the existing system and user requirements.

    Fact-Finding Measures: Techniques used to collect information about a system, including interviews, questionnaires, document reviews, and observations.

    Common fact-finding techniques include:

    • Interviews: Talking to stakeholders, users, and experts to understand their needs and perspectives. For example, interviewing sales representatives to understand their challenges with the current sales process.
    • Questionnaires: Distributing surveys to a larger group of users to gather standardized data about their requirements. For example, surveying all employees about their needs for a new internal communication system.
    • Visual Observations: Observing users working with the existing system to understand their workflows and identify pain points. For example, observing how warehouse staff currently manage inventory to understand inefficiencies.
    • Document Review: Analyzing existing documents, reports, and system documentation to understand the current system and its functionalities. For example, reviewing existing process flowcharts to understand the current order fulfillment process.

  3. Understanding End-User Operations: This step focuses on understanding how users will interact with the new system.

    This involves considering:

    • User Experience: Assessing the users’ general computer skills and experience to ensure the system is user-friendly. A system designed for elderly users might need a simpler interface than one designed for tech-savvy engineers.
    • System Usage: Determining how users will use the system in their daily tasks to tailor the system to their specific needs. A system for customer service representatives will have different usage patterns than a system for accountants.
    • User Environment: Understanding the context in which users will operate the system (e.g., office, field, mobile) to ensure the system is accessible and functional in their work environment. A system for field technicians might need to be mobile-friendly and work offline.

Phased Approach to Systems Analysis

Another perspective outlines a phased approach, breaking down systems analysis into five distinct phases:

  1. Scope Definition: Clearly defining the boundaries and objectives of the project.

    Scope Definition: The process of establishing the project’s boundaries, objectives, deliverables, and constraints, ensuring a clear understanding of what is included and excluded from the project.

    This involves:

    • Identifying Stakeholders: Determining all individuals or groups who have an interest in or are affected by the system.
    • Defining Objectives: Clearly stating what the project aims to achieve and what problems it intends to solve.
    • Setting Boundaries: Defining the limits of the system and what functionalities will be included in the project.

  2. Problem Analysis: Understanding the issues and needs that the new system aims to address.

    Problem Analysis: A systematic process of identifying, defining, and analyzing the problems and needs that a system is intended to solve.

    This involves:

    • Identifying Root Causes: Going beyond surface-level symptoms to understand the fundamental causes of the problems. For example, instead of just seeing slow order processing as the problem, analyzing why it’s slow might reveal issues with inventory management or outdated systems.
    • Defining Needs: Clearly articulating the requirements and needs of the users and stakeholders.
    • Analyzing Impacts: Understanding the consequences of the problems and the potential benefits of solving them.

  3. Requirements Analysis: Determining the specific conditions that the system must meet.

    Requirements Analysis: The process of identifying, documenting, and validating the conditions or capabilities that a system must possess to meet the needs of its users and stakeholders.

    This includes:

    • Functional Requirements: Describing what the system should do. For example, “The system must allow users to create and manage customer accounts.”
    • Non-Functional Requirements: Describing how well the system should perform. This includes aspects like performance, security, reliability, and usability. For example, “The system must respond to user requests within 2 seconds.”

  4. Logical Design: Creating a high-level blueprint of the system, focusing on the logical relationships between components and data.

    Logical Design: A conceptual representation of the system that describes what the system will do and how it will function, without specifying the physical implementation details.

    This involves:

    • Data Modeling: Designing the structure of the data that the system will use (e.g., using Entity-Relationship Diagrams).
    • Process Modeling: Defining the processes and workflows within the system (e.g., using flowcharts or data flow diagrams).
    • User Interface Design (Conceptual): Developing a high-level concept of how users will interact with the system.

  5. Decision Analysis: Evaluating different design options and making a final decision on the system’s architecture and implementation approach.

    Decision Analysis: A systematic approach to making choices, involving identifying alternatives, evaluating their consequences, and selecting the best option based on defined criteria.

    This involves:

    • Evaluating Alternatives: Considering different technical solutions, vendor options, and implementation strategies.
    • Cost-Benefit Analysis: Comparing the costs and benefits of each alternative.
    • Risk Assessment: Identifying and evaluating potential risks associated with each alternative.
    • Making a Choice: Selecting the most suitable option based on the analysis and stakeholder input.

Use Cases in Systems Analysis

Use cases are a popular modeling tool in systems analysis, particularly for capturing functional requirements.

Use Case: A description of a sequence of interactions between a user (actor) and a system that results in the actor achieving a specific goal. Each use case represents a business scenario or event for which the system must provide a defined response.

Use cases are useful for:

Example of a Use Case:

Use Case Name: Withdraw Cash from ATM

Actor: Bank Customer

Goal: To withdraw cash from their bank account using an ATM.

Steps:

  1. Customer inserts ATM card.
  2. ATM prompts for PIN.
  3. Customer enters PIN.
  4. ATM verifies PIN.
  5. ATM displays main menu.
  6. Customer selects “Withdraw Cash.”
  7. ATM prompts for withdrawal amount.
  8. Customer enters amount.
  9. ATM checks account balance.
  10. If sufficient funds, ATM dispenses cash and prints receipt.
  11. ATM returns card.

Use cases are often visually represented using diagrams and are a key component of object-oriented analysis and design methodologies.

Policy Analysis and Systems Analysis

Policy analysis, a discipline focused on improving public policy, has its roots in systems analysis. Its modern form originated from the application of systems analysis principles by Robert McNamara when he was the United States Secretary of Defense. He utilized systems analysis to bring a more structured and data-driven approach to defense policy decisions.

Policy analysis uses systems analysis techniques to:

Practitioners of Systems Analysis

Individuals who practice systems analysis are known by various titles, reflecting the diverse applications of the field. Common titles include:

Practitioners of systems analysis are often called upon to:

Systems analysis is not just a theoretical discipline; it is a practical field heavily relied upon by both researchers and practitioners across various industries to solve real-world problems and improve system performance.

See also

References

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