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What Is Systems Analysis?
System Analysis and Design · Chapter 1: Introduction to Systems Analysis and the Analyst's RoleSection 1.1 · lesson 1 of 6910 min · free with a free account
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In this lesson
Systems, their 6 components, and where analysis ends and design begins.
- Define a system and identify its 6 core components
- Distinguish open systems from closed systems
- Compare the 3 foundational types of information system: TPS, MIS, and DSS
- Explain how systems analysis differs from systems design
Transcript
Everything said in the video, section by section (1,505 words). Read along, or search it.
Systems Analysis and the Analyst's Role
What Is Systems Analysis?
Before anyone can improve a system, they have to be able to see one. That sounds obvious. In practice, it is the first real skill a systems analyst develops. This section builds that skill from the ground up. We start with what a system actually is, and the six components every system shares. Then we separate open systems from closed ones. Next come the three foundational types of information system, known as T P S, M I S, and D S S. And we finish with a distinction that trips up many new analysts. Systems analysis and systems design are not the same job. By the end, you should be able to look at any organization and describe it as a system.
The Core Idea
What Is a System?
Start with the definition. A system is an organized group of interrelated components, working together toward a common goal. The key word is interrelated. The components depend on one another, so a change in one part affects how the rest behaves. This definition is deliberately broad. It covers a university admissions office. It covers an airline reservation network. It even covers the circulatory system in the human body. What they share is this. Each is a set of parts, coordinated to produce an outcome that no single part could produce alone. That last idea is the real test of whether you are looking at a system, or just a pile of parts.
A Worked Example
The Coffee Shop as a System
Let's make that concrete with a coffee shop. This shop takes orders online and prepares them for pickup. There is an ordering app, where the customer places the request. There is the kitchen staff, who prepare the drink. There is a point-of-sale terminal, and there is a pickup counter. None of these parts is independent. Together, they form a system built to turn a customer's request into a finished drink, handed across the counter. Now notice how an analyst studies this. The analyst is not just looking at the app. And the analyst is not just looking at the kitchen. The analyst is looking at how all of the parts work together. A slow pickup might not be a kitchen problem at all. It might start in the app.
The Analyst's Toolkit
The 6 Components of Every System
Every system, whatever its size or purpose, can be described with six components. Input is the data, materials, or resources that enter the system to be worked on. In the coffee shop, that is the customer's order, entered into the app. Process is the set of activities that transforms input into output. Here, that is the staff preparing the drink according to the order. Output is the result the system delivers, once processing is complete. The finished drink, and the printed receipt. Feedback is information about the output, used to control or adjust the system. A complaint about a wrong order, which prompts staff retraining, is feedback. The boundary is the line separating the system from everything outside it. For example, the line between the shop's own operations and the delivery company that carries orders. And the environment is everything outside that boundary, which can still influence the system. Local traffic, the weather, and competitor pricing all shape how many orders arrive. Why learn these six so carefully? Because a requirement, a problem, or a proposed change almost always maps to one of them.
Figure 1.1
How the Components Interact
Here is how those components relate to one another. Input flows into the process. The process produces output. Then feedback carries information about that output back into the process. That loop is what lets a system adjust, instead of repeating the same mistake. Around all of this sits the boundary, which marks what belongs to the system. Outside the boundary is the environment. The system must respond to its environment, but it does not control it. Keep that distinction in mind. When an analyst asks what a system can change, the answer lives inside the boundary.
Classifying Systems
Open Systems and Closed Systems
Systems can also be classified by how much they interact with their environment. An open system exchanges information, energy, or materials with its environment, on an ongoing basis. And it adjusts its behavior in response. A closed system is isolated from its environment. It operates the same way, regardless of outside conditions. Here is the important caveat. Very few real organizational systems are fully closed. Organizations have customers, competitors, and regulators, and all of them push in from outside. So the term closed system is most useful as one end of a spectrum. In practice, you will mostly be asking how open a system is, not whether it is open.
Side by Side
Open vs. Closed in Practice
Let's compare the two side by side. An open system keeps exchanging data or resources with outside sources. A closed one has no exchange once it is running. It works on fixed internal rules. An open system adjusts as outside conditions change. A closed one stays fixed. Take an online retailer's pricing engine. It reacts to competitor prices and to demand, so it is a clear example of an open system. Now take a thermostat's internal control loop. It follows a fixed setpoint, until someone changes it. The last row is the one that matters for your work. For an open system, the analyst must model the external inputs, and how the system should respond to them. For a closed system, the analyst can focus mainly on the internal logic, since outside change is minimal.
Information Systems
TPS, MIS, and DSS
Organizations run several categories of information system side by side. Each serves a different level of decision-making. Three foundational categories appear throughout this course. The first is the transaction processing system, or T P S. It works at the operational, day-to-day level, recording routine individual transactions. Think of a grocery store's checkout scanner, recording each sale. The second is the management information system, or M I S. It serves middle management, at the tactical level. It summarizes transaction data into regular reports, such as a weekly sales-by-region report. The third is the decision support system, or D S S. It serves senior leadership, at the strategic level. It combines internal and external data with analytical models, to support non-routine decisions. For example, a model that helps leadership decide where to open the next store.
Why It Matters
Cumulative, Not Competing
It is tempting to see these three as alternatives. They are not. They are cumulative, and each one depends on the layer beneath it. A D S S is only useful if the M I S reports feeding it are accurate. In turn, an M I S report is only useful, if the T P S underneath it captured the original transaction correctly. This has a very practical consequence. Suppose someone asks you to fix a bad report. The instinct is to open the report and start adjusting it. But the real problem often traces back further, to how the underlying transactions were captured. Fixing the report alone would just hide the error one level down. Good analysts follow the data back to where it entered the system.
Two Distinct Phases
Systems Analysis vs. Systems Design
Now to the distinction that matters most for this course. Systems analysis and systems design are two distinct phases of building or improving a system. Systems analysis asks what the system must do. It studies the current operation, and identifies problems and opportunities. Then it defines the requirements a new or revised system must satisfy. Systems design asks how the system will do it. It takes the requirements from analysis, and turns them into a technical blueprint. That blueprint covers database structures, screen layouts, and processing logic, which developers can build from. Confusing the two is one of the most common early mistakes new analysts make. The usual version is jumping to screens and tables before anyone has confirmed what the business needs.
Worked Example
A Hospital Replaces Its Scheduling
A hospital replacing its patient scheduling process shows the difference clearly. During analysis, the team interviews front-desk staff and physicians. It observes how appointments are booked today. And it documents a requirement. The new system must prevent double-booking a physician across two departments. Notice that the requirement says nothing about how. During design, the team decides how that requirement will actually be met. Which database table will store appointment records? What validation rule will run when a booking is submitted? And what will the booking screen look like to the front-desk staff? The outputs differ too. Analysis produces a requirements document and process models, for business stakeholders and users. Design produces database, interface, and architecture designs, for developers and technical staff.
Key Takeaways
What to Carry Forward
Let's pull this together. A system is a set of interrelated components, working toward a common goal. Every system can be described by six components. Input, process, output, feedback, boundary, and environment. Open systems continuously interact with their environment. Closed systems do not. T P S, M I S, and D S S serve the operational, tactical, and strategic levels of an organization. And they build on one another, so errors at the bottom travel all the way up. Finally, systems analysis defines what a system must do. Systems design determines how it will do it. Hold on to that what-versus-how split. The rest of this course is built on it.
About System Analysis and Design at UPI Study
System Analysis and Design (Computer Science 390) is a self-paced online course of 69 video lessons in 9 chapters, from the analyst's role and requirements to UML modeling, interface and database design, testing, maintenance and project management. It carries a NCCRS credit recommendation for 3 semester credits.
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