IPO model

The input–process–output model

The input–process–output (IPO) model, or input-process-output pattern, is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or other process. Many introductory programming and systems analysis texts introduce this as the most basic structure for describing a process.[1][2][3][4]

Overview

A program or process using the input-process-output model receives inputs from a user or other source, does some computations on the inputs, and returns the results of the computations.[1] In essence the system separates itself from the environment, thus defining both inputs and outputs, as one united mechanism.[5] The system would divide the work into two categories:

In other words, such inputs may be materials, human resources, money or information, transformed into outputs, such as consumables, services, new information or money.

As a consequence, Input-Process-Output system becomes very vulnerable to misinterpretation. This is because, theoretically, it contains all the data, in regards to the environment outside the system, yet on practice, environment contains a significant variety of objects, that a system is unable to comprehend, as it exists outside systems control. As a result it is very important, to understand, where the boundary lies, between the system and the environment, which is beyond systems understanding. This is because, often various analysts, would set their own boundaries, favouring their point of view, thus creating much confusion.[6]

Systems at work

The views differ, in regards to systems thinking.[4] One of such definitions would outline the Input-process-output system, as a structure, would be:

"Systems thinking is the art and science of making reliable inferences about behaviour by developing an increasingly deep understanding of the understanding of the underlying structure"[7]

Alternatively , it was also suggested that systems are not 'holistic' in the sense of bonding with remote objects (for example: trying to connect a crab, ozone layer and capital life cycle together).[8]

Types of systems

There are three major categories that are the most cited in information systems literature: [9][10]

Natural systems

A system which has not been created as a result of human interference. Examples of such would be the solar system as well as the human body, evolving into its current form[9]

Designed physical systems

A system which has been created as a result of human interference, and is physically identifiable. Examples of such would be various computing machines, created by human mind for some specific purpose. [9]

Designed abstract systems

A system which has been created as a result of human interference, and is not physically identifiable. Examples of such would be mathematical and philosophical systems, which have been created by human minds, for some specific purpose. [9]

There are also some social systems, which allow humans to collectively achieve a specific purpose.

Social systems

A system created by humans, and derived from intangible purposes. For example: a family, that is a hierarchy of human relationships, which in essence create the boundary between natural and human systems.[9]

Human activity systems

An organisation with hierarchy, created by humans for a specific purpose. For example: a company, which organises humans together to collaborate and achieve a specific purpose. The result of this system is physically identifiable.[9]There are, however, some significant links between with previous types. It is clear that the idea of human activity system (HAS), would consist of a variety of smaller social system, with its unique development and organisation. Moreover, arguably HASes can include designed systems - computers and machinery. Majority of previous systems would overlap.[10]

System characteristics

There are several key characteristics, when it comes to the fundamental behaviour of any system.

  1. Systems can be classified as open or closed:'[4]

2. Systems can be classified as deterministic or stochastic:[4]

3. Systems can be classified as static or dynamic[4]

4. Systems can be classified as self-regulating or non-self-regulating[4][12]

Real life applications

Corporate business

Programming

Scientific

See also

References

  1. 1 2 3 Grady, J. O., "System Engineering Planning and Enterprise Identity," Taylor & Francis, 1995.
  2. Goel, A., "Computer Fundamentals," Pearson Education India, 2010.
  3. 1 2 Zelle, J., "Python Programming: An Introduction to Computer Science, 2nd edition," Franklin, Beedle, & Associates, 2010.
  4. 1 2 3 4 5 6 7 8 Curry, A. and Flett, P. and Hollingsworth, I., "Managing Information and Systems: The Business Perspective," Routledge, 2006.
  5. Waring A. Practical Systems Thinking, International Thomson Business Press: London. (1996)
  6. http://moazzen.net/uploads/file/SISEBOOK.pdf
  7. B. Richmond: Introduction to Systems Thinking, STELLA®© 1992-1997
  8. M. Balle: Managing With Systems Thinking: Making Dynamics Work for You in Business Decision Making 1996
  9. 1 2 3 4 5 6 P. B. Checkland: Systems Thinking, Systems Practice. 1981 .
  10. 1 2 B. Wilson Systems: Concepts, methodologies and applications ( 1984)
  11. Patching D. (1990) Practical Soft Systems Analysis
  12. Flynn D.J. (1992) Information Systems Requirements: Determination and Analysis
  13. 1 2 Martin C. and Powell P. (1992) Informational Systems. A Management Perspective
  14. http://smallbusiness.chron.com/use-ipo-model-37493.html
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