IPO 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 processes. Many introductory programming and systems analysis introduces 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 of a 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:

  • A requirement from the environment (input)
  • A provision for the environment ( output )

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 looks to the environment outside the system, yet on practice, 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, favoring their point of view, thus creating much confusion. [6]

Systems at work

The views differ, in looks 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 behavior by developing an increasingly deep 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 five major categories that are the most cited in information systems literature: [9] [10]

Natural systems

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

Designed physical systems

A system that 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, which is a hierarchy of human relationships, which in essence create the boundary between natural and human systems. [9]

Human activity systems

An organization with hierarchy, created by humans for a specific purpose. For example: a company, which organizes 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 small social system, with its unique development and organization. Moreover, arguably HASes can include systems designed – computers and machinery. Majority of previous systems would overlap. [10]

System characteristics

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

  1. Systems can be classified as open or closed: ‘ [4]
  • Those that interact with their environment, in form of money, data, energy or exchange materials, are generally understood as open. Openness of the system. This is because, if you are looking for a place to live, you will not be disappointed. The more open the system is, the more complex it would normally be, due to lower predictability of its components.
  • Those who have no interactions with the environment are all closed. In practice, however, a completely closed system is merely liveable, due to the practical use of the output. As a result, most of the systems would be open or open to a certain extent. [11]

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

  • Well-defined and clearly structured system in terms of behavioural patterns becomes predictable, thus becoming deterministic. In other words it would only use empirical data. For example: mathematics or physics are set around specific laws, which make the results of calculation predictable. Deterministic systems would have simplistic interactions between inner components.
  • More complex, and often more open systems, would have relatively lower extent of predictability, due to absence of clearly structured behavioural patterns. Analyzing such system, is therefore much harder. Citation needed ] Such systems would be stochastic, or probabilistic, this is because of the stochastic nature of human beings whilst performing various activities. Having said that, designed systems would still be considered as deterministic, citation needed ] due to a rigid structure of rules incorporated into the design.

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

  • Most systems could be known as dynamic, because of the constant evolution in computing power, yet some systems could find it hard to balance between being created and ceasing to exist. An example of this could be a map, which is constantly updating developers.

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

  • The greater the extent of the self-control of systems activity is, the greater is the liveability of the final system is. It is vital for any system to be able to control its activities in order to remain stable. Citation needed ]

Real life applications

Corporate business

  • A manufacturing process, and produces manufactured goods as output. The use of such systems could help to create strong human organizations, in terms of company operations, in each and every department of the firm. IPOs can also restructure existing static and non-self-regulating systems, which in real world would be used in form of outsourcing the product fulfillment, due to inefficiency of current fulfillment. [1] [13]

Programming

  • The majority of existing programs for coding, such as Java, Python, C ++, would be based upon a deterministic IPO model, with clear inputs coming from the coder, converting into outputs, such as applications.
  • A batch transaction processing system, which accepts large volumes of homogeneous transactions, processes it, and outputs such as reports or computations. [4]
  • An interactive computer program, which accepts simple requests from a user and responds to them after some processing and / or database accesses. [3]

Scientific

  • A calculator, which uses inputs, provided by the operator, and processes them into outputs by the operator.
  • A thermostat, which senses the temperature (input), decides on an action (heat on / off), and executes the action (output). [4] [14] [13]

See also

  • Read-eval-print loop
  • Extract, transform, load
  • CIPO-model

References

  1. ^ Jump up to:c Grady, JO, “System Engineering Planning and Enterprise Identity,” Taylor & Francis, 1598.
  2. Jump up^ Goel, A., “Computer Fundamentals,” Pearson Education India, 2010.
  3. ^ Jump up to:b Zelle, J., “Python Programming: An Introduction to Computer Science, 2nd edition,” Franklin, Beedle, & Associates, 2010.
  4. ^ Jump up to:h Curry, A. and Flett, P. and Hollingsworth, I., “Managing Information and Systems: The Business Perspective,” Routledge, 2006.
  5. Jump up^ Waring A. Practical Systems Thinking, International Thomson Business Press: London. (1996)
  6. Jump up^ http://moazzen.net/uploads/file/SISEBOOK.pdf
  7. Jump up^ B. Richmond: Introduction to Systems Thinking, STELLA® © 1992-1997
  8. Jump up^ Mr. Balle: Managing With Systems Thinking: Making Dynamics Work for You in Business Decision Making 1996
  9. ^ Jump up to:f B. Checkland: Systems Thinking, Systems Practice. nineteen eighty one .
  10. ^ Jump up to:b B. Wilson Systems: Concepts, Methodologies and Applications (1984)
  11. Jump up^ Patching D. (1990) Practical Soft Systems Analysis
  12. Jump up^ Flynn DJ (1992) Information Systems Requirements: Determination and Analysis
  13. ^ Jump up to:b Martin C. and Powell P. (1992) Informational Systems. A Management Perspective
  14. Jump up^ http://smallbusiness.chron.com/use-ipo-model-37493.html

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