Information feedback loops
Copyright 2016 Graham Berrisford.
One of about 300 papers at http://avancier.website. Last updated 08/01/2017 18:01
This paper discusses information feedback loops in various kinds of system.
And so, indirectly, offers some reasons why the EA team is usually rooted in the IT department.
Information feedback loops in cybernetics (after Ashby)
Information feedback loops in biology (after Ashby)
Information feedback loops in system theory (after Bertalanffy)
Information feedback loops in sociology (after Boulding)
Information feedback loops in business and EA (various industry sources)
The mathematician Norbert Wiener wrote the first book on cybernetics in 1948.
He defined cybernetics as “the science of communication and control in the animal and the machine.”
His phrase “communication and control” highlights the importance of information flows to regulatory control systems.
The phrase “the animal and the machine” points to there being general principles that apply to all systems, animate and inanimate.
W Ross Ashby’s “Introduction to cybernetics” defined it as being about information flows (rather than the energy flows of thermodynamics).
“what is important is the extent to which the system is subject to determining and controlling factors.
So no information or signal or determining factor may pass from part to part without its being recorded as a significant event.” W Ross Ashby 1956
Ashby said cybernetics focuses on general types of information and behaviour - rather than instances
“Cybernetics typically treats any given, particular, machine by asking not "what individual act will it produce here and now?" but "what are all the possible behaviours that it can produce?"
It is in this way that information theory comes to play an essential part in the subject.
For information theory is characterised essentially by its dealing always with a set of possibilities;
both its primary data and its final statements are almost always about the set as such, and not about some individual element in the set.”
Brains and businesses can be seen as systems that monitor and strive to direct some things in the real world.
A brain (an animal intelligence) has to form a mental model of what it perceives to be out there through its senses.
A business has to maintain documented models of the entities and events it monitors and directs through information feedback loops.
When tested against reality, these mental and documented models must be accurate enough, else the system will fail.
W Ross Ashby was interested in how an organism survives and thrives in fluctuating environmental conditions.
How does it adapt continually to environmental changes, maintain itself in a viable state, through a sensor-motor feedback loop?
Ashby treated the brain as a control system that directs organs to maintain such bodily state variables in the ranges suited to life.
There is an information feedback loop.
The brain receives information from sensors about the state of the body and its environment.
It processes this information and sends instructions to motors that act to maintain the state of the body (and perhaps produce other desired effects).
In thermodynamics, the inputs and outputs are matter and energy.
In social, business and software systems, the primary inputs and outputs are information or data flows.
“EA is about “information intensive organisations”, ArchiMate 2.1
“closely connected with system theory is… communication.
The general notion in communication theory is that of information.
A second central concept of the theory of communication and control is that of feedback.” Bertalanffy
Information is found in a system’s input and output data flows (messages or signals).
These input and output flows convey facts about the state of the system or its environment.
E.g. the bending of the bimetal strip is a signal that conveys information about the temperature of an environment.
Information is found also in the memory of a system.
Databases maintain state variables that record the current state of entities in the system and its environment.
Business databases can remember the past – remember historical states as well as the current state.
“Though it grew out of organismic biology, general system theory soon branched into most of the humanities.” (Laszlo and Krippner).
Kenneth Boulding’s famous essay in 1956 applied general system theory ideas to social entities.
Boulding considered that a social system depends on its individuals sending and receiving messages.
He said the concept of information flow must be added to the material and energy flows found in purely physical systems.
Boulding said a social system depends on its individuals sending and receiving messages.
The components of social systems are human roles rather than human beings.
The individuals who play those roles exhibit behaviour.
An individual interacts with its environment; an individual has a life history from birth to death.
An individual actor acts in a society in a way that depends on the messages it receives from other actors,
An actor’s current state is a collection of remembered “mental images”.
The concept of information flow must be added to the concepts of material flow and energy flow found in purely physical systems.
Boulding’s “mental images” form an obscure and fuzzy kind of system state.
And note that the state of a society is distributed across the minds of its members (and other knowledge stores).
A system in which a system’s state is distributed, replicated or inconsistent is a challenge for sociologists and enterprise architects alike.
Issues arising from distribution and incoherence of system state are a huge issue in EA, addressed in other papers.
In sociological tradition, sociologists tend to focus on or other of two alternative kinds of system element: on actors or actions.
At the extreme end of social system thinking, Luhmann focuses entirely on actions, with no reference to actors.
Luhmann proposes the actions of interest - the basic elements of a social system - are communication acts.
His system of transient communication events is radically different from systems as understood by Ashby, Boulding and most other system theorists.
Communication acts are about a code, and lead to decisions that sustain a system centered on that code.
Enterprise architecture is for and about “information-intensive organisations”, as the ArchiMate standard puts it.
In business, the term information is usually used to mean a sequence of symbols representing data about some entity or event.
Human and computer activity systems depend on the consumption, maintenance and production of such structured data.
To meet its goals, a business must monitor and direct relevant entities and activities.
A business needs to know the current state of the entities and activities it monitors or directs.
Towards the end of the 20th century, we entered “the information age”.
The concept of “the enterprise as a system” emerged out of requirements to integrate the information and processes in distributed systems.
All authorities in the list below position enterprise architecture as being about business roles and processes that are supported by information systems.
<![if !supportLists]>· <![endif]>“Enterprise architecture is the determinant of survival in the Information Age.” (Zachman)
<![if !supportLists]>· <![endif]>“Enterprise architecture planning is the process… to improve data quality, access to data, adaptability…, data interoperability and sharing, and cost containment.” (Spewak)
<![if !supportLists]>· <![endif]>“The domain of information-intensive organisations…is the main focus of the [enterprise architecture modelling] language” (ArchiMate standard v2.1)
<![if !supportLists]>· <![endif]>"Today’s CEOs know that the effective management and exploitation of information… is a key factor to business success.” (TOGAF 9.1)
<![if !supportLists]>· <![endif]>"Companies excel because they've [decided] which processes they must execute well, and have implemented the IT systems to digitise those processes." (RWR).
EA is concerned with business systems where the inputs and outputs can include materials as well as information.
But the primary focus is on information:
<![if !supportLists]>· <![endif]>On input data flows that describe the current state of external entities or request action, and
<![if !supportLists]>· <![endif]>On output data flows that inform or direct the behaviour of external entities.
EA concerned with business systems connected to their environments by information feedback loops.
It assumes a business acts in response to messages it receives, in the light of information it has about the current state of business’s entities and activities.
A business must know the state of those entities and activities in its environment that it monitors, supports or directs
It learns of changes to the environment and customer requirements through feedback - the arrival of new inputs.
It responds to inputs and/or state changes by sending outputs to inform or direct entities and activities in its environment.
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