Coevolving Innovations

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System types as purposeful, and displaying choice

Russell Ackoff has a four-way categorization of systems that I’ve found useful, and often shows up in my presentations.  I’ve had a history of citing a 1996 article that is peer-reviewed.  However, when I first saw him in person, speaking with an overhead slide projector in 1997, I recalled a slightly different language.  I’ve now discovered an article that is consistent with my memory.

In 1996, Ackoff & Gharajedaghi wrote (in a language consistent with the Ackoff & Emery 1972 On Purposeful Systems book):

Whatever one considers a system to be — and there is considerable agreement as to what a system is — there are obviously different ways of classifying them.  For example, they can be classified by size, by discipline (physical, biological, psychological, and so on), by location, by function, and many other ways as well.  The choice of a classification scheme normally depends on its intended use.  For our purposes — examining the consequences of mismatching systems and their models — the critical classifying variable is purpose and purpose is a matter of choice.

An entity is purposeful if it can produce (1) the same functionally defined outcome in different ways in the same environment, and (2) functionally different outcomes in the same and different environments.  Although the ability to make choices is necessary for purposefulness, it is not sufficient.  An entity that can behave differently but produce only one outcome in any one of a set of different environments is goal-seeking, not purposeful.  

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Russell Ackoff has a four-way categorization of systems that I’ve found useful, and often shows up in my presentations.  I’ve had a history of citing a 1996 article that is peer-reviewed.  However, when I first saw him in person, speaking with an overhead slide projector in 1997, I recalled a slightly different language.  I’ve now discovered an article that is consistent with my memory.

In 1996, Ackoff & Gharajedaghi wrote (in a language consistent with the Ackoff & Emery 1972 On Purposeful Systems book):

Whatever one considers a system to be — and there is considerable agreement as to what a system is — there are obviously different ways of classifying them.  For example, they can be classified by size, by discipline (physical, biological, psychological, and so on), by location, by function, and many other ways as well.  The choice of a classification scheme normally depends on its intended use.  For our purposes — examining the consequences of mismatching systems and their models — the critical classifying variable is purpose and purpose is a matter of choice.

An entity is purposeful if it can produce (1) the same functionally defined outcome in different ways in the same environment, and (2) functionally different outcomes in the same and different environments.  Although the ability to make choices is necessary for purposefulness, it is not sufficient.  An entity that can behave differently but produce only one outcome in any one of a set of different environments is goal-seeking, not purposeful.  

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Conversations on an emerging science of service systems (IFSR Pernegg 2010)

Earlier this year, in April, the International Federation for Systems Research hosted its biannual research conversation, this time in Pernegg, Austria.  This meeting was a four-day opportunity to continue developing ideas on the emerging science of service systems begun in July 2009.

The proceedings from the meeting have now been published.  I’ve extracted the chapter for our team as a separate downloadable document.  The report starts with a description of our activities, and an outline of our progress.

The conversation began with self-reflections on personal experiences leading each of the individuals to the systems sciences, acknowledging the influence of those trajectories on their perspectives on service systems.  In recognition of this science of service systems as a potentially a new paradigm, much of the time together was spent in sensemaking about the intersection between ongoing services research and systems sciences perspectives.  This sensemaking led the team to focus the dialogue more on posing the right questions to clarify thinking broadly, as opposed to diving deeply towards solutions that would be tied up as issues within a problematique.

During the conversation, the progress on ideas was recorded on flipcharts.  Nearing the end of our time together, the team cut up the flipcharts with scissors, and collated the discussion threads into five clusters:  (i) philosophy; (ii) science; (iii) models; (iv) education; (v) development.  With service systems as a new domain, the team found all five clusters underdeveloped.  Recognizing that all five clusters are coevolving, the phenomenon of service systems was listed in order from the most concrete (i.e.

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Earlier this year, in April, the International Federation for Systems Research hosted its biannual research conversation, this time in Pernegg, Austria.  This meeting was a four-day opportunity to continue developing ideas on the emerging science of service systems begun in July 2009.

The proceedings from the meeting have now been published.  I’ve extracted the chapter for our team as a separate downloadable document.  The report starts with a description of our activities, and an outline of our progress.

The conversation began with self-reflections on personal experiences leading each of the individuals to the systems sciences, acknowledging the influence of those trajectories on their perspectives on service systems.  In recognition of this science of service systems as a potentially a new paradigm, much of the time together was spent in sensemaking about the intersection between ongoing services research and systems sciences perspectives.  This sensemaking led the team to focus the dialogue more on posing the right questions to clarify thinking broadly, as opposed to diving deeply towards solutions that would be tied up as issues within a problematique.

During the conversation, the progress on ideas was recorded on flipcharts.  Nearing the end of our time together, the team cut up the flipcharts with scissors, and collated the discussion threads into five clusters:  (i) philosophy; (ii) science; (iii) models; (iv) education; (v) development.  With service systems as a new domain, the team found all five clusters underdeveloped.  Recognizing that all five clusters are coevolving, the phenomenon of service systems was listed in order from the most concrete (i.e.

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Metaphors and Models

What is a business?  How can (or should) an expert business practitioner relay his or her knowledge to another interested party?  Trying to understand these questions leads down a path of debating the merits and demerits of understanding through metaphors, and understanding through models.  This eventually ends up with a discussion of roots in philosophy of science.

During the Seiad project in 1977, Ian Simmonds and I had many discussions about understanding business, filling up the whiteboard in his office at the Watson Research Center.1 My studies into business strategy reflected the two primary foundations:  microeconomics  — Michael Porter is a leading proponent of this approach — and organization theory  — with roots in the research of the Tavistock Institute, and the sociotechnical systems thinking from Fred Emery and Eric Trist.  Add onto that my personal bent towards decision support systems — Peter Keen‘s research while at CISR at the Sloan School at MIT was highly influential — and a strategic view of marketing that can be described as Market-Driven Strategy, as described by George Day.  These all represent models of business.

Ian — as I recall, starting from a side discussion with Doug McDavid — brought up an alternative approach to businesses, with the book: Images of Organization, by Gareth Morgan.  I had a visceral response to this work, because it prescribed the use of metaphors to describe business.  The problem that I’ve found with metaphors is that they relay an initial — and possibly superficial — portrayal of business.… Read more (in a new tab)

What is a business?  How can (or should) an expert business practitioner relay his or her knowledge to another interested party?  Trying to understand these questions leads down a path of debating the merits and demerits of understanding through metaphors, and understanding through models.  This eventually ends up with a discussion of roots in philosophy of science.

During the Seiad project in 1977, Ian Simmonds and I had many discussions about understanding business, filling up the whiteboard in his office at the Watson Research Center.1 My studies into business strategy reflected the two primary foundations:  microeconomics  — Michael Porter is a leading proponent of this approach — and organization theory  — with roots in the research of the Tavistock Institute, and the sociotechnical systems thinking from Fred Emery and Eric Trist.  Add onto that my personal bent towards decision support systems — Peter Keen‘s research while at CISR at the Sloan School at MIT was highly influential — and a strategic view of marketing that can be described as Market-Driven Strategy, as described by George Day.  These all represent models of business.

Ian — as I recall, starting from a side discussion with Doug McDavid — brought up an alternative approach to businesses, with the book: Images of Organization, by Gareth Morgan.  I had a visceral response to this work, because it prescribed the use of metaphors to describe business.  The problem that I’ve found with metaphors is that they relay an initial — and possibly superficial — portrayal of business.… Read more (in a new tab)

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    • Reformation and transformation (Ackoff 2003, 2010)
      In his system of system concepts, Russell Ackoff made the distinction between reformation and transformation in many of his lectures. Here are two written sources. From Redesigining Society (2003) … Systemic Transformation A system is transformed, as contrasted with reformed, when its structure or functions are changed fundamentally. Such changes are discontinuous and qualitative, quantum […]
    • Goal, objective, ideal, pursuits (Ackoff & Emery, 1972)
      While Ackoff’s definitions of goals, objectives and ideals have been republished (and rewritten) multiple times, the 1972 definitions were derived from his original dissertation work.  Accordingly, in addition to the human-readable definitions, some mathematical notation is introduced. — begin paste — OUTCOMES 2.30. End (an immediate intended outcome) of a subject A in a particular […]
    • Pure Inquiring Systems: Antiteleology | The Design of Inquiring Systems | C. West Churchman | 1971
      The fifth way of knowing, as described by West Churchman, is a Singerian inquiring system. (This fifth way of knowing is more colloquially called Unbounded Systems Thinking in Mitroff and Linstone (1993)). The book On Purposeful Systems (Ackoff and Emery, 1972) was derived by Ackoff’s dissertation that was controversially coauthored with West Churchman. Purpose can […]
    • Process-Function Ecology, Wicked Problems, Ecological Evolution | Vasishth | Spanda J | 2015
      Understanding Process-Function Ecology by Ashwani Vasishth leads to luminaries in the systems sciences, including C. West Churchman, Eugene P. Odum and Timothy F.H. Allen.
    • The Innovation Delusion | Lee Vinsel, Andrew L. Russell | 2020
      As an irony, the 2020 book, The Innovation Delusion by #LeeVinsel @STS_News + #AndrewLRussell @RussellProf shouldn’t be seen as an innovation, but an encouragement to join @The_Maintainers where an ongoing thought network can continue. The subtitle “How Our Obsession with the New has Disrupted the Work That Matters Most” recognizes actual innovation, as distinct from […]
    • Republishing on Facebook as “good for the world” or “bad for the world” (NY Times, 2020/11/24)
      An online social network reproduces content partially based on algorithms, and partially based on the judgements made by human beings. Either may be viewed as positive or negative. > The trade-offs came into focus this month [November 2020], when Facebook engineers and data scientists posted the results of a series of experiments called “P(Bad for […]
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