The STREAMS confluence

The STREAMS Confluence

The maturing shift in Enterprise Architecture thinking

Previously I have written about Enterprise Architecture from several different perspectives – philosophical, technical, practice, knowledge etc. However, what all the previous articles had in common is that they were built on existing, established, even if not commonly-recognised, knowledge.

There is little in them that is completely novel and not just an extrapolation from or novel integration of what was previously known.

In this article, I want to be a little more speculative and forward-looking. I am suggesting that there is a coming together of thinking from several different areas of social and management science towards a new, more scientific approach to the design and management of large, complex human enterprises. I call this knowledge/thought nexus “The STREAMS Confluence”, for reasons which will become obvious. I also suggest that at the centre is an emerging and evolving integrative interdisciplinary field which we might call “Enterprise Architecture”.


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What are the STREAMS?

“STREAMS” is an only-a-little-contrived acronym standing for “Systems Thinking, Real Enterprise Architecture and Management Sciences”.

Systems Thinking, I have discussed before, and many knowledgeable Enterprise Architects and Enterprise Architecture scholars now regard it as the proper theoretical basis for the discipline.

You cannot manage what you cannot understand and traditional Scientific Management doesn’t understand modern enterprises anywhere near well enough – just as I.K.Brunel could not understand and manage Internet TV.

The “Real” in “Real Enterprise Architecture” refers to two things as follows.

1) The form of the discipline that takes its subject-matter to be the real-world constituents of the enterprise: its people, its technologies, its principles and objectives and how they are organised to achieve purposes. In this conception of the discipline, it is not primarily about manipulating models but about real-world change in the enterprise.

The range of technologies employed in enterprises is also far wider than just the so-called information technologies – and so the discipline is about the real world that includes vehicles and plants as much as (or more than) the virtual- or cyber-world of computer programmes and information flows.

2) Relatedly, it refers to a new form of philosophical Realism that supersedes and rectifies the mistakes of the traditional naïve Realism of the Steam Age. We are still living with some of the consequences of these mistakes including the inappropriate conception of human-intensive enterprises as machines, a misguided belief in linear, deterministic causality, an over-commitment to reductionism in analysis and an over-emphasis on the functional aspects of systems to the neglect of other aspects.

These mistakes and misconceptions can be seen at work every day in businesses and public-sector organisations. They are also the fundamental reason why traditional so-called Scientific Management struggles to maintain control in modern enterprises.

You cannot manage what you cannot understand and traditional Scientific Management doesn’t understand modern enterprises anywhere near well enough – just as I.K.Brunel could not understand and manage Internet TV.

This new form of Realism – it dates from the 1970s, which on philosophy timescales is relatively new – is labelled “Critical Realism”. [Right or wrong, that label has stuck.]

It distinguishes three layers of reality: the Real, the Actual and the Empirical and takes seriously the emergence of higher-level structures and phenomena from lower-levels. Its application in the analysis, management and direction of enterprises is described in two excellent books by John Mingers who is now at the University of Kent Business School: “Realising Systems Thinking – Knowledge and Action in Management Science” (sic) [1] and “Systems Thinking, Critical Realism, and Philosophy – A Confluence of Ideas” [2].

A shift in Enterprise Architecture thinking

I freely confess that I took the notion of a confluence of ideas from John Mingers.

“This is a highly opportune time when different fields – critical realism, philosophy of science, and systems thinking – are all developing around the same set of concepts and yet not realising it” as he puts it in the latter book. But I think the range of fields converging is perhaps wider than he himself realises.

It corresponds with a maturing shift in Enterprise Architecture thinking – which I’ll mention later – and perhaps marks the emergence of a new, properly science-based engineering-management discipline for human enterprises.

The “Management Sciences” part of STREAMs refers to a collection of methods and techniques, linked by an underlying methodology and theory, that might be taught on a “Management Science” course. This itself is something of a broad and fuzzy category and includes :-

  • methods and methodologies of Project, Programme and Risk Management like the Critical Path Method (CPM);
  • methods of financial analysis and planning such as Activity Based Costing or Capital Rationing; and
  • methods of Operational Analysis or Operations Planning like Process Mapping, Capacity Planning and Job Scheduling.

It also includes general numerical techniques – such as the use of statistics and probability, expected and expectation values, interpolation and extrapolation, forecasting and projecting, and ‘technical’ analytic techniques like general Network Analysis (of which PERT/CPM is a particular application), Ishikawa diagrams, Defect Analysis, Statistical Process Control etc.

Just as in building architecture – blueprints are irrelevant unless something is actually built using them. Enterprise Architecture should be about real change in the real-world, not just playing around with meaningless models.

Often, these methods are included under the banner of “Quality Management” – which can be considered a management science.

One particular identifiable field that might be included as either Management Science or Systems Thinking is “Operational Research” (OR). Traditionally, OR has been concerned with creating an appropriate algebraic mathematical model – writing some descriptive equations – of some organisational situation or process and then using algebra to solve them to find the optimum solution.

Recent years, however, have seen a shift towards not solving the models algebraically but numerically through computer simulation [hence, applying numerical methods such as Perturbation Theory, Linear Programming and Runge-Kutta Methods of numerical integration.]

This sort of numerical simulation has become a new research and development tool in several different fields of science, design and engineering – such as astronomy, and aeronautical and automotive engineering.


Even the intermediate stage of developing a mathematical model as a set of dynamical equations has become somewhat optional – and analysis can proceed straight from inferred regularities in empirical data to projections and predictions in numerical simulations. This is, of course, driven by the increasing number-crunching power of computers, databases and networks of computers.

The recent IT trends of so-called “Data Mining” and “Big Data” might be seen as the latest fashionable embodiments of this trend to data-centrism in Operational Research. At the same time, a shift has happened in Enterprise Architecture away from static structural models towards dynamic models in simulations (and modern, good EA modelling and repository tools increasingly include simulation facilities).

In my speculative view, all these fields are converging on or around a common set of shared ideas and principles.

The most obvious is a commitment to the use of models to understand things and direct change. Perhaps the second most obvious is that of seeing reality and problem situations in human enterprises as “Intelligent Complex Adaptive Systems of Systems” (ICASOSs) – with interdependent strata, domains and silos, complexity, dynamics and inter-linkage.

This recognition of the dynamic complexity of interlinked systems leads to a common commitment to holistic multifactor analysis – and a rejection of naïve, simplistic reductionism and assumptions of deterministic, linear causality in favour of more stochastic, probabilistic, trends, chaos and complexity perspective.

This in turn may lead to an eclectic mixing of methods from several historical paradigms – even from paradigms that assert their own incommensurability sometimes. It also leads to a recognition of the limits of analysis in terms of linear deterministic causation – and hence to taking emergence of both structure and dynamics in the ICASOS seriously.

It is also the source of the imperative to do a synthetical construction as well as an analytical deconstruction when trying to understand and change the situation. Emergence and complex dynamics over time naturally entail an adaptive and evolutionary perspective – which leads to a reconsideration of the nature and effectiveness of forms of intervention. And a recognition of the limits or difficulty of ‘control’.

The shift in thinking

This convergence I call “The STREAMS Confluence” represents a shift in thinking beyond the naïve scientistic and hubristic modernism of the 1950s, 1960s and 1970s – and beyond the negative and unproductive anti-science reaction against it of so-called postmodernism of the 1970s, 1980s and 1990s towards a more rational and holistic scientific attitude that transcends and supersedes both.

I don’t think I’m the only one to have noticed this trend – John Mingers also clearly has.

I think the Laszlos have also noticed it in their field and call the emerging discipline “Evolutionary Management” [3]. Pallab Saha, and collaborators, have noticed the shift in Enterprise Architecture and in an earlier book [4] called the emerging, more mature Enterprise Architecture “Coherency Management” but in his latest book [5] he reverts to “Systemic Enterprise Architecture”.

Gerald Midgley, coming from a ST perspective appears to think it is just the natural outcome of maturing ST and calls the new discipline “Systemic Intervention” – if I read his book right [6].

Other systems thinkers – such as Flood and Carson call it the “Management of Complexity”. [7] Jan Hoogervorst and Jan Dietz express similar views but label the emerging discipline “Enterprise Engineering” – and reserve “Enterprise Architecture” for the pure modelling activity. [8] [Personally, I think delineating EA as only modelling activity – as opposed to coordinating and driving change in enterprises – runs the risk of making it self-referential, self-contained, inert and irrelevant. Just as in building architecture – blueprints are irrelevant unless something is actually built using them. Enterprise Architecture should be about real change in the real-world, not just playing around with meaningless models.]

Whatever you call it (what’s in a name?), this is a cultural shift – a widespread shift and coming together in human thinking – that starts with Systems Thinking, has Real Enterprise Architecture in the centre and is rounded out with the Management Sciences. So calling it “The STREAMS Confluence” seems to me quite apposite.

This new way of thinking and doing should lead to much better – more effective and more efficient – human enterprises. Pallab Saha’s new book [5] describes how it could be applied for better Governments. If this is correct therefore, people should be promoting a change in thinking in the enterprises they are associated with.

How would you drive such a culture change in yours?

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[1] Mingers, J., (2006), “Realising Systems Thinking – Knowledge and Action in Management Science”;
[2] Mingers, J., (2014), “Systems Thinking, Critical Realism, and Philosophy – A Confluence of Ideas”;
[3] Laszlo, E. and Laszlo, C., (1997), “The Insight Edge: An Introduction to the Theory and Practice of Evolutionary Management”;
[4] Doucet, G., Gøtze, J., Saha, P. & Bernard, S. [Eds.], (2009), “Coherency Management – Architecting the Enterprise for Alignment, Agility and Assurance”;
[5] Saha, P., (2014), “A Systemic Perspective to Managing Complexity with Enterprise Architecture”;
[6] Midgley, G., (2001), “Systemic Intervention: Philosophy, Methodology, and Practice”;
[7] Flood, R.L. and Carson, E., (1993), “Dealing With Complexity – An Introduction to the Theory and Application of Systems Science”;
[8] Dietz, J. and Hoogervorst, J.A.P., (2012), “The Principles of Enterprise Engineering”, Advances in Enterprise Engineering, Vol. 1, No. 10.

Image courtesy Aaron Burden@unsplash.com

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