Ontonix S.r.l.: The 787 Dreamliner, Complexity, Systemantics And Linear Thinking

“In the past few decades we have conceived, designed and constructed extremely complex systems and infrastructures on which our lives depend to a very large degree. The list is endless but it all comes down to huge networks, systems of systems, computers, software, information and communication, the internet, etc. Such systems are indeed very complex and yet they have been designed without taking complexity into account…”

Ontonix S.r.l.: The 787 Dreamliner, Complexity, Systemantics And Linear Thinking.

6 Responses to Ontonix S.r.l.: The 787 Dreamliner, Complexity, Systemantics And Linear Thinking

  1. Unfortunately in the English dictionary the words ‘complex’ and ‘complicated’ are synonyms when they maybe shouldn’t be. There is a lot of ambiguity and misuse of terms happening and because I discussed them Jacek banned me from his LinkedIN group which is really a bad sign of uncertainty.

    Jacek and many before him are really referring to complicated, designed systems when they use the term complex. Yes, complicated systems do also exhibit complex behavior and that is what brings all the unintended side-effects. Yes, we do need complicated systems like airplanes and we must be aware of the possible complexity. I seriously doubt that the complicatedness of a system is in any way a measure of its complexity. The complicatedness can be a pointer to the possible complexity, but that is all. There may be a lot more or less complextiy than the complicatedness suggests. As I said before, actions to reduce the complicatedness may seriously impact the beneficial complex interaction of the system.

    Many system thinkers show quite a lot of arrogance because they pride themselves that they can properly decompose systems so that they can be better controlled. That is the largest fallacy of all. Complex sysrtems cannot be designed but they evolve and they cannot be predicted because they exhibit emergence. Complex systems evolve to be resilient and often when measuures are taken to reduce complicatedness, i.e. BPM, Lean, and other mumbo-jumbo, the positive side-effects of complexity are reduced. Often the complicated parts simply are ignored and the system starts to exhibit complex behavior such as doing process management via email rather than the BPM tool.

    So it is grand fallacy to compare a 787 to a business. The two have absolutely nothing in common.

    • Hi Max, good to hear from you again.
      Ah, the ‘old chestnut’ of people who are intent upon leading/driving things in the ‘right’ direction (potentially) failing to do so because they cannot agree on a definition! In fairness to Jacek I can understand his frustration as he has had to deal with such scenarios on numerous occasions over many, many years.

      To me and (it would appear) others, such as Dave Snowden [Cynefin], the inability to predict, control or manage outcomes within a meaningful timescale, because of the number of interacting parts, defines a system that can be simultaneously simple, complicated, complex or chaotic.

      We like certainty but overlook the potential for uncertainty at our peril. We can never know the unknowable but can, at least (using techniques that aid decision-making), make some unknowns known.

      In a complex system, if we can know where, when and how the interactions among multi-scalar mono-human/human components occur we are closer to identifying causal relationships and gaining ‘anticipatory awareness’ i.e. the potential for intervention to maintain resilience, rather than being reliant upon outcomes. And being wise after the event, by which time unknown/unknowable damage may have been done and costs incurred.

      THAT is significant progress that has been tested time and again by Ontonix clients across a wide range of systems…incl. biological (healthcare), aerospace, aircraft, automotive, financial, etc. Surely that is a sound platform to move forward from rather than to be ‘stuck’ in discussions that lead us nowhere.

      A brief and incomplete response to many questions I know but time is against me and there is another of your comments that I haven’t yet responded to…I’ll get there!


      • Hi David, been always ‘here’ … always read your posts … don’t always have or take the time to comment my thoughts in case there is something to say. I am not trying to say anything abd about Ontonix or its products or concepts, but as you blog about it and it is a subject that is very close to what I see as solutions to current business problems, I will comment as I see fit.

        Yes, all systems are always complex and have to deal with chaotic conditions. If they are small, simple and sturdy enough then their interaction with the complex outside can be ignored until they break. With large systems the problem is that the breaking can be catastrophic. No disagreements on people loving certainty and using odd ways to try and get it.

        But that was not my point. You bring in a BIG-BIG-IF: ‘… if we can know, where, when and how the interactions occur.’ My point exactly … you don’t know and you won’t find out. Or in what way does the software help to do so?

        My point is that (naive) intervention will never increase resilience, while it may produce the wanted outcomes. Using the not-fitting example of the 787, the plane does fly as expected until the battery explodes. As I wrote in my posts on the subject, failure is the main learning method.

        I do not understand … but most likely you consider that your ‘secret sauce’ that I consider an empty claim until I understand what it actually is that you are doing for your clients … in what way some mathematical observation on a purely abstract and arbitrary model of the business will improve resilience. It doesn’t! What improves resilience is constant adaptation to the constant changing environment. And yes, I admit if businesses are built in the same manner as aeroplanes then they will exhibit the same problems of complicatedness.

        I am not stuck anywhere and you claiming that I don’t get it, simply means that you have been unable to explain it. I get the concepts and the consequences of complexity more than most people and in my own work in AI has I have dealt with it for years.

        You claim progress in the sense that you make transparent HOW the complicatedness of a business causes it to be brittle to certain stresses and events. If you can’t explain in a few sentences what the function of your approach is, I think you should try.

        Here is your opportunity to gain a fervent supporter of your approach and explain to many who have similar doubts what it is … I might even become a customer!

        Look forward to less brief and incomplete information. All the best, Max

  2. Max,
    Just so you know, as you are someone with vast experience and significant achievement, I appreciate your time and REALLY welcome your feedback as it can only help me improve upon my ability to ‘condense’ or better explain the Ontonix proposition…dare I say simplify the complex!?

    I actually thought we had done this before in previous exchanges but you have known down the gauntlet and I am happy to pick it up, particularly if there may be scope for US to tailor better solutions to such a widespread problem!

    To borrow a well known expression “I’ll be back”, as soon as time permits.


  3. Sorry for the delay Max! Let’s try this for simplifying the complex…

    A complex system is created with specific purpose(s), as a result of an unfulfilled need from an existing market or opportunity to satisfy a new/future market. The function(s) are enabled by networks of human/non-human sub-systems and processes, aligned to the ‘common purpose’ and structured to operate as interdependent, synchronous, components.

    The capability, capacity and effectiveness of the system cannot be determined from conventional [independent] measurement of data. This merely serves as a, subjective, basis for comparison against past, peer or predicted measurements…hardly surprising when you consider the performance of complex systems is greater than the sum of the parts.

    The complexity of the system, its interdependencies, the nature and integrity of its interactions are revealed as ‘hubs and nodes’ in the information-flow.

    That is the brief version but…

    Where clarification on “the Ontonix approach” is, perhaps, required is in relation to the “value” of a measure of complexity, being:

    the total amount of structured system information [measured in bits].

    According to our definition complexity is a function of structure and entropy [C = f (structure, entropy)] in the information, that is verification of system processes that enable function(s): http://wp.me/p16h8c-Fv

    We gain intelligence, NOT from conventional statistical analysis of data (these pre-suppose we know what we are looking for!) but from the system information that is the ‘digital footprint’ of the multi-scalar interdependencies and interactions among complex processes:

    identifying the relationships among all possible pairs of variables.

    The information exchange reveals the nodes and hubs of the (otherwise hidden), silo-free, structure in the data and the integrity of the interactions.

    The two key components of our complexity metric are the so-called System (or Complexity) Map – which reflects how information flows within a system – and entropy, which measures the degree of disorganization in the system.

    A Complexity Profile itself ranks the business parameters in terms of importance (=impact on overall complexity).

    The profile is computed using a technique known as “knock-out” in genomics.

    The equation is as follows but the infographics in this article may help –

    Complexity (of the ‘system’ – business model, or corporation, etc.)


    Uncertainty (of the environment, market, economy)

    = Fragility (of the situation)

    Evidently, U cannot be managed but C can.

    Measuring, monitoring and managing ‘current complexity’ is more effective than conventional means of assessing, rating, managing and modelling risk. And why it is better that a system be less complex [Occam’s Razor].

    The best way to impact C is by starting from the top of the Complexity profile. Because the profile is computed based on a model-free method, there are no subjective ‘weights’ to adjust. Basically, this guarantees that you hit the most important parameters first, i.e the hubs.

    I hope all this helps but PLEASE do not hesitate to fire any queries in my direction and I will respond as best I can. I would love to have you as a supporter, collaborator or customer!

    All the best.

  4. I should have said that, whilst it is possible to have complexity without function we CANNOT have function without complexity. Complexity aligned to function is ‘value adding complexity’ whilst excessive complexity is ‘value destroying complexity’: the demand for function is the result of an identifiable signal [information].

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