Complexity CAN be managed…but only once it is measured

This article refers to complexity from an engineering perspective BUT, as the Ontonix “solutions” are model-free AND we already provide bespoke engineering products, the most significant aspect is the reference to COMPLEXITY AS A SYSTEM PROPERTY: Complexity demands a new mindset

We particularly liked this this quote:

“In a complex system, learning how all the pieces—constant and variable—interact gives a depth of understanding that averts catastrophe. That is what we mean by humancentred design—understanding the interfaces among technology, people, communities, governments, and nature. This is what makes complexity manageable”

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This is as close to our definition of complexity as I have seen but, in keeping with every other “expert” opinion on the subject, it still lacks a means of measurement so we aren’t quite sure how the author intends that complexity become “manageable”.

We have no such issue to overcome and are able to offer, even the most hands on C-level Executives, an insight into their organisation…and its ecosystem…that they could hitherto only have dreamt of.


What’s more we are able to deliver this “inside to out” (i2o) analysis by utilising the type of business information (BI) that is now recorded and monitored as a matter of course.

This graphic (on the left) summarises our approach. But of course there is much, much more to it than that! Otherwise how could we work apply our, model-free, technology in areas as diverse as Air traffic control – banking – mining – telecoms – healthcare – engineering – medical research – insurance – asset management – IT systems – petro chemicals – automotive.

So, we have already discovered a diverse range of applications but we believe that there are many more opportunities. Adoption has been slow but momentum has really been gathering and our Global footprint is increasing almost monthly. There are reasons for this gradual spread amongst which are the “nature” of the people involved with Ontonix. From the creator to the latest addition to the “Ontonix family” the people are committed, serious and dedicated to improving the organisations with whom we work. We aren’t salesmen! I want to ensure that we help organisations get and stay “fit for randomness”.

It would also be fair to say that complexity, as the term would suggest, is not easily understood or, for that matter, explained!!! Despite this and the apparent lack of a credible published definition IBM recently reported that may CEO’s across the globe are fearful of growing complexity and their ability to manage it in coming years. They are not alone. And, as the threat of complexity is not limited to the economic domain, it is hardly surprising that scholars, consultants (incl. McKinsey), regulators, Central banks, social, political and economic commentators have identified complexity as a huge and growing threat.

Of course we are grateful that so many influential people are publicising this issue…even when we disagree with fundamental aspects of their definition, approach, etc.

I think, by now, that the point is made..if not or if you want to know more please feel free to catch up on some previous blog items from the list below or view this more in depth presentation…but I would like to share with you this “definition” from a VP at a respected (Financial Services)innovation consultancy as we were discussing the recent IBM report:

“complexity, that could be defined as “hard to universally understand”. In products, it is the hard to understand features, benefits, administrative routines, variety of state regulations to adhere to, etc. Inside in the operations world, it reflects product complexity but it also reflects intangibility and sometimes even negativity associated with the products, causing people to behave differently from each other when certain challenges are present. A surefire way to know that complexity exists is when your people do not explain the strategy, a product, a market, a service, etc the same way. The heaviness of project management teams and long term processes, high operating costs, are all key indicators that complexity exists in an organization”

I am glad to say that this was the source of some considerable amusement for both of us and I very much doubt that this person would be offended that I referred to it. My response:

As far as I could see there was no definition of complexity in the IBM report. My first reaction was “if there is no definition how did IBM ask the question” and, if the respondents are leading CEO’s, “how could they answer a question about a term that did not appear to have been defined for them?”. THEN it occurred to me “if IBM don’t know what it is and the CEO’s haven’t asked what it means…”WHY THE HELL ARE THEY SO AFRAID!?”

Thankfully things fell into place when I read your “definition”.

If that was what IBM used as a definition no wonder CEO’s are afraid. I reckon I’ve got a pretty good handle on complexity but even I am scared to step outside.

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9 Responses to Complexity CAN be managed…but only once it is measured

  1. Shim Marom says:

    David, can you provide a link to the IBM publication referenced above?

  2. Shim Marom says:

    Hi David, having read the IBM’s “Capitalizing on Complexity” document I would like to make the following observations:
    1. I like, but only as a starting point, the definition above, being that “complexity is anything which is hard to universally understand”. This is too simplistic as there is no such thing as “universally”. Not sure if I could refine it any further as it will become too obscure to make any sense.
    2. I’m not against leaving the term undefined and leaving it to the individual to maintaing whether a particular paradigm is complex based on their subjective evaluation model. The fact that an X% of CEO’s have chosed to define something is complex, even without having a unique definition, is perfectly ok, as it represents their appreciation of reality, and for them that’s the only thing that matters.
    3. Having said that, just because we can’t define it does not mean we can’t measure it. Simply counting the number of moving parts would provide a fairly good starting point for measuring a complexity of a system. The more parts, the more complex the system is.
    4. The IBM document focused on CEO’s where my area of interest is technology and I would have loved to know what the CIO’s and CTO would have said given the same questions. My assessment is that they would (or should) have come up with similar observations.
    5. There is growin body of knowledge and anecdotal evidence to dismiss any notion that complexity is not an issue. It is certainly an issue and from my perspective the only way to deal with complexity is by introducing or substituting it with simplicity. I’m giving this point some attention in my own blog.

    I know I was late but hope I get a pass nevertheless.

    Cheers, Shim.

    • Shim Marom says:

      …and apologies for the spelling mistakes, should have checked before hitting the ‘post comment’.

    • Shim
      Thanks for your comment (don’t worry about the *spolling errirs*! Apologies for the delay in replying as I have been between Glasgow and Edinburgh over the last few days…in London start of next week, so thought I would write a very brief response.

      I must say that I don’t share your “enthusiasm” for the IBM definition. Principally because it is too vague to be useful!!! It contributes little to anyone’s ability to get to grips with the subject and, therefore, to begin the process of seeking solutions to specific problems. Of course Ontonix have determined our own definition, which, in view of the many schools of thought, will not satisfy every one – when is that possible!? – BUT, the most significant consideration is that ours has the unique distinction of being measurable and can therefore be applied.

      I like the commonly used reference to complexity being “problem solving capability”. This extract from my blog “The link between procrastination and complexity

      If complexity is created to facilitate problem-solving we educate (add complexity) to our brain to deal with the tasks that confront us on a daily basis as we go about our lives or in the workplace.

      We train our body to manage tasks requiring physical exertion

      We develop our business system to add functionality and create competitive advantage

      We expand our social and business groups to enrich our lives – and to resolve “bigger” problems together INTERDEPENDENTLY

      We add to our IT network and computer memory to ensure there is adequate speed and capacity, etc.

      As far as the ability to count the number of “moving parts” is concerned, that can certainly be misleading. A Swiss watch may have thousands of parts yet is not able to “surprise” in the manner of a complex system. It is certainly complicated but limited in function. It either works or doesn’t.

      On the other hand a system with very few components, for example, a small family unit of even 3 or 4 – YOU will already be VERY well aware – is enormously complex with the ability to shift (apparently without warning) from one mode of behaviour to another. Giving the appearance of equilibrium but capable of extreme unpredictability, hard to manage…but I reckon I don’t need to be telling you about that!

      Finally, replacing complexity with simplicity sounds and is sensible. That is until you try to do it! Hence, I suspect, Einstein’s famous quote.

      How does one reduce complexity without reducing functionality?

      Given two scenarios delivering the same outcomes how does one apply Occam’s razor? That is, how does one determine which is the simpler solution for a complex system without measuring the amount of complexity or the inter-connections within a complex system to determine that something that appears to be (intuitively) the “right way” is actually better addressed by a counter-intuitive action – this is not uncommon in complex systems.

      I believe that a valid example is the dilemma facing many organisations involved in Supply Chain activities in the current economic climate. Years of embracing a “Lean” philosophy would suggest that, in a downturn, redundancies are an obvious course when, in reality that may be sufficient to add fragility to an already fragile structure.
      Nassim Taleb oft refers to the need for redundancy in a system (a great example being the human body: 2 eyes, lungs, kidneys, etc.).

      Definitely counter-intuitive and a hard sell to most CFO’s…UNLESS YOU ARE ABLE TO MEASURE and make decisions based upon a quantitative assessment. Businesses need to ensure that they and their employees focus upon better decisions, because to judge the quality of a decision based upon the outcome is akin to putting all your eggs in the one basket and exposing it to the randomness of innumerable variables affecting the system, its ecosystem, inter-connected systems, networks, etc.

      The outcome may be OK but is not repeatable. If it isn’t OK it could be terminal! In which case the impact is not merely fatal for the business in financial terms but the inter-connectedness communicates that risk into its ecosystem and beyond. In addition to the impact upon the ECONOMIC domain, there is the unavoidable consequence for the employees, their families, community, etc so both SOCIAL and CULTURAL domains. Of course some poor decisions can have a severe impact upon the ENVIRONMENTAL domain which, amplifies and feedback into others, etc, etc.

      I hope that this provides you further food for thought? Rest assured I am in no position to determine whether someone pass or not, because, apart from not being formally qualified to do so, as far as I am concerned ANYONE who is thinking about the issue(s) has the potential to contribute to bringing about solutions. Even just by sharing concerns with colleagues or friends. So you keep thinking and keep in touch.


  3. Shim Marom says:

    Hey David, thanks for your thoughtful reply. Some food for thought here.

    Cheers, Shim.

    • Shim,
      When I got a chance to read it through late last night I had to laugh at the reference to a “very brief response”!


      • Shim Marom says:

        I”m still not happy with where we got to. More specifically your rebuke of the IBM definition. Let’s look at thiws again: “complexity is anything which is hard to universally understand”. I’ve gone throught your comment and couldn’t narrow down what your explicit definition it. Can you clarify?

      • Shim
        Sorry for the delay I was in London for meetings and am paying the price with lots to do…so blog stuff suffers! I hear but you are saying BUT I am comfortable with my “critique” of the IBM definition. If someone professes the ability to treat or cure an ailment of the mind I am entitled to believe that they have a detailed knowledge of the subject matter it is “universally” understood that the brain is complex and magnificent! Since Complexity Theory evolved out of Chaos (almost literally with so many disciplines, independently, reaching similar conclusions) there is no one agreed definition. It is such a vast subject, with so many centres for study and applications that this is not about to change in the near future. Fine if you are an Academic. NOT fine if you have common and recurring system challenges that can be addressed [mapped; measured; managed; monitored] across a variety of systems. There is always a need for philosophy but when a theory can withstand the rigours of a “hard science” approach and can bring benefit, irrespective of the system (health/business/aerospace/auto/IT/financial), do you disregard it because it does not fit exactly to someone else’s philosophy; pursue universal acceptance of a new definition; demonstrate, apply and gather support through results?

        I can recommend Jacek’s last book for further reading on the subject. It is now available as an ebook – Amazon Kindle ebooks: required complexity reading Practical Complexity Management is a very interesting collection of articles and blog items covering complexity from just about every imaginable angle!

        Rather than attempt to further re-invent the wheel I have extracted the following from one of our Ontonix documents. There is a considerable amount of information on the website and via this blog. I hope you find the clarification you seek. You may not, ultimately, agree with our definition but you will certainly not be short on reading material and MOST IMPORTANTLY a, 100% objective, quantitative methodology that has been and is being applied across a diverse range of systems: Complexity Management…

        What is Complexity? A widely accepted definition of complexity doesn’t exist. Many of the definitions refer to complexity as ”a twilight zone between chaos and order”. It is often sustained that in this zone Nature is most prolific and that only this region can sustain life. Others claim that the phenomena of self-emergence are manifestations of complexity. But such definitions are not practical since they don’t define anything measureable. At Ontonix we sustain that the fitness of a system is equal to its complexity. The evolution of living organisms, societies or economies constantly tends to states of higher complexity precisely because an increase in functionality and fitness allows these systems to better face the uncertainties of their respective environments, to be more robust, in other words, to survive better. Complexity, in our view, is not a phenomenon on the edge of chaos; it is an attribute of any system, just like energy, or momentum. Therefore, it can be managed.

        According to our philosophy, a comprehensive complexity metric should be a function of the following fundamental ingredients: structure, entropy and coarse-graining. Structure describes the way information flows within a given system. This may be represented via maps (graphs) such as those determined by OntoSpace™. Entropy represents uncertainty and the level of organization. Coarse-graining is essentially equivalent to granularity or resolution with which we manipulate data relative to the system. Very often, we can only express fuzzy statements about a system’s state (e.g. hot, very hot, extremely hot, etc.) or about given risk levels (very low, low, medium, high or very high). Complexity measures based exclusively on graph structure or entropy tell only part of the story.

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