Complicated or complex – knowing the difference is important

Birds flocking provide a good example of a complex adaptive system

Birds flocking provide a good example of a complex adaptive system

Understanding the difference between complex and complicated systems is becoming important for many aspects of management and policy. With complicated problems or issues one can define the problem and strategically develop actions, time-frames and milestones along a path to success. In contrast, cause and effect are difficult to predict in complex adaptive systems. This post aims to provide more detail around these concepts as an introduction. It complements the LfS Managing complex adaptive systems page, which provides annotated links to a number of key on-line resources in this area.

A major breakthrough in understanding the complex world of organizations and socio-ecological environments is the field of systems theory.  ‘Systems thinking’ is a way of helping people to see the overall structures, patterns and cycles in systems, rather than seeing only specific events or elements. It allows the identification of solutions that simultaneously address different problem areas and leverage improvement throughout the system. It is useful, however, to distinguish between ‘simple’, ‘complicated’ and ‘complex adaptive’ systems.

According to a classic report in healthcare by Sholom Glouberman and Brenda Zimmerman systems can be understood as being simple, complicated, and complex. Simple problems, such as following a recipe or protocol, may encompass some basic issues of technique and terminology, but once these are mastered, following the “recipe” carries with it a very high assurance of success. Complicated problems, like sending a rocket to the moon, are different.  Their complicated nature is often related not only to the scale of a problem (cf. simple systems), but also to issues of coordination or specialised expertise. However, rockets are similar to each other and because of this following one success there can be a relatively high degree of certainty of outcome repetition. In contrast complex systems are based on relationships, and their properties of self-organisation, interconnectedness and evolution. Research into complex systems demonstrates that they cannot be understood solely by simple or complicated approaches to evidence, policy, planning and management. The metaphor that Glouberman and Zimmerman use for complex systems is like raising a child. Formulae have limited application.  Raising one child provides experience but no assurance of success with the next. Expertise can contribute but is neither necessary nor sufficient to assure success.  Every child is unique and must be understood as an individual. A number of interventions can be expected to fail as a matter of course.  Uncertainty of the outcome remains. You cannot separate the parts from the whole. The most useful solutions to problems usually emerge from within the family and involve values. An outline of the management differences between complicated and complex systems can be seen below in  Table 1.

Table 1 Managing complicated and complex systems (From Glouberman & Zimmerman 2002)

Complicated systems (like sending a rocket to the moon) Complex adaptive systems (like raising a child)
Formulae are critical and necessary Formulae have limited application
Sending one rocket increases assurance that the next will be OK Raising one child provides experience but no assurance of success with the next
High levels of expertise in a variety of fields are necessary for success Expertise can contribute but is neither necessary nor sufficient to assure success
Rockets are similar in critical ways Every child is unique and must be understood as an individual – relationships are important
There is a high degree of certainty of outcome Uncertainty of outcome remains

Complicated systems are all fully predictable. These systems are often engineered. We can understand these systems by taking them apart and analyzing the details. From a management point of view we can create these systems by first designing the parts, and then putting them together. However, we cannot build a complex adaptive system (CAS) from scratch and expect it to turn out exactly in the way that we intended. CAS are made up of multiple interconnected elements, and adaptive in that they have the capacity to change and learn from experience. Examples of CAS include ourselves (human beings), the stock market, ecosystems, immune systems, and any human social-group-based endeavor  in a cultural and social system. CAS defy attempts to be created in an engineering effort, and the components in the system co-evolve through their relationships with other components. But we can achieve some understanding by studying how the whole system operates, and we can influence the system by implementing a range of well-thought-out and constructive interventions.

Getting people to work collectively in a coordinated fashion in areas such as poverty alleviation or catchment management is therefore better seen by agencies as a complex problem, rather than a complicated problem – a fact many managers are happy to acknowledge …. but somehow this acknowledgement often does not translate  into different management and leadership practice. Of course, many issues will have all system types present (simple, complicated and complex), and there may well be multiple systems involved. What is important is distinguishing between system types, and managing each in the appropriate way.

Indicators of progress in managing a complicated system are directly linked through cause and effect. However, indicators  of progress in a complex system are better seen as providing a focus around which different stakeholders can come together and discuss, with a view to potentially changing their practices to improve the way the wider system is trending. Understanding this difference has important implications for management action as Table 2 below highlights. In many cases people continue to refer to the system they are trying to influence as if it were complicated rather than complex, perhaps because this is a familiar approach, and there is a sense of security in having a blueprint, and fixed milestones. Furthermore, it is easier to spend time refining a blueprint than it is to accept that there is much uncertainty about what action is required and what outcomes will be achieved. When dealing with a complex system, it is better to conduct a range of smaller innovations and find ways to constantly evaluate and learn from the results and adjust the next steps rather than to work to a set plan. The art of management and leadership is having an array of approaches and being aware of when to use which approach. Most issues will have simple, complicated and complex system types present, and there may well be multiple systems involved.

Table 2 Different leadership tasks for different systems (from Anderson & McDaniel 2000; Snowden & Moone 2007)

Complicated systems Complex adaptive systems
Role defining – setting job and task descriptions Relationship building – working with patterns of interaction
Decision making – find the ‘best’ choice Sense making – collective interpretation
Tight structuring – use chain of command and prioritise or limit simple actions Loose coupling – support communities of practice and add more degrees of freedom
Knowing – decide and tell others what to do Learning – act/learn/plan at the same time
Staying the course – align and maintain focus Notice emergent directions – building on what works

As Irene Ng points out in her Complicated vs Complex Outcomes post we have spent the last 100 years doing complicated rather well. “We can pat our backs on putting the man on the moon, doing brain surgeries etc. We are now moving to a world where complex outcomes matter and this is a new capability. This capability uses different words. We can determine complicated outcomes. We can only enable complex outcomes. We can specify complicated systems. We can only intervene in complex systems. Often, the best way to think about whether a system is complex or complicated is to ask – ‘what is the outcome’; ‘is it achievable through a command and control structure’ and if the latter is no, then it’s usually complex.”

In complex situations it is useful to move beyond thinking of ‘a change’ that will fix the system, and instead look for a number of leverage points that may be changed to improve the system. Changing what people do, for example, may require changes in rules (e.g. laws, protocols and tacit norms), changes in relationships, networks and patterns of behavior (e.g. how conflict is handled, how mistakes are managed, how power is used), and tools (e.g. databases, checklists, guidelines) for this change to ‘stick’. One-sized fits all approaches are unlikely to work in complex adaptive systems. The way solutions are visioned and delivered locally must reflect the values, contexts and cultures of each different community.

Finally, as with raising a child, people working in these complex adaptive situations need to keep learning about that situation, and to keep talking and working together in an ongoing way. Future visions and common goals need to be openly discussed and negotiated, and tentative pathways forward charted. While some actions will be taken by individual agencies working alone, new layers of creative collaborative and partnering arrangements will need to emerge. In these situations agencies should look to theories of change, to go beyond linear paths of cause and effect, to explore how change happens more broadly and then analyze what that means for the part that their particular agency or program can play.

Related resources

It complements the LfS Managing complex adaptive systems page, which provides annotated links to a number of key on-line resources in this area. The previous blog post provides an introduction to theories of change, and a set of annotated links to key resources in this area can be found from the LfS web page – Theory of change. The BetterEvaluation Blog also has a very useful and related posting Addressing complexity which discusses the growing topic of how to address complexity in evaluation.

9 thoughts on “Complicated or complex – knowing the difference is important

  1. Margaret

    Thank you very much, Dr. Allen!
    You have very clearly analyzed the difference between complicated system and complex adaptive system(CAS). I love it. It makes me much more understanding now.
    I really appreciate and thank you for spending your time on sharing your excellent point of view of this complicated CAS with us.
    I learned a lot from your post.
    Highly recommend: It is very useful if someone is confused with the two concepts: complex and complicated.


  2. Diana

    Interesting that these words are used in systems definitions contrary to their English definitions.
    Usage: Although complex and complicated are close in meaning, care should be taken when using one as a synonym of the other. Complex should be used to say that something consists of several parts rather than that it is difficult to understand, analyse, or deal with, which is what complicated inherently means

  3. brano


    This view is similar to

    There is another view. The Zeno of Python states (from wikipedia):
    -Simple is better than complex
    -Complex is better than complicated

    My conclusion is:
    System with few elements is simple, system with many elements is complex.
    We can have simple system which can be very complicated and outcome is hard to predict.
    And contrary, complex system (like processor) can have many elements but outcome is very accurately predicted.

    Can you comment this view ?



  4. Susan Goff

    Hello Dr Will, And I whole heartedly join in expressing my appreciation and gratitude for the work you have done here. A formidable form of curating. You have kindly invited me to contribute and I have chosen this entry point. I work in Australia as a Participatory Action Research practitioner. My primary intention is to work on the complex issue of reconstructing humanity’s relationship with planetary systems for the health and wellbeing of future generations. Sounds impossible and as if I have major problems with my ego – but working at the edges of the problems in every day public, professional and private life just makes it the thread of life. Currently in Australia the voices of our First Nations peoples are finally becoming audible. This is largely to do with the activism and astounding resilience of the original peoples and their cultures. As a non-indigenous inhabitant of their countries my interest is to learn with them when they choose to share their journeys with me and then turn my own voice back to “my” own peoples (I am Pakeha but see “my” people as anyone who has arrived since 1788 whatever their cultural background may be) and work to create spaces in which First Nations peoples can be heard and included in mainstream interventions, if that is what First Nations peoples see as being what they need and can do. I do not speak for others, but express my learning and face the assumptions that others make in a manner that questions them from the learning I have been given and made. This is a really difficult, complex space. And as non-indigenous peoples are increasingly educated by First Nations, the more of us are participating in these complex, adaptive systems. It is very consistent with your statement of moving beyond envisioning a “change” and move instead to improve the conditions of a system in which change needs to come about. It is a praxis issue involving presence and discourse. In this instance the change is my being, in relationship with others, and the heuristic of self critical inter-subjectivity that we can co-create. The most difficult of these spaces are these where First Nations peoples are also present and witnessing this shift in non-Indigenous perspectives and actions. Recently I was in such a space and speaking of decolonisation as the context in which we are operating. My First Nation colleague commented that it was OK to speak of this, but the risk is that others will think that we just tick that box and move on. I purposefully do not use the language of “post colonial” for this very reason. But I completely take the point of the risks; on the other hand to remain entrenched in perspectives and feelings that we no longer possess because we are learning to do and be better just holds everyone down. I would be very interested indeed in any reflections anyone has from the perspective of CAS with regard to this problem.

  5. Kptn Blizz

    Even if a complicated systems is fully predictable (e.g. technical engineering) – Its (long-term) effects in complex systems like our socio-economic system and ecosystem are still far from certain. that should be considered especially within our technological practice.

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  7. Augusto Carreira

    I enjoyed the reading, which is in line with my own thinking on the subject. The terms complex and complicated are undergoing a semantic twist (Diana’s comment) that I think will eventually become permanent. Complexity and complication deal with information. A complicated system (a car, for instance) can be fully discovered and described, so that information requirements to deal with it become quite low. A complex system (urban traffic, for instance) can never be fully discovered and the information required to understand it changes dynamically, hence being always quite high. Yet we can deal with it, but only locally, i.e. on a subset of the system that is at at an arm’s reach.
    I didn’t like the “adaptive”, as in CAS. Complex systems don’t have to be adaptive, in spite of a substantial subset of complex systems being adaptive.

  8. Guy Hoelzer

    Branko: I think your post is confounded by your use of the word “system”. If the parts of the whole have organically come to compliment one another as they relate to the function of the whole, then you have a complex dynamical system. Complicated systems can be engineered, which means they are devised rather than organically developed. I think it is misleading to classify these kinds of systems based on the number of parts. You can have complex systems with few parts. I like thinking about the semantics of this set of terms: complexity, simplicity, complicity, and simplexity.


    Guy Hoelzer

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