Complicated or complex – knowing the difference is important

Understanding the difference between complex and complicated systems is becoming important for many aspects of management and policy. Each system is better managed with different leadership, tools and approaches. This post explains those distinctions and introduces approaches suited to working adaptively in complex, real-world contexts.

[Originally published February 2016. Updated October 2025 to include new reflections and links to recent resources.]

A major breakthrough in understanding how to manage complex multi-actor situations and programs has come through the fields of systems thinking and complexity-aware practice. Systems thinking helps people see the overall structures, patterns and cycles in systems, rather than focusing only on specific events or elements. It highlights interconnections and leverage points for improvement across a wider system. Complexity-aware practice complements this by emphasising feedback, emergence, and learning over control, helping teams stay responsive as situations evolve.

Simple, complicated or complex

It is useful, however, to distinguish between different types of systems. According to a classic report in healthcare by Sholom Glouberman and Brenda Zimmerman – Complicated and Complex systems: What would successful reform of Medicare look like? – systems can be usefully seen as lying along a broad continuum from ‘simple’ to ‘complicated’ to ‘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 the problem, but also to their increased requirements around coordination or specialized 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, interconnections 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. Formula 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. The most useful solutions usually emerge from discussions within the wider family and involve values.

Management implications

These differences have practical implications for management. Complicated systems are usually predictable and can often be engineered. We can understand them by analysing the parts and how they fit together, then design and assemble them in a planned way. Complex adaptive systems, by contrast, cannot be built from scratch and expected to behave as intended. They are made up of many interconnected elements that change and learn from experience – their history matters. Examples include ourselves, ecosystems, markets, and any group of people working together within a social or cultural context. In these settings, relationships shape outcomes, and the system evolves through these ongoing interactions. While we cannot control such systems, we can still influence them through thoughtful, well-timed interventions that strengthen patterns that work and help shift those that do not.

Systems thinking offers powerful ways to make sense of patterns and interconnections, but in complex settings these tools are best understood as heuristics for reflection and learning, not predictive models. They help us frame questions, visualise relationships, and identify potential leverage points, but they do not tell us what will happen. Complexity-aware practice complements systems thinking by keeping us attentive to uncertainty, feedback, and emergence, supporting an ongoing process of sense-making and adaptation rather than fixed design.

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, 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.

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 actors 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 the table 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 plan, and fixed milestones. Furthermore, it is easier to spend time refining a plan 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 lies in having an array of approaches, and being aware of when to use which approach. Most situations will have simple, complicated and complex system types present, and there may well be multiple systems involved. What is important is distinguishing between system types, and managing each in the appropriate way. Table 1 looks at different leadership roles that can be employed depending on whether one is dealing with a complicated or complex system.

Table 1: Different leadership roles for different systems

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 learning and innovation are becoming key outcomes, and delivering these requires new skills and capacities. As Irene Ng so eloquently puts it, “We can determine complicated outcomes. We can only enable complex outcomes. We can specify complicated systems. We can only intervene in complex systems.”

Look for leverage points

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 adjusted to improve the system. Encouraging the development and implementation of new work practices, 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 the use of a range of tools (e.g. databases, checklists, guidelines). One-size 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 of actors.

Those working with complex adaptive systems can add most value by supporting reflection and collaboration among the people involved. Shared visions and goals are best developed through open discussion and negotiation, helping chart tentative pathways forward. Over time, these practices build the relationships and partnering arrangements that enable ongoing innovation and more sustainable outcomes.

Continuing relevance (2025 reflection)

Almost a decade on, the distinction between complicated and complex systems remains central to how we think about change. It underpins much of today’s practice in adaptive management, developmental evaluation, and co-design. Importantly, systems thinking tools are now widely used as learning heuristics – ways to explore and question relationships – rather than as models to predict outcomes. Complexity-aware approaches build on this by emphasising emergence, adaptation, and collective reflection as essential to working effectively in dynamic, multi-actor contexts.

A recent companion post, Working between systems and complexity: a practitioner’s guide, builds on this foundation and explores how systems thinking and complexity-aware approaches can work together in practice  – helping practitioners navigate between structure and emergence.

Readers interested in exploring these ideas further may find the following site posts helpful: Working with complexity which builds on the concept of complex adaptive systems; Evaluation in complex settings which introduces complexity-aware monitoring and learning (CAMEL); and Designing together which reflects on facilitation and collaboration in co-design. Together these posts show how the distinctions first outlined here continue to shape systems thinking and systemic design practice.

Together, systems thinking and complexity-aware practice help us move from seeking control to supporting learning. They offer practical ways to navigate change, reflect collectively, and act with greater awareness in complex, multi-actor settings.

More information on tools and methodologies to implement systems thinking can be found through the linked LfS pages on  systemic design,  systems thinking tools and conceptual modelling.  Theories of Change and associated outcomes models are useful tools which help managers 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.

If you’ve found this topic helpful, consider sharing it with others who might benefit too. You can also sign up for occasional site updates to hear about new tools, guides, and key resources.

[* Image: Red-billed quelea flocking at waterhole – Photo by Alastair Rae, via Wikimedia Commons (CC BY-SA 2.0)]