‘Cake Rocket Child’: A problem typology tool

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What is it and why is it useful?

Cake Rocket Child is a tool to help you think about the nature of the problem you’re working with.

We call it ‘Cake Rocket Child’ because the original version, which the below is adapted from, compared the characteristics of three different types of problems (simple, complicated, and complex) with three examples:

baking a cake (simple problem)
sending a rocket to the moon (complicated problem)
raising a child (complex problem)

A fourth category, ‘wicked’ problems, was added in later versions.

Wicked problems are entrenched, highly complex, societal problems. For example, biodiversity loss, childhood obesity, or illegal immigration. Most social sector organisations are dealing with complex or wicked problems.

The original framework was designed to show how our ways of solving social problems often fail because they are mismatched to the nature of the problem they are trying to address.

The model is not saying that raising a child is harder or easier than sending a rocket to the moon, just that the characteristics of the problem are different. Understanding the characteristics of the problem you’re dealing with is vital to designing an effective solution. For example, multi-causal, fluid problems won’t be solved by singular approaches with rigid, long-term plans.

The table below can help you consider the nature of the problem you are working on and whether your approach is appropriate for that kind of problem.

Type	Simple	Complicated	Complex	Wicked (highly complex)
Example	Baking a cake	Sending a rocket to the moon	Raising a child	Preventing biodiversity loss
Nature of the problem	Consensus exists on problem definition and solution.	Problem can be scientifically approached and resolved.	Each situation is unique. Formulae have limited application.	No consensus on nature of problem or solution.
Predictability	Highly predictable: following standard operating procedures can achieve desired outcome.	There are known and/or predictable characteristics identified by sufficient testing.	The problem has a high degree of uncertainty. Predictions cannot be relied upon.	Problem is multi-causal, dynamic, fluid; activity hard to predict or control.
Expertise	Problem can be solved by small teams or individuals with little conflict.	Success possible by highly skilled teams from a variety of fields.	Insight and experience across fields is required, although will not necessarily ensure success.	Requires cross-system working but high potential for conflict due to multiple perspectives and actors.
Approach	Expertise creates the solution which can be implemented with training.	Although challenging, repetition increases chances of implementing solution.	Highly dynamic problem, resistant to predetermined solutions which need to be contextualised.	Highly contextualised solutions required at multiple levels.

Application: Do I have a complexity problem?

We have created a tool based on the original Cake Rocket Child table to help you think about how these four categories of problems apply to your issue and what kind of approaches might be appropriate.

We have added a row to help you think about not just the overall problem, but also different sub-problems or tasks within that overall issue. Where do they sit along this simple-wicked scale?

Although a problem may fall into the highly complex or wicked category overall, there will likely be problems within it that have different characteristics and require a different approach.

Becoming complexity literate involves being able to shift modes according to the nature of the problem or situation faced. We have used the example of Covid-19 to illustrate how the tool works.

Even though the issue as a whole was highly complex, different aspects of it fell into different categories– as shown in the table. (Download a blank template on the homepage or below.)

Issue: Covid-19

	Simple	Complicated	Complex	Wicked (highly complex)
Problem/task	Administering a vaccine to an individual	Developing a vaccine	Vaccinating a population	Preventing the next pandemic
Nature of the problem	Standard operating procedure (SOPs) applies	Problem can be approached using accepted scientific processes	Unpredictable and uncertain situation, solutions must be contextualised	Problem is multi-causal, dynamic, fluid: effects of activity hard to predict or control
Predictability	Predictable: follow SOPs	Known unknowns: uncertainty in methodology but sufficient testing and investment ensured result	Unpredictable – e.g., resistance from different population groups; specific supply chain challenges hard to predict	High degree of uncertainty and unpredictability in how/ where pandemics may emerge
Expertise	Experts created SOPs that can be followed by those without expertise	Success made possible by high level of technical expertise in skilled teams	Applied insight required across multiple fields- technical and social- in response to emerging situations	Technical expertise crucial but not sufficient; relational / diplomatic skills needed to establish trust, understand agendas and build shared approach
Approach	Create operating instructions, train administrators, implement vaccine	Test, trial, monitor, review, iterate. Repeat until solution found	Test rollout approaches / messaging and adapt to responses of target groups Use live data to ensure feedback loop and inform decision making	Continual sensing across multiple social, political and medical spheres Continually engage with diverse global stakeholders Establish trusting relationships of shared interest