Designing complex systems requires methods that can handle many actors, long time horizons and interwoven dependencies. In this context, it is not enough to develop a single service or product. Tools are needed that make it possible to prototype relationships, roles, incentives, processes, policies and market logics. System-adapted sprints are a way of using design methodology at the system level to create testable models of how a system could work in the future.
Design, traditionally, has often been used to create something concrete and close to the user. But when design is scaled up to the system level, it becomes a way of thinking. Instead of asking what a service should look like, we ask how the building blocks of the system can change to enable a new behavior and a new reality. This makes the design methodology a strong catalyst for system innovation.
What are system-adapted sprints
System-adapted sprints are time-bound processes that take inspiration from the sprint format of service design but start from the levels of the system instead of the needs of an individual user. The aim is to get actors to explore future possibilities together, test how central parts of the system can function and make visible which dependencies require change.
A system-adapted sprint does not work with a prototype in the traditional sense. The prototype can instead be a simulated policy, a fictional future role, a model for a market function or a prototype of a collaboration agreement. The point is to create something that actors can react to in order to reveal what requires transformation in the system.
It is therefore about building a test system in miniature, not to scale it up directly but to learn what really needs to change.
Why system-adapted sprints are important in system innovation
System innovation differs from other innovation in that the change must take place in relationships, even when each actor is motivated to solve their own part. A transport system does not change just because a new type of vehicle is launched. It changes when infrastructure, rules, business models, behaviours and data flows change together.
There are several reasons why system-adapted sprints work in these contexts. They allow complex issues to be broken down without losing the whole. They create shared concrete learning that is otherwise difficult to obtain when only discussing problems at an abstract level. They make it possible to test system changes on a small scale before trying to implement them on a large scale. And they give actors a safe place to try something new without directly affecting their regular organization.
The role of design labs in system innovation
There are three established design-oriented approaches used in system innovation and which form the basis for how system-adapted sprints can be implemented. These are strategic design, transition design and policy labs. Together they form a framework for how design can be used as an engine in system change.
Strategic design
Strategic design uses design principles to shape structures such as policy, organizations, markets and control systems. Instead of starting from a specific service, strategic design takes a step up and asks how the framework conditions need to be designed to make a transformation possible. In a system-adapted sprint, this means modeling and testing new system logics. For example, you can create a prototype for how a new market for recycling will work and let actors try out different roles to see what incentives are needed.
Transition design
Transition design focuses on long-term sustainability transitions and is based on future visions and system mapping. This approach complements sprints by anchoring them in a movement towards a future desirable system level. In system-adapted sprints, transition design is used to ensure that the focus of the sprint is not stuck in short-term solutions but is linked to a transformation that takes place over decades. The sprint then becomes a practical step in a longer transition.
Policy labs
Policy labs are environments where actors can experiment with policies in a controlled way. By testing policy hypotheses on a small scale, consequences and unexpected effects can be quickly seen. In a system-adapted sprint, policy labs can create prototypes of regulations or government processes that participants act in. This makes it possible to see how policies would work in practice and which obstacles need to be removed.
How to use system-adapted sprints as a system innovation leader
- Create a shared system map
The work begins by mapping the system’s actors, relationships, drivers and obstacles. This is the basis for understanding where a sprint should be focused. The system innovation leader helps the actors see the big picture and define a common challenge. - Formulate a future system logic
The leader guides the actors towards a shared future vision that describes how the system should function if the problem is solved. This becomes the direction that the sprint will test parts of. The future vision needs to be concrete enough to be translated into prototypes. - Define the level of the prototype
Determine what is to be prototyped. It could be a policy, an incentive, a structure, an actor role or a new market model. The important thing is that the prototype is something that affects the relationships in the system. - Conduct the sprint in cross-functional groups
Actors from different parts of the system work together and test prototypes in a simulated reality. The system innovation leader facilitates, captures learning and helps the groups navigate between details and the whole. - Test the future in miniature
The core of the sprint consists of participants testing the system as if the future were already a reality. They move through scenarios, interact with prototyped policies or roles and discover where friction arises. It is in these frictions that the potential for system innovation lies. - Collect learning and translate into the next step
After the sprint, the insights are documented. The system innovation leader translates them into change hypotheses, prioritized efforts or new prototypes. The learning is lifted back to the organizations and to the policy level where changes can be decided.
Example of a system-adapted sprint
Think of a regional food system that is to become more circular and climate-neutral. A system-adapted sprint could then include a prototype for a future marketplace for residual flows, a simulated policy that rewards short transport chains and a role distribution that distributes responsibility between municipalities, producers and logistics actors. By playing through a future scenario, participants can identify which collaborative processes are needed and what is missing in today’s system.
System innovation requires new tools
System-adapted sprints create a place where the system can be tested before it changes. They make it possible to learn quickly, gather actors around a common picture and build concrete bridges between vision and reality. This is one of the most powerful methods for a system innovation leader who wants to drive real transformation.
