The ripples of impact: how innovation labs create system change

Innovation labs are increasingly used to tackle complex challenges in health and care. 

They are programmes which create spaces for creative thinking on improving solutions and services. They can use a variety of methods and tools, often led by ​‘design thinking’. As in the case of Q Lab, there’s often a process of research, experiment, test and refine – alongside working with a human-centre approach. New services and solutions in innovation labs focus on responding to people’s needs. 
 
Given their variety of forms and functions, robust evidence of whether and how labs lead to lasting change remains limited. This is something we explored in our evidence review of labs. 

At Q, we set out to understand how an innovation lab can support system change. Do the solutions and improvements that are developed, support new models and mods of care delivery? Alongside the individual projects, are they building individual and organisational capability, relationships and confidence over time? 

When labs are judged solely on the number of successes of individual projects they have supported, it misses some of the broader, systemic impacts they can achieve. Taking into account how they shape people, organisations and relationships, we see labs as powerful engines of system change, alongside the possibilities of the individual projects. 

The independent and in-house evaluations of Q Lab across multiple cohorts, including follow-up with teams several years later, show a clear pattern. Q Lab consistently generates ripples of impact: building people’s confidence, changing ways of working, and strengthening the collective capacity of the health and care system to improve over time. 

We’re very proud that many Q Lab projects have redesigned services, influenced policy, improved patient care, and shaped national conversations. 

For example, Stockport NHS Foundation Trust aimed to reduce the waiting times for patients living with complex pain management needs to access elective surgery, and had significant impacts, as shown below. 

Yet, some projects stalled or changed direction. This variation reflects the reality of innovation in complex systems. One of the most important implications of this experience may also be the most uncomfortable: if every Lab project succeeds, the Lab is probably not ambitious enough. 

Innovation in complex systems carries risk, so some ideas need to stop. Others should pivot. The evaluation of the Q Lab shows that, even where projects did not go on to widespread implementation, the learning generated and the skills developed continued to create value. 

Teams repeatedly described how Lab participation surfaced structural barriers, shifted their understanding of the problem, and redirected effort toward more meaningful solutions. 

For some people this led to a change in product and project that was more useful than their original idea. The lived experience inputs into workshops in some cases led to changes in perceptions of the problem, and therefore the kind of services needed. 

From an evaluation perspective, this is a legitimate and valuable outcome, even where final implementation was partial or delayed. In complex environments, stopping or pivoting can be as important as delivery. 

While teams work on real, live challenges, the Lab deliberately invests in how people work together: revealing assumptions, reframing problems, drawing in lived experience, testing ideas, and learning from failure. 

Across cohorts, Q Lab had its strongest and most consistent impact at the individual level. 

Using Q’s Skills for Collaborative Change framework, around 80–90% of participants reported significant increases in their capabilities. 

This growth was particularly seen in working collaboratively, tolerating uncertainty, and engaging people with lived experience. 

These gains were actively cultivated through the Lab’s design through the coaching, peer learning, structured reflection and experimentation support. 

Impact also varied depending on participants’ starting points. For more experienced participants, the Lab helped consolidate and sharpen their existing practice, legitimising ways of working they already valued, but struggled to sustain day to day. 

For others, it built foundational skills and offered permission to work differently. 

Individual capabilities matter because it leads to changing behaviour. After the Lab, participants described themselves approaching problems differently feeling better equipped to lead change in uncertain, pressured environments. 

One of the most consistent findings across evaluations was that Lab participants carried new approaches back into their organisations, influencing future projects and ways of working. 

Teams consistently reported being more deliberate about problem framing, involving people with lived experience earlier and more meaningfully, testing ideas rather than over-designing solutions, and especially, increased confidence to challenge assumptions and ​“the way things are done”. 

Labs were vehicles for cultural change. 

In some cases, these changes were experienced as genuinely transformative: 

In some organisations, participation helped shift attitudes toward improvement more broadly: 

This organisational ripple is a critical, but often overlooked, form of impact. Although it may not show in standard metrics, it fundamentally shapes the conditions for future change. 

These effects help explain why Labs can feel disproportionately influential relative to their size.  Over time they build the organisational capability for change. 

Evaluating innovation labs presents some challenges. Innovation labs usually operate at early stages of idea generation, in complex systems shaped by workforce pressure, funding constraints and shifting policy priorities. Not every project or idea generated through a lab will be implemented or scaled. This is why Q Lab runs in two stages, the first nine months for discovery and experimentation, and then a follow up year for implementation of some of those projects – which we’ve done for the last three labs. 
 
By taking an experiment, test and learn approach, most labs are setup for and comfortable with some level of ​‘failure’ – by which we mean the kind of learning from ​‘failing well’ which Amy Edmondson and others speak about. 

Impacts from labs are often delayed, indirect and distributed across people and organisations. Without taking a longer view, important impact can remain invisible, and innovation labs risk being undervalued or misunderstood. 

Recognising this, our 2024 evaluation was designed from the outset to answer the question: how do labs create value over time, and at what levels? 

We combined: 

• a clear ​‘theory of change’ to say what we expected to happen 
• evaluating the lab during delivery so we could adapt, as well as at the end to review 
• a retrospective follow-up. This included the subsequent independent evaluation led by Picker, and tracking what changes had sustained or spread years later. 

This approach allowed us to distinguish between the impact of individual Lab projects, and the impact of the Lab model itself, particularly its effects on people and organisations. 

What we’ve learned is both reassuring and important: some of the success of innovation labs shows up beyond simple, linear changes that are easy to evaluate. They reliably build momentum for change across people, organisations and systems. 

What was really positive was how our evaluation revealed that individual-level outcomes ripple outward. They shape organisational culture, influence service design and, in some cases, contribute to system-level shifts. 

We saw that, over time, individual and organisational impact interacted: greater confidence enabled people to collaborate differently; organisational shifts created space for continued innovation; and relationships sustained the change beyond the end of the Lab. 

Although system level change was harder to evidence and slowest to emerge, when it did, it happened cumulatively. Labs led to relationships that endured, shared language for change, and a growing critical mass of people fluent in collaborative ways of working. As one participant put it: 

Q Lab’s experience demonstrates the additional benefits you can get from innovation labs. 

The ripple effect of the Lab mirrors how change can happen in health and care: gradually, unevenly, and through people.