Through our work in the Innovation Skills team, we often find ourselves being asked by governments and civil servants which innovation tools and techniques they should use. So what innovation approaches are there that can be applied in the public sector? And how are they related to each other?

With these questions in mind, over the last couple of years we’ve been mapping out the various innovation methods and approaches we’ve come across from studying innovation practice and our many conversations with different lab practitioners, colleagues and other innovation experts.

Download this diagram as a PDF.

The map we’ve created provides an overview of innovation methods and approaches that help people make sense of reality, and approaches that help develop solutions and interventions to create change.

Understanding and shaping reality

The approaches mapped out in the diagram are structured into four spaces: intelligence, solution, technology and talent. These spaces are built on the premise that in order to create change, you need to make sense and understand reality, as well as develop solutions and interventions to change that reality:

• intelligence space – focuses on approaches that help you make sense of and conceptualise reality
• solution space – focuses on methods that help you test and develop solutions

In terms of mindsets, you could say that the intelligence space is more academic, whereas the solution space involves more of an entrepreneurial approach. The activities in these are supported by two further spaces:

• technology space - includes approaches and technology that enable action and change, such as digital tools and data-related methods
• talent space - focuses on how to mobilise talent, develop skills and increase organisational readiness in order to ultimately make change happen

Challenging personal preferences and biases

In innovation labs, we often see that practitioners use more than one tool or method, and that they have a diverse set of skills to ‘get the job done’. For example, Nesta’s report on Innovation Teams shows that, in practice, design thinking is often used in conjunction with other methods such as open data, ethnographic research, challenge prizes or behavioural insights. Hence, in the diagram design thinking is positioned at the intersection of the intelligence and solution space.

We have also noticed that people often have a personal bias when considering innovation methods. For example, designers are generally strong advocates of design related methods such as design thinking or human centred design. When academics are involved in an innovation process, they can show a preference for more analytical methods. But it’s important to challenge these biases and look beyond our own disciplines at other methods. Hopefully this diagram will help you to identify your own biases and make better informed decisions when planning your innovation journey.

Work in progress

To date, this map has been a work in progress that we’ve regularly updated and occasionally shared, and we’d now like to share it with a wider audience. Our hope is that it will help people to get a sense of the range of innovation approaches available, making them easier for newcomers to navigate. We also think the diagram is helpful for supporting conversations around setting up a team or lab, or when considering the content of a learning programme.

From experience, we find it also useful to share this map with managers and executives who are asking “what is different”, or who want to get a better grasp of the learning gaps in their organisation - a quick and dirty self-assessment tool of sorts.

Although this map is neither exhaustive nor definitive – and at some points it may seem perhaps a little arbitrary, personal choice and preference – we have tried to provide an overview of both commonly used and emerging innovation approaches.

Some of these methods have been widely adopted, while others are more exotic and only serving a niche, but may eventually become more mainstream. Additionally, some are well codified through guides, toolkits and learning programmes, while others are still considered “dark arts” that are not yet fully understood and only used by a small group of early adopters.

Have comments or suggestions on how to improve the map? Please let us know.