A flexible framework for stakeholder engagement

Community member post by Michelle Banfield

Michelle Banfield (biography)

How can stakeholder engagement in research be effectively planned? What parameters need to be taken into account? How can flexibility be built in to accommodate different levels of researcher and stakeholder experience?

The framework presented here was developed for health services research, but is more broadly applicable. The framework has three separate dimensions.

  1. The stakeholders to involve
  2. The stages of the research at which they will be involved
  3. The level of involvement for each stakeholder group at each stage.

When combined, these dimensions form an easy to use matrix to plan the involvement of stakeholders at the initiation of the project. The model is designed to break planning into manageable pieces. This encourages thinking “outside the box” in terms of design and methods, giving stakeholders the opportunity to decide how they would like to contribute and reducing the chances of imposing the researchers’ plans upon them.

The stakeholder engagement matrix

The relevant stakeholders will vary from project to project and it is helpful to consider everyone who has something useful to contribute to understanding or acting on the problem. There are also multiple ways of describing the stages of research, with the five stages shown in the figure below providing a straight-forward characterisation that is broadly applicable.

As the figure below demonstrates, when the first two dimensions (stakeholders and research stages) are combined, they form a blank matrix into which research planners can insert level of involvement ‘markers’ to complete the plan of involvement in their project.

(Source: Banfield, Yen and Newby 2011)

The level of engagement shown in the figure below is based on Arnstein’s ladder (1969), a description of which can be found in Katrin Prager’s blog post comparing participation and co-creation.

(Source: Banfield, Yen and Newby 2011)

The “best” involvement is that which is appropriate to the project as well as to the skills and experience with collaborative research of all stakeholders including the researchers. This is not always at the highest end of the scale.

A completed matrix may then look something like the figure below (based on a fictitious example), where:

  • there is joint planning among all stakeholder groups when deciding what to research
  • researchers have greater responsibility for deciding on methods and carrying out the project, with some consultation and advice from stakeholders
  • consumers and practitioners have more responsibility when the research findings are disseminated
  • completing the cycle (and beginning a new cycle) with decisions on the next steps such as implementation plans and further research is again a joint planning process.

(Source: Banfield, Yen and Newby 2011)

A key feature of the proposed framework is flexibility. Researchers are not constrained by applying one level of involvement to their entire project or to all the involved stakeholders. Further, the plan should not be considered as fixed, but rather to be modifiable throughout the course of the research if necessary. For example, if consumers showed particular interest in data collection and capacity existed to train them, it would be possible to update the above plan to reflect delegated responsibility for consumers in carrying out the research.

Final thoughts

Engagement needs to be appropriate – don’t set people up to fail, so consider:

  • Skills of the people offering the engagement opportunity
  • Skills of the people being engaged
  • Build in plenty of time and resources for engagement – it should be central to program and research design, not an afterthought
  • Ensure people involved in your work are not out-of-pocket (reimburse costs)
  • Shared expectations are crucial to a good experiences for all parties
  • Document your own assumptions about engagement, what you want from the process, boundaries of things that cannot be altered and areas of flexibility
  • Document the same for the people being engaged
  • Invest time discussing documented positions to reach a shared understanding
  • Be prepared to negotiate and ensure you are in a position to use the feedback provided: it is tokenistic to consult stakeholders, especially people with lived experience, if you are unwilling or unable to use their recommendations.

Finally, the proposed framework is designed to encourage researchers to think about their own capabilities in managing the involvement process and to design a project that maximises the opportunity of all to succeed. Many researchers strongly support stakeholder involvement in research but feel they do not have sufficient experience and skills to undertake higher level involvement such as employing a consumer researcher. The proposed framework allows these researchers to start with involvement in specific parts of their research and build on their successes in a continual cycle of improvement and extension.

What do you think? Would you find such a framework useful? Does it cover everything that you think is important? Are there other frameworks that you use?

To find out more:
Banfield, M., Yen, L. and Newby, L. (2011). Stakeholder involvement in primary health care research: Report and recommendations. Australian Primary Health Care Research Institute: Canberra, Australia. Online (downloadable): http://rsph.anu.edu.au/files/Stakeholder%20involvement%2025%20page%20final.pdf (PDF 612KB)

Arnstein, S. R. (1969). A ladder of citizen participation. Journal of the American Institute of Planners, 35, 4: 216-224.

Biography: Michelle Banfield PhD is Head of Lived Experience Research at the Centre for Mental Health Research, Research School of Population Health, The Australian National University in Canberra, Australia. She leads a program of work that takes a health systems approach to evidence for effective mental health service provision. As a researcher with lived experience of mental illness, her research has a strong engagement and translational focus. She conducts research in collaboration with other consumers, carers and stakeholders to develop and implement effective mental health services and policy reform.

Michelle Banfield is a member of PopHealthXchange, Research School of Population Health at The Australian National University.

Four strategies for improving knowledge exchange among scientists and decision-makers

Community member post by Chris Cvitanovic

Chris Cvitanovic (biography)

How can we improve knowledge exchange among scientists and decision-makers to facilitate evidence informed decision-making? Of course there is no one size fits all approach, but here I outline four strategies that could be adapted and implemented across different contexts: (i) knowledge co-production, (ii) embedding, (iii) knowledge brokers, and (iv) boundary organisations. These are illustrated in the figure below.

Knowledge co-production

Perhaps the most widely advocated approach to achieving improved knowledge exchange, knowledge co-production refers to the process whereby decision-makers actively participate in scientific research programs from the onset, collaborating with researchers throughout every aspect of the study including design, implementation and analysis. Including decision-makers in research programs in this manner ensures that decision-makers develop a strong understanding of the research content, as well as developing a strong sense of ownership in the research, which they can then communicate more broadly within their organisation, raising the awareness of others.

Conceptual diagram outlining the four primary models believed to increase knowledge exchange among scientists and decision-makers (Cvitanovic et al., 2015)


Improving knowledge exchange among scientists and decision-makers can also be achieved by embedding scientists in decision-making agencies. Permanently embedding research scientists within organisations dominated by decisions-makers will improve the likelihood that priority knowledge gaps will be answered, with the information quickly spreading among decision-makers via social networks. In turn this will increase the likelihood that new scientific knowledge is integrated into decision-making processes.

Knowledge brokers

Another approach to improving collaboration and knowledge exchange among scientists and decision-makers is through the use of knowledge brokers. While the exact role and function of knowledge brokers are conceptualized and operationalised differently in various sectors and settings, the key feature of such a role is to facilitate the exchange of knowledge between and among various stakeholders, including researchers, practitioners, and policy makers. To achieve this, knowledge brokers are typically embedded within research teams or institutions and act as intermediaries who develop relationships and networks with, among, and between producers and users of knowledge, to facilitate the exchange of knowledge among this network. When implemented effectively, knowledge brokers are believed to have the ability to facilitate organisational change by removing barriers to evidence-based decision-making and promoting a culture that values the use of the best available science in policy and practice.

Boundary organisations

Boundary organisations have also been identified as a novel approach to improve knowledge exchange among producers and users of scientific knowledge. Like knowledge brokers, boundary organisations facilitate communication and knowledge exchange among diverse networks of stakeholders. However, unlike knowledge brokers, boundary organisations are not typically embedded within research teams or organisations but are established as a separate entity, thus more effectively representing both sides across the boundary (ie., science and decision-making) while maintaining credibility through independence. In this way, boundary organisations are to be able to unite groups that may otherwise have strained relationships (for example, based on the cultural differences between scientists and decision-makers as outlined above) to enhance evidence-based decision-making. Boundary organisations have already proven particularly effective when dealing with a specific issue in a specific location.


While all four options described above are designed to improve knowledge exchange among scientists and decision-makers, there is much that we still don’t know, including the traits that influence the effectiveness and efficiency of each option, as well as how best to monitor and evaluate each option’s effectiveness. Irrespective, the increased awareness and implementation of these approaches to date provides an optimistic outlook for improved knowledge exchange among scientists and decision-makers, leading to improved capacity for evidence-based decision-making in the face of complex and uncertain futures.

What has your experience been with any of these strategies? And how have you adapted them to successfully fit within your specific circumstance or context?

This is based on a longer blog post also titled ‘Four strategies for improving knowledge exchange among scientists and decision-makers‘, published in Research to Action on 18 November 2015; http://www.researchtoaction.org/2015/11/four-strategies-for-improving-knowledge-exchange-among-scientists-and-decision-makers/

To find out more:
Cvitanovic, C., Hobday, A. J., van Kerkhoff, L., Wilson, S. K., Dobbs, K. and Marshall, N. A. (2015). Improving knowledge exchange among scientists and decision-makers to facilitate the adaptive governance of marine resources: A review of knowledge and research needs. Ocean and Coastal Management, 112: 25-35. Online (open access): https://www.sciencedirect.com/science/article/pii/S0964569115001167

Biography: Chris Cvitanovic (@ChrisCvitanovic) is a research scientist and knowledge broker at CSIRO in Hobart, Australia, specialising in knowledge exchange, stakeholder engagement, and the governance of marine resources. He draws on almost ten years of experience working at the interface of science and policy for the Australian Government Department of Environment.

Conditions for co-creation

Community member post by Gabriele Bammer

This is part of a series of occasional “synthesis blog posts” drawing together insights across blog posts on related topics.

Gabriele Bammer (biography)

What is required for effective co-creation, especially between researchers and stakeholders? In particular, what contributes to a productive environment for co-creation? And what considerations are relevant for deciding who to involve?

Twelve blog posts which have addressed these issues are discussed. Bringing those insights together provides a richer picture of how to achieve effective co-creation.

What makes a productive environment for co-creation?

A good starting point is to be working in an environment and organizational culture that support co-creation and to have sufficient financial, personnel and other resources, as pointed out by Kit Macleod and Arnim Wiek.

Dialogue-based processes are often an important part of co-creation and they need to be established as a generative space, focused on synergy, not conflict. Continue reading

Language matters in transdisciplinarity

Community member post by Tilo Weber

Tilo Weber (biography)

Why should transdisciplinarians, in particular, care about multilingualism and what can be done to embrace it?

From a linguist’s point of view, I suggest that, in a globalized world, a one language policy is not only problematic from the point of view of fair power relations and equal participation opportunities, but it also weakens science as a whole by excluding ideas, perspectives, and arguments from being voiced and heard.

When people communicate, more is at stake than mere exchange of information, coordination of activities, and joint problem solving. Continue reading

Twelve ways to kill research translation

Community member post by Lewis Atkinson

Lewis Atkinson (biography)

Want to reduce the likelihood that your research will produce policy and practice change? Here are 12 anti-rules to prevent research translation.

Anti-rule #1: ONLY FOCUS ON YOUR PART OF THE PROBLEM. Avoid seeing the problem as a whole to limit the intervention possibilities. Acknowledge the translational “gap” but be ambivalent about who owns it. Contest it with others and perpetuate confusion with a range of definitions for what research translation means.

Anti-rule #2: CLOSE OFF THE FLOW OF INFORMATION AND KNOWLEDGE. Keep a tight lid on who is involved and what knowledge is seen to be relevant. Do not share your data or allow access to your sources of data. Minimise the rate of data exchange within and among various research and non-research partners. Continue reading

You are biased!

Community member post by Matthew Welsh

Matthew Welsh (biography)

Complex, real-world problems require cooperation or agreement amongst people of diverse backgrounds and, often, opinions. Our ability to trust in the goodwill of other stakeholders, however, is being eroded by constant accusations of ‘bias’. These are made by commentators about scientists, politicians about media outlets and people of differing political viewpoints about one another. Against this cacophony of accusation, it is worthwhile stepping back and asking “what do we mean when we say ‘bias’ and what does it say about us and about others?”. Continue reading