Rethinking professional roles in the knowledge economy

Ingo Peters (Canada) and Charles Dweha (Zimbabwe) sharing knowledge via Google Earth

In late April I participated in an international conference called K* 2012 convened by Dr Alex Bielak of the United Nations University Institute for Water, Environment and Health (INWEH) in Hamilton, Ontario, Canada. K* or Kstar is a convenient short-hand umbrella term for a broad spectrum of knowledge roles. More on that later. The objective of the conference was to “bring together knowledge intermediaries working across the knowledge-policy interface all over the globe, to share experience, lessons learned and build a global community of knowledge practitioners.”

The conference richly delivered on its objectives and its promise. Alex Bielak and his conference co-chair Louise Shaxson (of the British Overseas Development Institute ODI) did a great job assembling an eclectic assortment of knowledge practitioners from multiple sectors across many countries, some of them very experienced and others relatively early in their careers, all with interesting perspectives and stories to tell. For the participants lucky enough to be invited it was a unique and memorable event — no other forum, organisation or event could have brought together this group of people.

Alex, Louise and the organising committee also deserve credit for designing a highly participatory conference format that, coupled with a Powerpoint ban, short (<10 minute) presentations in interactive panels and skilful facilitation, offered maximum opportunity for the diverse talents of participants to express themselves, and for people to learn from others and generate new insights through dialogue.

Participation was extended beyond those physically present through web-casting and social media, with more than 100 people from 40 countries joining in online during the course of the conference. Many conferences claim to promote online participation, but very few deliver in an interactive sense. This was the best use of the technology I’ve yet seen. You need to experience this in real time to fully appreciate the degree of interaction, but a flavour of the contributions can be found here.

Now to the subject of the conference itself. Firstly, I was struck by the interplay between two countervailing principles: the crucial importance of understanding context before designing or implementing a knowledge intermediary process; notwithstanding the extraordinary cross-overs between sectors, experiencing similar issues and benefiting from similar approaches in very different contexts. The diversity of people from different backgrounds playing different roles in the knowledge systems of different sectors in different countries could easily have led to confusion and people talking at cross-purposes. But in general it made for rich learning at an individual and collective level.

Which brings me to terminology. Faced with a plethora of terms including knowledge brokering, knowledge mobilisation, knowledge translation, science communication, extension and knowledge management, with a significant degree of overlap between them, Alex Bielak coined the term K* as a short-hand umbrella term for this broad suite of knowledge roles and processes that are used across the spectrum from science to policy and practice.

Andrew Campbell on a K* field trip to Niagara Falls

For the participants in the K*2012 conference (especially those who had been involved in planning it and/or had read the background documents, among whom there was a reasonable level of shared understanding), the K* moniker is a very convenient short-hand catch-all that we know covers a broad spectrum of roles within what keynote Professor John Lavis[1] calls a diverse ‘knowledge ecosystem’. For a general audience however, the term is opaque and does not convey any sense of what it means, so I’m less sure of its enduring value.

I’m more comfortable staying within the domain of Knowledge Management than trying to establish a new label. That said, we need to ensure that the boundaries of KM encompass the broad spectrum from scientific discovery through co-learning in all its rich complexity, weaving together scientific, local, tacit, experiential and other forms of knowledge through various types of inquiry, including (but not only) positivist scientific research. This is consistent with the breadth and interactive, contextual depth that thought leaders within the Knowledge Management field like Dave Snowden (with whom we worked in LWA in the early 2000s) have been emphasising and illuminating for many years.

The six functions of knowledge brokering

The six functions of knowledge brokering - click to enlarge

Catherine Fisher from the Institute of Development Studies in the UK and a facilitator of the Knowledge Brokers’ Forum, drew on papers from Sarah Michaels (2009), and Louise Shaxson and Elin Gwyn (2010) to map some of the roles, functions and activities that were the focus of the K*2012 conference, as depicted in the diagram above. This diagram attempts to show different roles along a spectrum of knowledge processes, from conventional, linear dissemination of information (science communication) on the left hand side, through intermediary and brokering strategies in the middle, to co-production of knowledge and innovation on the right hand side.

This diagram hints at an important distinction observed by John Lavis. For some people or in some contexts, these knowledge intermediary processes begin where the research stops — they are essentially about getting better uptake of research results and amplifying research impact. In such contexts, scientific knowledge is privileged, and extending it to wider audiences is seen to be unambiguously a good thing.

In other contexts however, brokering processes between the producers and users of knowledge (who may overlap to a significant degree) are seen as an essential prerequisite before research is initiated, to refine research questions, influence methodologies, and ensure that intended end-users have a degree of ownership of research outputs. In such contexts, scientific inquiry may not be the only or even the most appropriate mode of knowledge production, and co-learning approaches are likely to be more effective.

Reflecting on the K*2012 event itself, there were many ‘Aha!’ moments or take home messages for me, including:

  • The crucial importance of context, and hence of diagnostic tools to assist in understanding the context (e.g. where you are on the spectrum in the diagram above, and the relative importance of scientific, tacit, experiential, local, Indigenous and organisational knowledge), and how and why it affects the choice of and likely effectiveness of knowledge strategies. For example, as we are seeing with the climate debate and other ‘wicked problems’, it is not sufficient to assume that scientific consensus about the facts will be influential in policy or the wider community.
  • The value of having a toolkit (here is a good example, see Appendices for an annotated menu) of approaches for different contexts, and the challenges this represents in terms of developing the tools and having the balance of skills needed to implement them (rarely to be found embodied in one person).
  • The importance of clarifying objectives and making them very explicit and transparent. For example, in Australia it is now increasingly common for research organisations (including my own) to employ knowledge brokers. But for many of these people, their core function is to promote the research outputs of their own institution — a conventional science communication role — with limited scope to influence research priorities or methodologies, or to promote science done elsewhere. In my view such roles should be more accurately labelled, and people should not be called brokers unless they have the capability and the mandate to negotiate in both directions.
  • That said, it is arguable for me whether an organisation can jump to sophisticated knowledge intermediary processes without being competent at the basics of science communication: the ability to pick up research highlights early and present them well; good web interface and search capabilities; effective media and events strategies; and the ability to synthesize research outputs in attractive ways targeted to the knowledge needs of intended audiences.
  • As a general rule, research organisations are more likely to employ people towards the left side of Figure 1, whereas it is easier for intermediary and boundary organisations to employ more ‘independent’ knowledge brokers that can work more effectively across multiple organisations and types of knowledge — challenging the science if necessary. There was considerable discussion at K*2012 about whether a knowledge intermediary can ever be truly independent. The general consensus was ‘no’, and that it is very important that knowledge professionals make their own objectives (what others see as their agenda) clear from the outset.
  • For me at least, all the strategies in the diagram above are equally valid depending on context. They tend to be complementary rather than alternative strategies, particularly for an organisation as a whole. While the more interactive and interpersonal activities on the right hand side of the diagram above may be more exciting for some people, it is important to get the basics right: the underlying data systems that make information discoverable, searchable and accessible, the integration and synthesis tools that can help pull information from diverse projects together to meet a given need, and the ‘big C’ science communication tools that make it easier for scientists to promote their outputs and for media, government, industry and the community to find and access intelligible information.
  • At the risk of labouring the point, it is difficult to sustain deep knowledge intermediary processes if the basic information and communication systems are lacking. From my experience in policy, management, consultancy, research management and now a university, many science organisations still struggle to get far beyond conventional scientific publications, media releases and websites, perhaps dipping a toe into social media. To be fair, the existing performance metrics, funding and reward systems for academic research act as a disincentive to go further along the track to get involved in very meaningful, interactive co-production of knowledge, especially if that might reduce the flow of publications in ‘high impact’ refereed journals.
  • It seems trite and redundant to say it, but new technologies offer extraordinary potential to share knowledge, to facilitate interaction and to accelerate social learning. They are far more than just cool gadgets, but enable new pedagogies and fundamentally different ways of tackling old problems. We need to be ready for revolution as ‘digital natives’ leave school and become the new wave of knowledge professionals.
  • Wearing my other hat as chair of the board of TERN (the Terrestrial Ecosystem Research Network in Australia), and focusing on the environmental sector, I’m equally conscious of what McKinsey & Co calls the era of ‘Big Data’ and The Economist refers to as the ‘data deluge’. We now generate (and hopefully are now able to manage) vast amounts of information in ways that were hitherto inconceivable. A recurring theme at K*2012 was that a key role for K* professionals is to help people to negotiate ‘infoglut’, to find sense in a world of information bombardment, overload and a cacophony of competing knowledge claims. Yes we need K* professionals with finely tuned interpersonal skills to perform brokering roles. But equally, we also need K* professionals with sophisticated informatics skills to design search and retrieval systems and intuitive user interfaces to improve system-wide learning.

K*2012 conference co-chairs Dr Alex Bielak (UNU INWEH) and Louise Shaxson (ODI UK)

My final lesson reinforced an already strongly held view. Evaluating the impact or value added by skilled knowledge intermediary processes remains our biggest challenge. At Land & Water Australia we placed a high priority on evaluation, but even with a strong mandate and a systematic approach it is difficult to measure science impact in a robust, consistent and timely way. It makes intuitive sense that a better KM process will accelerate and improve salience, credibility, legitimacy, uptake and application and hence impact. But it is very difficult to set up an experiment or some other means of quantifying that value add. What difference did our KM process make to the overall outcome? Attribution is hard, and it is difficult to explore the null hypothesis – i.e. what would have happened in the absence of the intervention? Often this means qualitative assessments, case studies, anecdotal and narrative techniques.

As Professor David Pannell and colleagues note in a comprehensive review of the vast extension literature, too often the fundamental characteristics of the scientific ‘innovation’ or knowledge product are such that lack of uptake by intended beneficiaries is a reasonable and rational response. In such contexts, conventional science communication is probably a waste of money, and a genuine knowledge brokering process would deliver uncomfortable messages back to researchers. That could be seen as a negative by the research institution, but from an overall system perspective might be a very good investment indeed, if it leads to more relevant and useful research.

Irrespective of methodological challenges, it is crucial to establish the value of these processes, so it is not good enough to leave evaluation in the ‘too hard’ basket.

In universities and other science and research institutions we are in the knowledge business. This business involves many roles for professional intermediaries across different sectors. The K*2012 conference in Ontario provided rich insights into the value to be gained through bringing practitioners together, sharing experiences and developing a global community of practice. I look forward to tracing the impact of this catalytic event.

References cited

Bennet, Alex and David Bennet (2007) Knowledge Mobilization in the Social Sciences and Humanities: Moving from Research to Action Mountain Quest Institute In cooperation with the Social Sciences and Humanities Research Council of Canada. MQI Press, Marlinton WV. http://www.mountainquestinstitute.com/knowledge_mobilization.htm

Campbell, Andrew (2007) The Getting of Knowledge: a guide to funding and managing applied research Land & Water Australia, Canberra. http://lwa.gov.au/products/pk071243

The Economist (2010) “Data, data everywhere” The Economist special report 25 February 2010. http://www.economist.com/node/15557443

Manyika, James, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh and Angela Hung Byers (2011) Big data: The next frontier for innovation, competition, and productivity. McKinsey & Company. http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation

Michaels, Sarah (2009) “Matching Knowledge Brokering strategies to environmental policy problems and settings” Environmental Science and Policy 12:994-1011

Pannell, David, Graham Marshall, Neil Barr, Allan Curtis, Frank Vanclay, and Roger Wilkinson (2006). Understanding and promoting adoption of conservation practices by rural landholders. Australian Journal of Experimental Agriculture 46(11):1407-1424. http://dpannell.fnas.uwa.edu.au/dp0502.htm

Schofield, Nick, Peter Chudleigh and Sarah Simpson (2007) Land & Water Australia’s Portfolio Return on Investment & Evaluation Case Studies 3rd Edition Land & Water Australia, Canberra. http://lwa.gov.au/products/ec071442

Shaxson, Louise and Elin Gwyn (2010) “Developing a strategy for knowledge translation and brokering in public policymaking” paper from Knowledge Translation and Brokering workshop, Montreal, Canada, 20 October 2010


[1] Incidentally, Prof John Lavis of McMaster University in Toronto must be the only person in the world who is a professor of both Clinical Epidemiology and Political Science.

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