Agricultural innovation (AI) coaching

Introduction
KIT & AI-coaching
Success factors
Challenges
Projects

Introduction
While a lot of research has been and will be kept being done on innovation processes, KIT is also rethinking innovation processes in developing countries and is –like others- even more so, trying to find answers to the question on how to facilitate such processes. KIT always aims at bringing research and reality closer together. In this regard, KIT will thus look into how agricultural innovation processes can be set into actual motion. Laurens Klerkx et al write about innovation brokers - as sketched out in the in-depth section - as possible solutions to strengthening agricultural innovation capacity. Their findings are mainly based on research in the Netherlands. In line with research on brokers in the European agricultural context, KIT is exploring ways of stimulating and supporting agricultural innovation and wonders whether Agricultural Innovation Coaches could be starting and supporting innovation processes in a developing or transitional environment.

KIT & AI-coaching
Innovation ‘brokering’ has been identified and is functioning in a recognized and legitimized way in Europe. In the Netherlands, for example, the privatization of extension services has led to the emergence of a variety of innovation brokering forms. In developing countries, we often see entrepreneurs playing this role. Others are private consultants, researchers, and individuals working in national extension services. At the Royal Tropical Institute in Amsterdam, we refer to people playing this role as agricultural innovation coaches – AI-Coaches, for short.

Coaching, brokering, what is in a name? What is the difference? Where are the similarities? These and many other questions were raised during a workshop hosted by KIT in December 2008 (for the workshop report: click on the second item under the picture on the right). Eight de facto AI-Coaches were invited to join us in Amsterdam for a week to think through a capacity development programme – what capacities are required? Who is best situated to play this kind of a role? What conditions are required to make it possible? These were amongst the guiding questions. In addition to the 8 de facto AI-coaches, we also invited two staff from each of two Africa-based organizations working on similar themes – IIRR (Kenya) and IFDC (Mali) (Rhiannon Pyburn, 2010). After the December 2008 workshop, we have been continuing our AI-coaching efforts for the last 2 years. Presentations have been held, partnerships created, contributions to training have been given and papers, concept notes and a planned publication are in the pipeline. Find below some of the success factors and challenges met so far during our working process.

Success factors
What we have found is that several factors are quite essential for success in playing a brokering role:

• A good understanding of innovation systems theory and the differences between institutional, technical and organizational innovation
• Strong MSP facilitation skills
• Credibility and recognition as leaders/negotiators/knowledge holders in the sector
• Resources, most importantly TIME to dedicate to coaxing the actors towards concerted action
• Organizational support to do this largely ‘invisible’ work

Challenges
By far the greatest challenge in establishing innovation brokers ‘on the ground’ is the lack of basic understanding of Innovation Systems thinking, also among those with many years of exposure to the subject. This field is largely couched in scientific language, using abstract terms that assume a thorough grasp of sometimes very abstract notions. This lack of communicability is a major constraint. It simply should not take an MSc program or more to get professionals acquainted and operational within the terminology.

The second challenge lies with those who understand the concepts but are then faced with the functionality (or lack thereof) of innovation systems thinking. We tempt to agree with Andy Hall who says that Innovations Systems thinking is a good diagnostic tool, but is limited. What do we do once the diagnosis is done and it is time to act? AIS is manageable when used in a way to understand actors and their relationships, but the jump to how that understanding can be used to generate change, is a big one. It needs to be made practical and understandable to get used.

Language is a third challenge. “Networks” suggest loosely connected, changing, dynamic webs. By contrast, platforms or groups – other terms used interchangeably - conjure up a much longer lasting, static, membership-basis constructions. Language is important. We need to give enough foundation and clarity to allow practitioners to use this stuff! Institutional innovation is a particular challenge and case in point. Technological innovation is relatively straightforward to understand – a farmer starts to use a new variety of sorghum or a new way of harvesting. Easy enough. Likewise, organizational innovation is conceivable – people organize themselves in a new configuration with new results. But institutions in the sense of norms, values, rules and ‘rules of the game’ is harder to grasp. And it is even tougher to get one’s head around how to stimulate this in practice – what does it look like to stimulate institutional change? We need to give practitioners more support in putting all the concepts and abstractions to work.

Projects
Convergence of Sciences: agricultural innovation in West Africa
January 2008 - December 2013
The Convergence of Sciences programme aims to improve the livelihoods of farmers by exploring new pathways for agricultural innovation. Please click here for more information about this project.