The need to rapidly “scale up” successful climate change adaptation projects, programmes and policies is widely recognised, but there are currently few adaptation-specific examples to demonstrate how such scaling up can take place, or what elements are necessary for such scaling up to take place.
The question of how to turn “pebbles in a small pond into ripples of change” is not, however, a new one. The development community has grappled with this problem for a few decades at least, and while success may have been limited even in that context, there are some important lessons that can be imported into the adaptation context to avoid wasting precious time in the fight against climate change.
Attempts to scale up development interventions date back to at least the 1970s, starting with the World Bank’s attempts to promote replicability and address development challenges on a larger scale. In the 1980s, as non-government organisations were increasingly involved in development activities, they were faced with the question of how to scale up their interventions, which are typically small, but often apply new approaches. More recently, the international community’s efforts to address the Millennium Development Goals, the Paris Declaration on Aid Effectiveness, and the economic crisis have driven the quest to scale up development interventions.
A couple of years ago, I worked on a project for GIZ India where I had the chance to explore some successful examples of scaling up in the development context, in India and around the world, to identify common elements that could be applied to the adaptation context. The results of this analysis are not at all surprising – in fact, most of the key common elements turned out to be fairly commonsensical. What is surprising, perhaps, is that these commonsensical elements have not yet found wider application.
I propose to explore the concept of scaling up successful development interventions in a series of four or five blogs, starting with a crash course in definitions and concepts related to scaling up (in this blog – boredom alert!); going on to a couple of successful case studies (or more – who doesn’t love case studies, particularly successful ones); and finally summarising key lessons.
Definitions of the scaling up process have been developed over time, along with conceptual frameworks and implementation tools. The most common and widely adapted definition is perhaps the one proposed by the World Bank in 2005: expanding, replicating, adapting and sustaining successful policies, programs or projects in different places and over time to reach a greater number of people.
Literature on scaling up development practices views scaling up as a very deliberate process, a definite aim from the beginning of a project or activity, rather than an afterthought at the end. The Brookings Institution identifies three distinct phases of this process in a working paper on scaling up: innovation, learning and scaling up.
During the innovation phase, a new model, idea or approach is embedded in a pilot intervention or project. Other practitioners define the difference between pilots and demonstration projects – the former includes at least one innovation, while the latter takes an existing model to demonstrate its usefulness to decision makers and potential users. They also differentiate between innovations (minimal objective evidence); promising practices (anecdotal reports and testimonials); models (positive evidence in a few cases); good practices (clear evidence from several settings/evaluations); best practices (evidence of impact from multiple settings, meta‐analyses, expert reviews); and policy principles (proven in multiple settings, considered widely applicable, and a “truism” essential for success).
During the learning phase, the experience with the design and implementation of the pilot is monitored and evaluated, and a knowledge management strategy is implemented to ensure that lessons are captured, disseminated, and stored in an “external knowledge base”. Finally, in the scaling up phase, the original idea, model or approach is brought to scale, based on the learning of the pilot phase itself, and on additional knowledge from the broader external knowledge base.
Scaling up could be horizontal (replication from one geographical area to another); functional (through adding additional areas of engagement); and/or vertical (for instance, from the local level to provincial or nation-wide engagement, or to “mainstreaming” in national practice or policy).
Finally, the Brooking Institute working paper calls for close attention to “drivers” and “spaces” for scaling up.
Drivers refer to forces that can push the scaling up process forward – including for instance, a new idea or innovation (or an old one, whose time has come); suitable leadership, or a champion; a vision; an external catalyst (such as a natural disaster); and a system of incentives and accountability that encourages actors to look toward scaling up as a key criterion defining their success.
Spaces refer to the opportunities that can be created, or potential obstacles that need to be removed for interventions to grow. Such spaces could include fiscal space (resources that need to be mobilised for scaling up); policy space (the policy and legal framework needed to allow scaling up); institutional/organisational space (the capacity that has to be created); political space (the political support needed from important stakeholders); partnership space (partners that need to be mobilised); learning space (knowledge about what works and doesn’t work, harnessed through monitoring and evaluation, knowledge sharing and training); natural resources/environmental space (mitigating harmful effects to the environment, and rewarding beneficial impacts); and cultural space (cultural obstacles or support mechanisms need to be identified, and the intervention suitably adapted).
A commitment of time
A clear idea of the ultimate scale or magnitude to which an intervention should or could be taken, given the needs of the target population and the nature of the intervention, is a useful starting point for scaling up. It is also important to be realistic, from the start, about the time it will take to achieve the desired ultimate scale – which could be as much as a decade or more.
For instance, DHAN Foundation in Tamil Nadu, India, is one of the few organisations I know of that is committed to trying out innovations in the field, turning successful innovations first into models and then programmes, and finally building resource centres to promote scaling up. In this way, they have successfully promoted innovations in community banking and microfinance, water management, strengthening local governance, and ICT for the poor, among others.
According to M.P. Vasimalai, Executive Director of DHAN, the DHAN model of scaling up involves an innovation phase, which extends over five to eight years. The first three to five years of this phase are necessary to ensure local buy-in, establish local leadership, and ensure basic infrastructure is in place. Later during this phase, project participants from different implementation sites are brought together and given the opportunity to exchange information and experiences. Based on this feedback, a basic model is created, which is tested in different ecosystems where it is fine tuned and adapted. Finally, once 40-50,000 families have tested the model, DHAN creates a resource centre to provide institutional back up for further scaling up. The whole process could take well over ten years.
In my next blog, I will leave this admittedly less familiar territory of theories, concepts and tools to return to experiences on the ground. I am generally suspicious of the theory, toolkit and tickbox (Triple T!) approach to development, and certainly don’t advocate rushing off, pencil in hand, to look for innovations, pilots, driver and spaces. Instead, I hope that these definitions will present a broad idea of what scaling up means and highlight the key elements that should be considered, while the case studies I describe in subsequent blogs will show that the process itself need not be so complicated. I will begin with what is arguably the most successful example of scaling up in India: watershed management.
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