Can a challenge prize improve farming in Nepal? The Data-Driven Farming Prize developed an impact framework to capture its effects on problem-solving, building capabilities and wider knowledge and awareness.
The DDF Prize aimed to support solutions for smallholder farmers and agricultural stakeholders in Nepal, to help them make effective choices to enhance on-the-ground decision making, their productivity and market planning. The prize also aimed to recognise and promote localised data-driven solutions that could be accessible to and used by smallholder farmers to improve agricultural productivity in a sustainable manner.
Global concern regarding agricultural and food production has been growing. By 2050, over a billion people will be at risk of hunger, with arable land becoming increasingly scarce. Nepal’s agricultural sector contributes 26 per cent of the national GDP as of 2017, with 71 per cent of the population working in this field as of 2018. Nepal has the potential to be a food surplus country if smart, sustainable intensification that includes smallholder farmers can be realised.
The impact methodology used in the Challenge Prize Centre is structured around the impact framework, which includes three key impact categories:
The three categories reflect the types of impact that all prizes should have - prizes are meant to solve problems, improve capabilities, and lead to broader systemic changes. Using the same framework across all prizes ensures more consistency than creating a bespoke process each time. It also allows for comparison between different prizes, which leads to recommendations on how to improve prize methodology. The DDF Prize evaluation was run throughout the prize process, enabling the collection of relevant data to inform a robust evaluation. The outcomes and key results from the prize are noted below.
On Innovation Impact, the DDF prize focused on:
On Capabilities Impact, the DDF prize focused on:
On Ecosystem Impact, the DDF prize focused on:
Following this impact methodology allowed us to better map out the narrative on the impact that the prize would have. By understanding the benchmarks, baselines and impact metrics, the prize was able to build a strong evidence base. We used various evaluation methods including surveys, interviews, focus groups, desk and field research to collect key information.
The data collected at various stages of the prize helped inform certain prize decisions such as with early research into the ways in which farmers take decisions; this informed innovators on how best to frame their proposed solutions or the types of request for mentoring support, allowed us to allocate mentors who were most appropriate for the finalists. We did not adjust the prize design based on any of the data we had collected during the prize, as the prize design was sufficiently robust. We were, however, able to provide innovators in the prize with greater access to farmers and extension workers based on this feedback.
We learnt that it is necessary to have a mix of evaluation methods at every stage in order to gain perspectives of innovators and partners. It is also important to have high response rates to surveys. This proved difficult in the DDF prize and involved having to chase the respondents. However, as part of another prize, we tried to gain the maximum responses to our surveys by ensuring that surveys were sent out alongside key milestones e.g. finalists pre co-creation event survey was sent with the seed funding contract.
A key challenge was the difficulty in measuring the broader ecosystem given the magnitude of the problem that was being tackled in Nepal. Therefore some of the indicators for the DDF prize were either proxies and calculations, but in some instances we were unable to fully capture the ecosystem impact. For example, the number of jobs created as a result of the prize; though one of the finalists was able to hire a new employee, this was an indicator that plays out over longer timescales than we were able to track during and immediately after the prize.
To address this, the team will be conducting a post-prize assessment in Nepal (9-10 months after the prize). This work will be focused on three key areas:
There were some key lessons that were learnt from the utilisation of a prize as a programme.
The evaluation confirmed that this was a well-designed and well-implemented prize, serving as a model for the future. We are reviewing the impact framework, to further strengthen it.
This includes looking at:
Overall, the impact of this prize was overwhelmingly positive, and the success of this prize was such that it inspired and informed the design of future prizes - including the Fall Armyworm Tech Prize.
The design elements that were integrated into this prize following the Data Driven Farming Prize were: