optimizes its own internal processes and systems using the latest technologies
in communication, management and results monitoring. We support out partners to
build knowledge-driven institutions through the development of ‘open data’
strategies underpinned by the use and analysis of big data. This ranges from
data of telecommunications operators to the provision of geographical
information collected by interventions.
Example from Rwanda: Mobile data collection for the BE1-EARP intervention’s baseline
The Belgian contribution to the Electricity Access Roll-Out Programme (BE1-EARP) aims to improve the access to reliable on-grid electricity services in rural areas in Rwamagana, Ngoma and Kirehe districts. The main activity to achieve this is the electricity grid extension in specific lots in these districts with the construction of new transmission and distributing lines connected to the national electricity network. The existing houses, public institutions and businesses in the intervention area are then connected to this grid.
In the end of 2017, the construction works in Rwamagana were completed. Parallel with the final stage of the works in December, the intervention conducted a survey amongst a large sample of beneficiaries. Out of apx. 8000 new connections, a sample of 954 households and 152 non-households (non-residential customers such as small businesses and churches, and to a smaller extent also schools, health centers and cell offices) were interviewed using Kobo Toolbox, an open source mobile data collection tool.
Increased data quality through mobile data collection
The survey is conducted by use of a mobile data collection tool, Kobo Toolbox. After a one-day training and a pilot survey, a team of 7 data collectors visited all respondents for face-to-face interviews and presented them a set of questions. Answers were registered on tablets, containing the pre-programmed surveys with apx. 50-70 questions (taking into account different scenarios in the course of the survey). A great advantage of Kobo Toolbox is that it can be used offline, as all the interviews took place in remote areas.
However, the improved data quality is the most important advantage. The data collectors upload the completed surveys every evening to the Kobo platform, which then automatically generates a database of collected data. This allows real-time monitoring and easy data analysis. The skip patterns and validation functions (build-in limitations for data entry) inside the tool ensure both the logic of the survey and of the answer to each question.
Working with digital tools also avoids the risk of post-survey data entry mistakes, which is often the case with paper based surveys.
Through the survey, data were collected regarding the current energy consumption of households and non-households, and their intentions and expectations regarding the future (after connection to the on-grid electricity). The obtained data allow the intervention to better understand the potential results on outcome level as well as they point out challenges to be considered.
53% of the sampled households responded using torchlights to brighten their houses (possibly in combination with other traditional sources), while others are found using candles and off-grid solar lamps as lighting solutions.
97.8% of households and 99.3% of non-households expressed their willingness to connect to the grid. People not only expect to better their lives with improved lighting solutions, they also foresee positive changes in the community as electricity opens up new economic opportunities, improve health facilities and delivery of public services.
However, the biggest challenge is the cost of electricity and its affordability for the households. The current energy related expenditures of sampled households are found to be on average a monthly 1905 RwF. With this amount, households will not be able to consume more electricity than what is required for basic lighting and mobile phone battery charging. The looming question is thus will the cost of electricity risks prohibit certain section of household to reap the benefits of electricity despite being connected to the grid? Are the benefits for the population sufficient to justify an investment equivalent to apx. 300 months of electricity consumption for the average household?
A similar baseline survey will take place in Ngoma and Kirehe during the next months. In a second phase, there will be a follow-up survey amongst the same sample of beneficiaries in all 3 districts. The follow-up survey is planned to take place minimum 1 year after the baseline survey and will serve to get better insight in whether and to what extent beneficiaries make use of electricity, the reasons why they potentially don’t and whether or not access to on-grid electricity has resulted into (direct or indirect) socio-economic results, and thereby provides data for the intervention to measure results on outcome level.