Data collection, data use and (sub-) systems building: the SMARTerWASH experience
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The SmarterWASH project aimed to enhance water, sanitation, and hygiene (WASH) monitoring in rural Ghana through ICT development and extensive data collection across 131 districts. The project successfully established data collection systems, assessed the functionality and service levels of water sources, and produced valuable resources like regional factsheets. However, challenges remain in ensuring ongoing monitoring and leveraging data for improved service delivery, highlighting the need for adequate capacity and incentives.
Data collection, data use and (sub-) systems building: the SMARTerWASH experience
- 1. Supporting water sanitation and hygiene services for life Marieke Adank So what for lunch, 2 May 2017 Data collection, data use and (sub-)systems building: the SMARTerWASH experience
- 2. SMARTerWASH 3,5-year project (March 2013 -December 2016) Partners: IRC, CWSA, Akvo FLOW, SkyFox Purpose: To scale up and consolidate WASH sector monitoring in rural communities and small towns in Ghana. Major components: − ICT development − Monitoring (baseline data collection) at scale
- 3. 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Publication of monitoring framework NLLAP meeting on indicators Triple-S ICT development Regional posters and factsheets National Forum Development of indicator framework Piloting of indicator and data collection tools in 3 districts Data collection 16 districts SMARTerWASH Data collection 131 districts DiMES development SkyFox SMS dev FLOW dev
- 4. The successes: ICT development DiMES, Akvo FLOW, SkyFox further developed Interoperability between ICT systems
- 5. Akvo FLOW (dashboard and app) - Surveys - Collect data Skyfox Database with: - Facilities - Spare parts - orders DiMES The elements
- 6. Akvo FLOW (dashboard and app) - Surveys - Collect data Skyfox Database with: - Facilities - Spare parts - orders SMS/ USSD / Call centre DiMES Current database Reports Excell Data cleaning Community CWSA management CWSA Regions Districts SkyFox data - functionality DIMES database: - Population data - Facility data / asset data FLOW data • Functionality • Service level • SP Performance • SA performance Manual entry Other stakeholders • Coverage figures • Functionality • Service level • SP Performance • SA performance
- 7. The successes: data collection at scale • Leveraging funding from different projects • Data from 131 districts was collected, processed and analysed • Capacity built for data collection, processing and analysis • Regional and district factsheets, regional posters, digital atlas produced
- 8. The successes: data collection at scale 23,001 handpumps 938 piped schemes Almost 15,000 Water and Sanitation Management Teams 131 Service authorities Data collected by Local government, in collaboration with CWSA: • Functionality • Level of service (reliability, distance, crowding, quality, quantity), assessed against national norms and standards Performance on: • Governance • Operations • Financial management Assessed against indicator benchmarks, based on national guidelines Performance assessed against indicator benchmarks
- 9. Baseline results: Comparing handpump service levels between regions 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Brong Ahafo Central Northern Upper East Upper West Western Proportionofhandpumps Per region I: Not functional or not used II: Sub-standard service level - 2 or less of 5 service level norms met II: Sub-standard service level - 3 of 5 service level norms met II: Sub-standard service level - 4 of 5 service level norms met III: Basic service level 6% 25 % 30 % 14 % 26 % Overall
- 10. Baseline results: Comparing performance of small community (rural) and small town Water and Sanitation Management Teams Indicator group Indicator – Benchmark Small communit y WSMT Small town WSMT Governance WSMT composition - In line with guidelines and members have been trained 6% 40% Operational team (PS only) - At least half filled by qualified staff NA 33% Financial and operational records - Kept up-to-date 10% 31% Political interference - no political interference in composition of WSMT 97% 85% Operations Spare parts - Available within 3 days 54% 74%Area mechanic (HP) / technical services (PS) - Available within 3 days 68% Routine maintenance - Done at least annually (HP) / according to maintenance schedule (PS) 44% 21% Water quality testing - Done by certified institute on regular basis (HP) / annual basis (PS) 6% 25% Financial manageme nt Revenue/expenditure - Positive balance 14% 85% Bank account - available and accounts up to date (HP) / 3 bank accounts and accounts up-to-date (PS) 10% 11% Tariff - Tariff set 22% 80% Facility management plan (HP only) - Facility management plan in place 22% NA
- 11. Baseline results: Comparing performance of small community (rural) between districts
- 12. Baseline results: Comparing performance of service authorities between districts
- 13. Lesson learnt: Baseline data collection at scale is doable (with project funding) Costs of data collection (Per diems, transport, tools etc only): − About 6422 Euro per district (for on average 176 handpumps, 7 piped schemes, 115 WSMTs, 1 service authority) However, main challenge: ensuring ongoing monitoring (incentives, financial and institutional frameworks and mechanisms for ongoing monitoring) − About 3235 Euro per district for subsequent monitoring rounds (so about 28 Euro per WSMT per year)
- 14. Lessons learnt: Is data used and does it lead to better services? Mostly anecdotal evidence of data use at district level, e.g. data used to: − Inform District Water and Sanitation Plans (DWSP) in 11 districts in the Upper West, Upper East, Western, Brong-Ahafo and Northern Regions − Inform repairs and rehabilitation of over 600 boreholes with hand pumps restoring water services to an estimated 180,000 people; ( e.g. rehabilitation of 18 boreholes, construction of 75 boreholes with handpumps and four mechanised boreholes in Hilton districts) − Stimulate DA to form or reconstitute WSMTs (e.g. reconstitution of 203 WSMTs in Hilton districts and 24 in Unicef districts).
- 15. Does it lead to better services? Answer based on data over 5 year period from 2 districts: “No” 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2012 2013 2014 2015 2016 Handpumpfunctionality East Gonja Sunyani West Just having the data is not sufficient. Need for human, financial and logistical capacity and motivation and incentives for data use. This goes beyond the monitoring (sub-) system and possibly even beyond the WASH sector
- 16. Lessons learnt related to systems building • Building (sub-)systems takes time; • In order to improve services, there is a need to look beyond the monitoring (sub-) system alone. Way forward • Baseline data collection in remaining 85 districts • Ensure use of data at all levels • Data analysis on whole dataset, including cross analysis (schemes and management), which can inform national level planning and policy making • Development and formalisation of institutional and financial mechanisms for continuous monitoring ………Other suggested lessons learnt? ………..Other suggestions for the way forward?