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Digital Data Collection

Digital Data Collection. MEL CoP October 2018. MEL Updates:PIIRS. Staff data are ready and can be accessed here ! Reach data Thanks to those who have validated data! Plan to share published figures in the first few weeks of November Impact data

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Digital Data Collection

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  1. Digital Data Collection MEL CoP October 2018

  2. MEL Updates:PIIRS • Staff data are ready and can be accessed here! • Reach data • Thanks to those who have validated data! • Plan to share published figures in the first few weeks of November • Impact data • Review and publishing will occur after reach data are released • Have feedback on the PIIRS FY18 process? We are happy to receive it at piirs@careinternational.org • This will support a future CoP meeting on learnings and next steps for FY 19

  3. Improved timeliness in the reporting of data FY 18 FY 17 We received data a month sooner than last year! THANK YOU!!!

  4. MEL Updates: Building a MEL Package • Have MEL orientation materials that you would like to share? Want to be involved in developing this package? • Please email Ximena Echeverria and Korinne Chiu • We are looking for materials in the following categories: • General • Design/planning • Data collection • Data analysis • Reflection and learning • Are there materials you would like to have, but can’t seem to find? We want to know!

  5. MEL Updates: Looking for RCTs and quasi-experimental evaluations in the past 5 years 1. Country/countries 2. The specific design (e.g. how many arms etc.) 3. Main impact indicators 4. Start and end dates-year (i.e. when was baseline and endline) 5. Research partners involved 6. Lessons-what went well/ didn’t go well (if available) • Send to Nidal Karim and Anne Sprinkel 

  6. Our presenters • Kobo Toolbox Antoine Attiogbe-Ghana Muhamed Bizimana-Mano River Region • DHIS2 Ekene Osakwe-Nigeria Dora Curry-SRHR CARE USA

  7. Gradual and low cost development of M&E system using Kobotoolbox

  8. REASONS FOR A CENTRALIZED M&E SYSTEM To get the full picture in one place  Tap into the magical world of data visualization Better project management and opportunities for organizational learning  Moreefficiency and the reduction of errors  Audit findings about gap between M&E reports and field reality  Get the information ‘Live and Direct

  9. KOBO Sync KIT data INTEGRATED SYSTEM send KIT data M&E/ PM partners Field Agent CARE Field Agent partners Field officer CARE MGT MR MGT CIV Collect KIT data M&E/PM Field Agent partners Field Agent partners Field Agent CARE Field Agent CARE

  10. USE OF DATA AREAS THE AVAILABILITY OF RELIABLE,ACCURATE AND TIMELY DATA IS KEY • Management and Decision Making(MIS) • Monitoring • Reporting • Evaluation (Doing thingsright) Of Processes and Implementation (Of the use of inputs/activities and process – Random spot checks of intermediate outcomes:Annual surveys) (Achievement ofTargets) On Inputs and Outputs. (On expenditures, activities, coverage (targets) (reporting and monitoring for mid term correction; evaluation for planning and scale up) Using relevant and timely information for decision making (Doing the rightthing) Of Outcomes and Impact (To assess long-term outcomes and impact through studies Reporting: On expenditures, activities, coverage (targets) ) 04 01 QUALITYDATA 03 02

  11. DATA QUALITY CRITERIAS Can technology(MDC) help us address data quality issues 1 3 5 2 4 6 DAta reliability Data validity Data security/confidentiality Data accuracy/precision Data timeliness Data integrity Is the data measuring the “indicator” accurately?) Are we getting the data in time? Is the data free of manipulation? Loss of data / loss of privacy will we get the same data, when collected again? Are we measuring what we say we are measuring?

  12. Mobile data collection Why use Mobile Technology for M&E Real-time decision-making, better implementation and delivery Transparency & Accountability Enabling organizations, donors and stakeholders to use M&E data for real-time decision-making, better implementation and delivery of projects and services Improving transparency & accountability in development organizations and partners, though technology-enabled M&E for better monitoring, sharing, and application of data.

  13. HARMONISE DATA COLLECTION/PROCESS ACROSS MR Manu River Difficult overview Cote d’ivoire Project based system Sierra Leonne Project based systems 03 07 01 05 Guinea Project based systems Liberia Project based systems 02 06

  14. Why we choose MDC as Foundation- Kobotoolbox Among several reasons these are the main ones Cost effective over time- involves one-time hardware costs and ongoing maintenance. No paper, printing costs Real-time data from the point of collection Deployed remotely and tracked in real time, offline collection Easy to manage and analyze large amounts of data Built-in logical flow and validation checks improves data quality Reduces intermediate levels of data transmission

  15. The steps we are going through The foundation is Mobile data collection

  16. WHERE WE ARE

  17. KEY FEATURES OF THE FINAL SYSTEM LINKED TO KOBO 01 - Project 02 - Activity 03 - Logframe 04 - Indicators 05 – Beneficiaries/facilities The Project module allows you to track activities, performance indicators and easily navigate through the project logframe, review the last submitted report, or easily check lessons learned collected on the field as well as other key project data. The Activities module and the Project portfolio module are related as they manage similar data but on different levels. For each project, you can create, plan and monitor activities. Logframe module is a powerful module that allows you to monitor the success and impact of your projects. Mutlilogframe proof. link to parents strategies or programs. Each indicator is linked to a code, label/description and is given a measuring unit and appointed a data entry Frequency or a data table. Most importantly, users can define if the nature of the data is qualitative or quantitative. Beneficiaries and facility management for all projects etc..

  18. DATA STRUCTURE FOR THE INTEGRATED SYSTEM Your Footer Here

  19. QUICK AND EASY SETUP • Improving: • Dataquality • Speed • Transparency • Accessibility • Flexibility

  20. Technical support structure for CIV CO level empowered Team is the best approach, when leadership is supportive

  21. DIGITAL TECHNICAL SUPPORT ROLES 1 3 This role is elected every 6 months, it is the custodian of CO data collection. He/she Provides data management and form authoring support to the entire CO. This role provides also technical advise for MDC related equipment purchase. Finaly ensure project based form sharing protocol is always active Role1-Admin Manage CO data collection and reports, Provide technical support in form design and deployment Role 3 – M&E Support the digital process and design forms for their respective project 2 This role is also elected every 6 months and assist the Admin in all functions. He also ensure that standard are followed. 1 Role2- Admin assistant Assist The CO Admin in his/her role + ensure standard are followed 2 3 Although all M&E seems to me autonomous they also provide they also provide peer review support to their fellows during form design or questionnaire elaboration.

  22. Few USE CASES IN civ and Liberia Facility mapping Savings groups mapping Project evaluations Reporting and monitoring Field form kits standadized All VSLA in Ivory Coast and Liberia created by CARE have been mapped out, all VSLA projects PROCOCO, COCOALIFE, W4C PROCOCO, COCOALIFE, W4C,H&M, PARSI, SAFPAC, POWER AFRICA All facility present in communities where VSLA are, have been mapped out in CIV and Liberia, all VSLA Projects Facility mapping form Activity forms Value chain actors tracking forms Beneficiaries db form Beneficiaries needs form Most significant stories form

  23. Map showing VSLA groups in ivory coast The selected group has quick basic information

  24. Map showing VSLA groups in ivory coast - contd

  25. Facilities available in vslacommunitIES SAFPAC – ONE FACILITY SELECTED

  26. CHALLENGES General challenges and specific challenges shared by CO’s Admin • Generally Since this process was a pilot, buy-in by CO has not been smooth.(we are extremely grateful to CO who supported this initiatives) • Project and COs have not budgeted for the process especially for the smartphones so in most case we will have to resort to BYOD tactics • Community agents need furthertraining – use of the phones • Peer support has been low in the beginning but it is better now. • We need more dedicated time/staff to track and support the system completion • M&E need further training in data analytics to harness the best of kobo

  27. Antoine yawo Attiogbe Muhamed Bizimana Presentation on manu river digital data implemenation Antoine.Attiogbe@care.ORG Thank You!  Q&A Photo credit: HypnoArt via Pixabay (Creative Commons Zero license)

  28. DHIS2 for routine MIS at CARE – options and possibilities One project’s approach to going digital for routine monitoring for quality improvement

  29. What is DHIS2? • Non-profit, open-source management information system program • data collection, storage and analysis • Currently being used for WASH, livelihoods, forestry… (as well as health) • In development for over 20 years, supported by University of Oslo plus network of consultants, new version every 3 months • Funded by NORAD, PEPFAR, the University of Oslo, the Global Fund, CDC, Gates Foundation & others • Used by 47 countries and national standard in 16 countries

  30. The “DISC” • What is it • an MIS for project monitoring and program improvement • A web-based database in the DHIS2 platform • Routine monitoring for • One initiative, i.e., one outcome area • Two languages • Multi-country • Monthly reporting on outputs, quality and service delivery • Tracking over time for health providers’ clinical skills

  31. What was the challenge? The Current System at CARE: SAFPAC as an example Many, many documents in different formats (hardcopy, MS Word, MS Excel) Many steps for data transfer Prone to human error Very time-consuming Limited flexibility for data visualization Cannot track progress of individuals Rapid increase in data as we are growing fast Peer organizations are moving away from this kind of system Very difficult to compare results across programs

  32. What solution did we try??? – the “DISC” • A database • To unify all out data collection • To link multiple data sources • Web-based (remote server hosted) • To shift to real-time (removing multiple days of waiting in email inboxes from the cycle time • To expand access to data visualization and reporting functions to anyone we give a log in to once, instead of only those we’ve emailed the latest excel to. • To enable mobile collection - theoretically

  33. Why THAT solution? Why DHIS2??? • Open-source, not dependent on a vendor, guidance on how to minimize costs • Works with intermittent internet connections • Collects data with mobile phones/data entry apps (no internet connection needed) • Uploads data into system when internet is available • Very flexible • works with multiple data formats • imports/exports to multiple systems • Can track individuals • Dashboards can be customized • Technical support and learning opportunities => part of a knowledge sharing community

  34. Using the system – Who uses it? How hard is it? What support is needed? • Users • CO MEL focal point = CO level system admin • Field = data entry • Program managers, ACDs, etc. = data viz and custom reporting • Data • SRH indicators – services, community engagement • Process indicators – training, competence, activity monitoring • Skill • For data entry – simple online form • For system admin – basic familiarity with DHIS2, accomplished with week-long academy run by DHIS2 • Support • For overall system support – 2 DHIS2 super-users on global team (full DHIS2 academy plus ongoing self-directed learning, no special software expertise, plenty of M&E background)

  35. Check it out! https://srhedata.care.org/dhis-web-dashboard-integration/index.html

  36. What’s working? • Open source community • Multiple sources for input, guidance technical support • French support (and Portugese and Spanish!) • Positive reception from CO teams • Ease and quality of data entry • Fairly friendly and pretty data viz

  37. What could work better? • Some data manipulations require export to Excel/SPSS/R • Can be finicky to make changes • Requires vendor support for data migration en masse • Some functions aren’t fully supported in other languages besides English

  38. Thank you!

  39. Q&A This Photo by Unknown Author is licensed under CC BY This Photo by Unknown Author is licensed under CC BY-NC-ND

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