1. SHARING EXPERIENCES WITH MOBILE PHONE DATA COLLECTION IN UGANDA FLAVIA KYEYAGO OUMA UGANDA BUREAU OF STATISTICS 14 th October 2015 REGIONAL WORKSHOP & CONFERENCE ON THE USE OF MOBILE TECHNOLOGIES FOR STATISTICAL PROCESSES; UNITED NATIONS CONFERENCE CENTER, ADDIS ABABA, ETHOPIA; 13-16 OCTONER 2015

2. CONTENTS  Introduction  Pre Mobile CIS issues  Design & Methodology  Data collection and Extraction  Lessons  Benefits  Challenges  Conclusions .

3. INTRODUCTION  Mobile Data Collection (MDC) - use of mobile phones, tablets or PDAs for data collection.  Many platforms that can be used to design surveys to collect specific data i.e statistical data, photographs, data from a preselection, voice recordings, GPS coordinates, etc.  Platforms vary in ease of use, cost, and features.  Some requirements that must be defined.  sample sizes, budgets, technology services  data quality requirements.  Variances in the interfaces, server side components like databases, data reporting and management interfaces and available technology services and infrastructure  Mobile Data Collection Application Trends:  Development of Native applications installed on the data collection device  Use of USSD as the messaging framework to send the data to server via SMS  The use of the browser based software to collect and send data to an Application server

4. INTRODUCTION  In 2008, GOU, started a programme called the Community Information System (CIS)  The main objective was to  collect Administrative data  empower communities to make informed decisions using readily available up to date information.  The CIS was first implemented in 2009 in about 50 districts  Multisectoral approach and UBOS was in charge of data processing  used paper based questionnaire and  a system for data entry was developed  However, there were many challenges experienced that included technical and non technical issues that led to the exercise stalling

5. Pre Mobile CIS issues  Infrastructure limitations no electricity and room at Sub- counties  Limited HR for entry even at both Sub county & district level  Entry required long term employment not sustainable  Data delays and data obsolete yet wanted real time data for planning at that level  lack of integration of the data - In 2011, the growing use of mobile phones pushed the IT team to innovate and experiment the use pf mobile phones on the CIS project - The developed a web based solution which could be accessed through the web browsers that are native on the mobile phone - Was done with the objective of introducing the alternative of MDC - Reduce on some of the infrastructural limitations

6. Design & Methodology  The Web application was designed by the IT Team at UBOS using previous experience  This web interface is accessed through phones with web browsers.  Why Web - web is ubiquitous in nature and can be accessed by any device, anywhere, anytime  Scope: 5 Modules with about 25 questionnaires, that included administrative data on health, education, financial institutions, general operations  Technology and Application: mobile device phones with sim cards, Designed using HTML5, CSS, PHP and Java Script for the front end & Mysql for the back end.  Server was configured at UBOS § IT team monitored data transmission, aggregation and extraction 

7. Design & Methodology  The conceptual stages involved  designing the form,  deploying the Form on the server,  deploying the form on the device,  collecting data, sending data to the server and  downloading the data from the server and analyzing the data.  the Client module - functionalities of getting blank forms from the web server to a mobile phone and also filling the forms and sending the forms to the server.  allows for setting logical question flow–thereby making non-applicable questions hidden from enumerator,  Administration Module : for data management, data reports, data exportation, data visualization

8. Data collection & Extraction  Testing : 3 Districts (Urban/Rural)  Training : Done at the Sub county level  Staffing  Enumerators – CDOs – Parish and Village  Supervisors – District Planners & Population Officers  Supervisors – UBOS  Rolled out to date in about 12 districts  access to the application is done through the browser, with user name & Password  Data is captured via the mobile client and sent via the internet using mobile data transmission technologies (edge or GSM) to a central server at UBOS.  Once a user has filled in the questionnaire, they are able to submit the data and get a notification message that the data has been submitted.  Validation is done on the phone before the data is sent to the server.  No data is stored on the phone.  Set validation checks are programmed into the system for answers entered ( logic skips)  some data cleaning is already completed due to these features built into the system  system is real time it allows for prompt review of data quality and makes auditing much easier.  Data can be exported to different formats: CSV, Ms Excel

9. MCIS Project planning TasksDuration Project Planning6 months Proof of Concept (3 districts)3 weeks Design & Testing by the UBOS IT team10 weeks Deployment and Training5 days Data Collection10 days Generate Draft Data Collection Report2 days

10. Lessons Piloting and iteration are critical  Decide on the course of actions  target data collection efforts to the needs and usage the CIS  eliminated the fears of the government officials Technology and Team  Composition of the team ( IT & Statisticians). Training and Support  4 days of In-depth training of enumerators and supervisors (questionnaire/System/Trial ) and continuous support . Security  Data integrity and security Project planning  The team should plan way in advance in order to loose any time factors System should be fully developed  before the actual data collection exercise where possible  Learning curve  enumerators using the phone for data entry  For the development team

11. Benefits/ Results Reduced time  Faster, received in real time  of data collection impacting on presentation of findings  the combination of Data extraction and data entry Processes Provision of real time data and improved data monitoring process Reduced cost  reduced paper use, storage space and paper waste  More innovation which has lead to more capacity built and Adoption More support from management, more awareness, training support  Sustainable system that can obtain data on a regular basis  .

12. Challenges  Fears to move from PAPI to CAPI – keep adopting and improving  Lack of Policy on Mobile phone use -  Training the CDOs – slow learning curve, emphasize key point & give support  Internet Connectivity  Poor network coverage - change sim cards to the network that is available/ adding an offline mode.  Battery life  Phone batteries would not last the whole day  – charge with the local area centres and also some have backups and others would use their phones.  using the in-built touch keypad  size of keypad especially for a very long questionnaire was seen a problem  Errors  small keys -correcting mistakes -decimal point  Data sharing to other MDAs is not yet very feasible

13. Conclusions Policy Issues  With the increasing data demands, NSOs should put in place policies that support mobile phones usage  Budgeting and planning for such projects is important  Capacity building and benchmarking should encouraged Infrastructure issues  Network connectivity shortcomings – consider using off line platforms  Research on mobile GSM Terminals that can expand network coverage (PPPs)  Expand the use of Mobile phones to  Push for more support and collaboration from developing partners and TRIs  Do more research on the best platforms (Cross sectional and long term surveys)  Distinguish factors responsible for error rates  Measure the CBA by carrying out the same survey with both Paper & Mobile for comparison purposes Data Management issues  Management of the full data production cycle to dissemination and archiving stages should considered.