Terms of Reference (TOR) Data Analyst

Transcription

1 LOCATION: Terms of Reference (TOR) Data Analyst APPLICATION DEADLINE: 25 August 2017 TYPE OF CONTRACT: Post Level: Languages required: Yangon, Myanmar and home-based (with possible domestic travel) Individual Contract (IC) International Consultant English Duration of Contract: 40 Working Days (October December 2017) Agency/Project Name: UNDP Myanmar, Pillar 1, Output 2-Civil Society and Media 1) Background and Project Description UNDP in Myanmar is partnering with Myanmar s largest federation of women s Self Reliant Groups (SRGs) called May Doe Kabar in implementing a data innovations prototyping project for women s economic empowerment. SRGs are women s village-based savings and loans groups in which members contribute savings to build up a common fund from which they can borrow. The groups promote access to credit, livelihood activities, and improved skills and strengthening of social capital of poor rural women, to aid in poverty alleviation and boost local economic development. A typical SRG is comprised of approximately women with close affinity, who contribute weekly savings to establish group owned common funds, which are then built up to a sustainable level and leant out for livelihood investments (e.g. purchase of tools), urgent family consumption needs (e.g. health or education). In addition, and given sufficient funds and consensus in the group groups also support small community development projects (e.g. building access roads). Through a federation process, 2000 SRGs have networked with each other and elected township and national leadership to form May Doe Kabar. Many of the SRGs have been operating for 5-10 years or more, and hold detailed paper records on household poverty status, savings contributions, and loans data (including the purpose of the loan and repayment status) for the member households stretching longitudinally across these years. With an eye towards these records and the larger objective of the SRGs and their national federation, this data innovations prototyping project is based on the following observations and problem statements: (1) The paper-based record keeping by village-level SRGs hinders the effectiveness of the national federation to mobilize its strengths in achieving the members and groups objectives of women s economic empowerment and poverty alleviation. May Doe Kabar, whilst now formed as a national level federation, continues to offer

2 financial products to its savings and loans members that are based on separate, atomized village common funds. As such, it is potentially missing out on opportunities to leverage the benefits of its national structure for risk diversification, different size or types of loans, and different packages of financial products. Through data analysis of previous experience with individual and village group savings and loans over time, models of alternatives that could address shortcomings, create new opportunities, and forge new partnerships with MFIs or banks, could potentially be developed. Successful prototypes could be tested by assessing member/user feedback on possible alternative financial product offerings (using ways of helping members/users envision alternatives). (2) Information about household poverty status and patterns of financial mobility, resilience and local economic development, and the factors that influence these, may be hidden in the SRG records of the borrowing and savings behaviors over time and associated characteristics and conditions of individual members and village groups. Anecdotally, it appears that successful SRGs follow a progression from predominantly borrowing for immediate consumption needs -> to borrowing for basic livelihood investments -> to borrowing for more entrepreneurial investments. From this we hypothesize that ability to address immediate consumption needs sufficiently to enable the progression to more productive livelihood and entrepreneurial investments can be an accelerator of households /groups poverty alleviation and economic development. Through data analysis on previous experience with individual and village group savings and loans over time, plus other potential factors related to household poverty status that are within the knowledge of these groups, it is possible to identify whether there is any statistical relationships among identified factors in the data that appear to predict greater likelihood of stepping out of poverty, or being more resilient to shocks, or overall group/local economic development effects. Successful prototypes would be tested by (a) determining whether such statistical relationships exist in the data, and (b) designing a proposed set of randomized control tests/experiments for interventions that accelerate the positive effects. To implement the prototyping project, UNDP Myanmar with May Doe Kabar have inventoried the potential data available in SRGs detailed records on members savings and loans history and household conditions. Through field collection in sample locations in the federation, longitudinal records are now being digitized for data analysis. Additional variables related to household poverty status, local economic development and other environmental factors are being gathered through ethnographic research to develop thick data for inclusion in the data analysis. For the next step, UNDP requires the Consultant services of an expert Data Analyst to run data modeling and data exploration research on the database. The modeling will look at alternative financial products now made possible through the federation of SRGs across villages. The data analysis will further explore what statistical relationships exist between access to finance (i.e. savings and loans behavior) and household poverty alleviation, household resilience and local economic development. Based on the results, the Data

3 Analyst will support UNDP s Consultant for Data Management and Data Engagement to formulate hypotheses about interventions to accelerate the positive effects of SRG-based access to financial products and their effects on household poverty alleviation, resilience and local economic development, and to design Randomized Control Tests to test the hypotheses. 2) Scope of Work Reporting to UNDP s National Coordinator-May Doe Kabar, under the direct guidance of the International Consultant for Data Management and Data Engagement, and under the overall guidance of Programme Specialist-Civil Society and Media the Data Analyst will have responsibility for the longitudinal data modeling and data exploration research aspect of the data innovations prototyping project with May Doe Kabar and its SRGs. Specifically: (i) The modeling will look at alternative financial products now made possible through the federation of SRGs across villages. (ii) The data analysis will explore whether and what statistical relationships exist between access to finance (i.e. savings and loans behavior) and household poverty alleviation, household resilience and local economic development. (iii) The results aim to provide a basis for formulating hypotheses about interventions to accelerate the positive effects of SRG-based access to financial products and their effects on household poverty alleviation, resilience and local economic development, and to design Randomized Control Tests to test the hypotheses and make policy recommendations. 3) Deliverables, Timeframe and Level of Inputs Deliverable Due Date Estimated Time Commitment 1. Inception meetings with data innovations prototyping consultants/staff/stakeholders to understand the data and database, ethnographic research and observation to yield additional standardized data, resulting in a written proposal of relevant hypotheses for exploration and analysis. 2. Data exploration, analysis and modeling performed on the database, resulting in a written report. 3. Based on the analysis and modeling results, written inputs provided to support design of Randomized Control Tests (RCTs) to test hypotheses and make policy recommendations on accelerating the positive effects of SRG-based access to financial products and their effects on household poverty alleviation, resilience and local economic development, and (on request) meetings/presentations of the analysis and proposed 10 Oct days (in Yangon) 10 Nov days (home based) 10 Dec days (in Yangon)

4 RCTs. 4) Payment Terms Payment will be certified Programme Specialist-Civil Society and Media, based on review and acceptance of the completed deliverables presented with required IC contract paperwork. Full-day work and meetings on weekends will be counted as working days. The contract anticipates a level of input of 40 working days over October 2017 through December 2017, with two trips to Yangon, Myanmar. Payment will be based on actual number of days. Payment breakdown of the all-inclusive fixed contract total price is as follows: of Deliverable #1 of Deliverable #2 of Deliverable #3 40% 40% 20% The all-inclusive fixed contract total price includes fees and costs and all necessary software, hardware and server space to complete the assignment. The assignment requires two trips to Yangon, and costs of travel and living expenses/visa should be taken into account in the all-inclusive financial proposal. If any field travel outside is required, UNDP will arrange and cover the expense of transportation between Yangon and the field location as per travel policies. 5) Institutional Arrangements The Data Analyst will work under the supervision of UNDP s National Coordinator-May Doe Kabar, under the direct guidance of the International Consultant for Data Management and Data Engagement, and under the overall guidance of Programme Specialist-Civil Society and Media. The Data Analyst may also interact with project stakeholders in May Doe Kabar at various levels, as well as other UNDP staff and development partners. The Data Analyst will be home-based with two trips to Yangon to facilitate coordination and brainstorming on the project, as well as results presentation and discussion. The Data Analyst will be expected to furnish his/her own computer, software, server space, and (aside from meetings at UNDP office in Yangon) own working space. 6) Qualifications

5 The qualifications of the successful Data Analyst (IC International Consultant) should include: Education Masters Degree in an area relevant to the assignment, such as Computer Science, Information Systems, Mathematics, or Statistics. Experience At least 7 years experience in longitudinal data modeling and analysis. Strong background in research and analysis in the areas of household poverty alleviation and access to finance. Understanding of data innovation methodologies and designing data-based experiments preferred. Flexibility to adapt expectations and project outputs to field-level realities. 7) Recommended Presentation of Offer a) Confirmation of Interest and Availability; b) P11 indicating all past experiences from similar projects, as well as contact details ( and telephone number) of the Candidate and at least three (3) professional references; c) Cover letter with brief description of why the individual considers him/herself as the most suitable for the assignment; d) Financial Proposal that indicates the all-inclusive fixed total contract price, supported by a breakdown of costs. Cost of round trip economy class airfare may be included. 8) Criteria for Selection of the Best Offer Combined Scoring method where the Qualifications will be weighted 70% and combined with the Price offer which will be weighted 30%. Qualifications will be assessed as per following criteria: 20 points = education, 30 points = experience in longitudinal data modeling and analysis, 30 points = background in poverty alleviation and access to finance research, 20 points = understanding data innovation methodologies and designing data-based experiments. (Total 100 points.) Passing score of Qualifications is 70 points, and only passing applicants will be evaluated in combined scoring with Price offer. Approved by: Jane Lawson Programme Specialist-Civil Society and Media OIC Date: 03 August 2017