Antecedentes

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.

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 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 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.

Deberes y responsabilidades

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:

1. The modeling will look at alternative financial products now made possible through the federation of SRGs across villages.
2. 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.
3. 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.

Deliverables, Timeframe and Level of Inputs

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:

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.

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.

Recommended Presentation of Offer

1. Confirmation of Interest and Availability;
2. P11 indicating all past experiences from similar projects, as well as contact details (email and telephone number) of the Candidate and at least three (3) professional references;
3. Cover letter with brief description of why the individual considers him/herself as the most suitable for the assignment;
4. 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.

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.

Competencias

Corporate Competencies:

• Demonstrates integrity by modeling the UN’s values and ethical standards and acts in accordance with the Standards of
• Conduct for international civil servants;
• Advocates and promotes the vision, mission, and strategic goals of UNDP;
• Displays cultural, gender, religion, race, nationality and age sensitivity and adaptability;
• Treats all people fairly without favouritism.

Functional Competencies:

• Good knowledge of the natural resource management particularly lake and watershed management, the concept of sustainability and sustainable development in the region and developing countries;
• Ability to quickly grasp and synthesize inputs from a range of disciplines related to sustainable financial mechanism for environmental conservation;
• Ability to advocate and provide technical advice on the relevant sector/theme;
• Self-motivated, ability to work with minimum supervision;
• Promotes a knowledge sharing and learning culture in the office;
• Sensitivity to and responsiveness to all partners, respectful and helpful relations with all UN/UNDP staff;
• Consistently approaches work with energy and a positive, constructive attitude;
• Remains calm, in control and good humoured even under pressure;
• Demonstrates openness to change and ability to manage.

Habilidades y experiencia requeridas

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.

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Annexes – Please visit  http://procurement-notices.undp.org/view_notice.cfm?notice_id=40073
Template for Letter of Interest and Availability

Financial Proposal Template
Terms of Reference

P-11