The value chain to be analysed is on Mango and Lime in Guinea Bissau.  The assignment would possibly start with a mission in June and then go on in October after the rainy season.

We are looking for 4 experts: one agro-economist, one environmentalist, one social expert and one local expert.

They will each provide an input of about 45 working days.

The deadline for presenting CVs is on 6th April 2017 by close of business.

The experts will perform the value chain analysis according to a methodological framework (see attachment). This will focus on collecting quantitative data and evidence based data for informing decision.

  1. Agro-economist
    S/he will be a senior expert with deep knowledge of and experience on value chain analyses from an economic point of view. S/he will be able to undertake a full functional analysis with the support of his/her colleagues. S/he will elaborate financial and economic accounts of the VC actors and the VC as specified in the toolkit to inform indicators such as the total Value Added (in contribution to GDP), the production accounts per type of actor, the impact on balance of trade; impact on public funds balance; competitiveness and sustainability within the international economy through the Domestic Resource Cost ratio.

    Specific experience on agricultural value chains in developing countries will be an asset.

    Experience in arboriculture value chains (in particular mango and lime) is required.

    Knowledge on Guinea Bissau will be appreciated.

    Experience in stakeholder management or policy and practice capacity is a plus.

    Knowledge of Portuguese is an asset.

    S/he will provide a report on Functional Analysis and Economic Analysis that will be included in the final report.

    A demonstration of the specific software AFA used for the economic analysis will be made to the Economist prior to the first mission.


  2. Social expert
    S/he will be a senior expert with deep knowledge of and experience on social issues related to value chain in developing countries (gender, youth, social inclusion, social cohesion, labour conditions, social values and norms, customary rights, food security…).

    S/he will have experience at least in one or these domains and be able to handle the other ones.

    Specific experience in the analysis of the agricultural sector in developing countries will be an asset.

    Experience in the arboriculture value chains (in particular mango and lime) is required.

    Knowledge on Guinea Bissau is required.

    Knowledge of Portuguese is an asset.

    Experience in stakeholder management or policy and practice capacity are a plus.

    S/he will provide a report on Social Analysis that will be included in the final report.

    A demonstration of the Social Profile as a guiding tool will be made to the Social Expert prior to the first mission.


  3. Environment expert
    S/he will be a senior expert with deep knowledge of the Life Cycle Analysis.

    Experience on value chain analysis in developing countries will be appreciated.

    Experience in the arboriculture value chains (in particular mango and lime) is required.

    Knowledge on Guinea Bissau will be appreciated.

    S/he will preferably use the SimaPro software for LCA.

    Knowledge of Portuguese is an asset.

    S/he will provide a report on Environmental Analysis that will be included in the final report.


  4. National expert
    S/he will be a specialist of the arboriculture chain (in particular mango and lime) in Guinea Bissau.

    Relevant knowledge of the national institutions (technical, economic and political ones) and of stakeholders involved in fisheries is required.

    At the beginning of the study, s/he will provide overall information on the value chain, identifying the key players and existing and relevant information to be used later for the analysis.

    S/he will facilitate the access to information and complete the data collection.

    The local expert will help to select the most relevant data from available sources, help to clarify inconsistencies and select relevant data to improve the coherence of analysis.

    Please send your applications to Olimpia Orlandoni
27.03.2017