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Priority assessment, process and 
linking with IDOs and business cases 
RTB Annual Review and Planning Meeting 2014 
29th Sept to 3rd Oct, Entebbe, Uganda
Task Force Permanent Members 
Bioversity: Diemuth Pemsl, Charles Staver 
CIAT: Bernardo Creamer, Glenn Hyman 
CIP: Guy Hareau, Ulrich Kleinwechter 
IITA: Tahirou Abdoulaye, Arega Alene, 
Joseph Rusike, Holger Kirscht 
RTB: Graham Thiele
Outline of presentation 
• Status of RTB priority assessment (PA) 
– Overview of six steps methodology 
– Summary of key outputs and results 
• Lessons learnt from the PA exercise 
– What went/worked well? How to improve? 
• Next steps: outlook on 2014/15 activities 
– Communication strategy for priority assessment 
– Ex post impact assessment studies 
• Discussion 
– Stakeholder feedback 
– Data bases including RTB maps 
• Linking with IDOs and business cases 
• Discussion: Application of PA outputs and results
Strategic assessment of research 
priorities for the RTB : six steps
Key outputs of priority assessment 
• Expert survey (N = 1,681) to identify key constraints 
with input from diverse, international group of stakeholders 
• Priority research options selected 
based on expert survey results & input from RTB resource persons 
• Collection of data/information for model parameters 
from statistics, existing data sets and group of technical experts 
• Economic surplus (ES), poverty and cost-benefit 
analysis for a total of 31 research options 
with harmonized assumptions and methods across all five crops 
• 10 RTB working papers completed 
Expert survey & ES report for each crop 
• RTBMaps developed as cooperation of RTB Centers 
interactive online tool providing geographic information to the 
research and development community of roots, tubers and bananas
How many participated: 
Expert survey on key constraints: 
- Bananas 
- Cassava 
- Potato 
- Sweet potato 
- Yam 
Research options and model parameters: 
- Bananas 
- Cassava 
- Potato 
- Sweet potato 
- Yam
All reports uploaded to RTB webpage 
Online comment function are available! 
http://www.rtb.cgiar.org/category/resources/working-papers/
Editors’ Choice Winner 
ComputerWorld 2014 
Special Achievement in GIS Award 
ESRI International Conference 2013
Potato expert survey results: top 10 
Notes: Experts scored research activities on a five point scale: 1 = not important, 2 = somewhat important, 
3 = important, 4 = very important, 5 = extremely important: 
LAC: Latin America and Caribbean (N=140), SSA: Sub-Saharan Africa (N=79), ESEA: East and Southeast Asia (N=121), 
SWCA: South, West and Central Asia (N=61); 
Share of female respondents: 22%
Priority assessment: Summary of results 
Expert survey 
• Contact lists of crop experts/stakeholders 
• Major constraints and opportunities by crop 
• Ranking of different research options for each crop 
(results can be explored on global or regional level, by ecosystem, country 
or in the case of banana by cultivar group or cropping system) 
• Rich data set available for further applications 
Selection of research options / model parameters 
Different approaches for different crops 
• Banana: Kampala workshop with 45 ARI and national 
banana scientists to select ROs and initial parameters 
• Banana: final parameters by few CG experts 
• Cassava and yam – expert consultation CG based 
• Potato / sweet potato – similar options as Fuglie + CIP 
consultation
Priority assessment: Summary of results 
Economic surplus model and poverty effect 
Total of 31 research options (RO) assessed; # RO by crop as follows: 
Banana - 6; Cassava - 10; Potato - 6; Sweetpotato - 4, Yams - 5 
• Data base of parameters (country and technology specific) 
• Positive net present values (NPVs) for all RO 
• IRRs of assessed ROs well beyond 10% benchmark 
• Results indicate considerable poverty reduction
Banana: Overview of research options
Yam results: adoption ceiling & benefits 
Note: Lower adoption scenario: analysis with 50% lower adoption ceiling. 
Net Present Values (NPV) calculated using a real interest rate of 10%.
Cassava: beneficiaries & poverty effect 
Note: Lower adoption scenario: analysis with 50% lower adoption ceiling. Poverty reduction 
computed using on NPV (10% interest rate), national poverty incidence, share of agriculture on GDP 
(%), population, region specific elasticity (see Alene et al. 2009).
Sweetpotato: adoption by region
Extending economic surplus analysis: 
estimation of DALY benefits for OFSP 
Note: Lower adoption scenario: analysis with 50% lower adoption ceiling. 
NPV calculated using an interest rate of 10%.
Lessons learnt: what went well? 
• Successful application of priority assessment 
approach in a multi-Center and multi-crop context 
(consistent methodology and same set of outputs for each crop) 
• Generated valuable information to guide strategic 
decision making and inform RTB target setting 
(rich and detailed data set from expert surveys; data compiled for 
economic surplus analysis  both can be further explored) 
• Participation of a global group of stakeholders (large 
scale expert surveys, workshops and groups of resource persons) 
• Capacity building of RTB scientists in ex ante impact 
assessment approaches (crucial especially for Centers with 
no previous experience in systematic priority assessment)
Lessons learnt: how to improve? 
• Careful cross calibration of parameter estimates 
e.g. to ensure same levels of optimism about scale of adoption and 
magnitude of effects such as yield increase or cost reductions 
• Expand depth and breadth of impact modeling 
- incorporate additional methods (e.g. DALY for health impacts) 
- compare different models (e.g. IMPACT) for other indicators 
- develop methodology to incorporate gender aspect/impacts 
• Harmonize & integrate with other RTB activities 
- Link data collection from field trials and M&E with PA data needs 
- Better link development of RTB flagships and PA 
• Consistent/continuous involvement of stakeholders 
- stakeholder feedback on parameter estimates 
- future use and updating of RTBMaps and Banana mapper 
- encourage involvement of RTB scientists in (next) PA
Next steps: Activities for 2014 
• Completion of priority assessment work: 
– Review of RTB working papers 
http://www.rtb.cgiar.org/category/resources/working-papers 
• In-house: pdfs available on RTB webpage 
(online comment function will be added soon) 
• Peer-review by selected independent (crop) experts 
– Synthesis report 
• Develop and implement PA communication strategy 
together with RTB communication unit 
– Sharing with and feedback from stakeholders 
e.g. SROs (CORAF,ASARECA, IICA, etc.), banana networks, 
RTB meetings and webpage, social media 
– Publications: RTB working papers, journal papers
Next steps: an integrated approach 
for RTB ex post impact assessment 
PMU supporting impact studies for 2014/15: 
– Re-engaging stakeholders: leveraging priority assessment and 
network analysis for more effective outcomes and impact of 
RTB research (Bioversity, cooperation with ILAC and 
coordination with RTB communication strategy) 
– Use of DNA finger-printing and improved measures of on-farm 
yield gains to assess poverty impacts of cassava in sub-Saharan 
Africa (Nigeria), Asia and Latin America (Colombia) (CIAT, IITA, 
coordination with BMGF) 
– Outcomes of crop germplasm improvement research: cassava, 
potatoes and sweetpotatoes varietal release & adoption in Asia 
(China, India, 12 other countries) (CIP, CIAT, coordination with 
SIAC/MSU/SPIA) 
 Taskforce will develop and apply common methods & databases
Key points for discussion 
• How to engage stakeholders: 
- Appropriate communication strategy, to whom and 
about what 
feedback on parameters 
informing research priorities and regional policy 
in what languages? 
- More applications/use of priority assessment 
outputs by stakeholders 
• RTB crop maps and other data bases – link to other 
uses and build for future use
Linking with IDOs and business cases 
Assessed banana research options and links to RTB flagships
RTB impact pathway and links with PA 
Research 
products Research 
outcomes 
Flagships and 
linked products Next Users 
IDOs 
First level 
development 
outcomes 
End Users 
Intermediate 
development 
outcomes 
System level 
development 
outcomes 
RTB – Impact pathways 
Adoptable 
innovations 
( = outputs) of 
research options 
Adoption 
estimates 
Estimates of: 
economic surplus, 
poverty reduction; 
nutrition and 
health benefits 
Benefit estimates: 
Changes in costs, 
productivity, 
income, health, 
etc. 
RTB Priority Assessment
Key points for discussion 
• What will be the role of priority assessment in the 
development of the second phase? 
• When do we do the next priority assessment? 
• What are key areas for improvement for the next 
time and how to we build the data bases?
Thank you for your attention!

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Priority assessment process and linking with IDOs and business cases

  • 1. Priority assessment, process and linking with IDOs and business cases RTB Annual Review and Planning Meeting 2014 29th Sept to 3rd Oct, Entebbe, Uganda
  • 2. Task Force Permanent Members Bioversity: Diemuth Pemsl, Charles Staver CIAT: Bernardo Creamer, Glenn Hyman CIP: Guy Hareau, Ulrich Kleinwechter IITA: Tahirou Abdoulaye, Arega Alene, Joseph Rusike, Holger Kirscht RTB: Graham Thiele
  • 3. Outline of presentation • Status of RTB priority assessment (PA) – Overview of six steps methodology – Summary of key outputs and results • Lessons learnt from the PA exercise – What went/worked well? How to improve? • Next steps: outlook on 2014/15 activities – Communication strategy for priority assessment – Ex post impact assessment studies • Discussion – Stakeholder feedback – Data bases including RTB maps • Linking with IDOs and business cases • Discussion: Application of PA outputs and results
  • 4. Strategic assessment of research priorities for the RTB : six steps
  • 5. Key outputs of priority assessment • Expert survey (N = 1,681) to identify key constraints with input from diverse, international group of stakeholders • Priority research options selected based on expert survey results & input from RTB resource persons • Collection of data/information for model parameters from statistics, existing data sets and group of technical experts • Economic surplus (ES), poverty and cost-benefit analysis for a total of 31 research options with harmonized assumptions and methods across all five crops • 10 RTB working papers completed Expert survey & ES report for each crop • RTBMaps developed as cooperation of RTB Centers interactive online tool providing geographic information to the research and development community of roots, tubers and bananas
  • 6. How many participated: Expert survey on key constraints: - Bananas - Cassava - Potato - Sweet potato - Yam Research options and model parameters: - Bananas - Cassava - Potato - Sweet potato - Yam
  • 7. All reports uploaded to RTB webpage Online comment function are available! http://www.rtb.cgiar.org/category/resources/working-papers/
  • 8. Editors’ Choice Winner ComputerWorld 2014 Special Achievement in GIS Award ESRI International Conference 2013
  • 9. Potato expert survey results: top 10 Notes: Experts scored research activities on a five point scale: 1 = not important, 2 = somewhat important, 3 = important, 4 = very important, 5 = extremely important: LAC: Latin America and Caribbean (N=140), SSA: Sub-Saharan Africa (N=79), ESEA: East and Southeast Asia (N=121), SWCA: South, West and Central Asia (N=61); Share of female respondents: 22%
  • 10. Priority assessment: Summary of results Expert survey • Contact lists of crop experts/stakeholders • Major constraints and opportunities by crop • Ranking of different research options for each crop (results can be explored on global or regional level, by ecosystem, country or in the case of banana by cultivar group or cropping system) • Rich data set available for further applications Selection of research options / model parameters Different approaches for different crops • Banana: Kampala workshop with 45 ARI and national banana scientists to select ROs and initial parameters • Banana: final parameters by few CG experts • Cassava and yam – expert consultation CG based • Potato / sweet potato – similar options as Fuglie + CIP consultation
  • 11. Priority assessment: Summary of results Economic surplus model and poverty effect Total of 31 research options (RO) assessed; # RO by crop as follows: Banana - 6; Cassava - 10; Potato - 6; Sweetpotato - 4, Yams - 5 • Data base of parameters (country and technology specific) • Positive net present values (NPVs) for all RO • IRRs of assessed ROs well beyond 10% benchmark • Results indicate considerable poverty reduction
  • 12. Banana: Overview of research options
  • 13. Yam results: adoption ceiling & benefits Note: Lower adoption scenario: analysis with 50% lower adoption ceiling. Net Present Values (NPV) calculated using a real interest rate of 10%.
  • 14. Cassava: beneficiaries & poverty effect Note: Lower adoption scenario: analysis with 50% lower adoption ceiling. Poverty reduction computed using on NPV (10% interest rate), national poverty incidence, share of agriculture on GDP (%), population, region specific elasticity (see Alene et al. 2009).
  • 16. Extending economic surplus analysis: estimation of DALY benefits for OFSP Note: Lower adoption scenario: analysis with 50% lower adoption ceiling. NPV calculated using an interest rate of 10%.
  • 17.
  • 18. Lessons learnt: what went well? • Successful application of priority assessment approach in a multi-Center and multi-crop context (consistent methodology and same set of outputs for each crop) • Generated valuable information to guide strategic decision making and inform RTB target setting (rich and detailed data set from expert surveys; data compiled for economic surplus analysis  both can be further explored) • Participation of a global group of stakeholders (large scale expert surveys, workshops and groups of resource persons) • Capacity building of RTB scientists in ex ante impact assessment approaches (crucial especially for Centers with no previous experience in systematic priority assessment)
  • 19. Lessons learnt: how to improve? • Careful cross calibration of parameter estimates e.g. to ensure same levels of optimism about scale of adoption and magnitude of effects such as yield increase or cost reductions • Expand depth and breadth of impact modeling - incorporate additional methods (e.g. DALY for health impacts) - compare different models (e.g. IMPACT) for other indicators - develop methodology to incorporate gender aspect/impacts • Harmonize & integrate with other RTB activities - Link data collection from field trials and M&E with PA data needs - Better link development of RTB flagships and PA • Consistent/continuous involvement of stakeholders - stakeholder feedback on parameter estimates - future use and updating of RTBMaps and Banana mapper - encourage involvement of RTB scientists in (next) PA
  • 20. Next steps: Activities for 2014 • Completion of priority assessment work: – Review of RTB working papers http://www.rtb.cgiar.org/category/resources/working-papers • In-house: pdfs available on RTB webpage (online comment function will be added soon) • Peer-review by selected independent (crop) experts – Synthesis report • Develop and implement PA communication strategy together with RTB communication unit – Sharing with and feedback from stakeholders e.g. SROs (CORAF,ASARECA, IICA, etc.), banana networks, RTB meetings and webpage, social media – Publications: RTB working papers, journal papers
  • 21. Next steps: an integrated approach for RTB ex post impact assessment PMU supporting impact studies for 2014/15: – Re-engaging stakeholders: leveraging priority assessment and network analysis for more effective outcomes and impact of RTB research (Bioversity, cooperation with ILAC and coordination with RTB communication strategy) – Use of DNA finger-printing and improved measures of on-farm yield gains to assess poverty impacts of cassava in sub-Saharan Africa (Nigeria), Asia and Latin America (Colombia) (CIAT, IITA, coordination with BMGF) – Outcomes of crop germplasm improvement research: cassava, potatoes and sweetpotatoes varietal release & adoption in Asia (China, India, 12 other countries) (CIP, CIAT, coordination with SIAC/MSU/SPIA)  Taskforce will develop and apply common methods & databases
  • 22. Key points for discussion • How to engage stakeholders: - Appropriate communication strategy, to whom and about what feedback on parameters informing research priorities and regional policy in what languages? - More applications/use of priority assessment outputs by stakeholders • RTB crop maps and other data bases – link to other uses and build for future use
  • 23. Linking with IDOs and business cases Assessed banana research options and links to RTB flagships
  • 24. RTB impact pathway and links with PA Research products Research outcomes Flagships and linked products Next Users IDOs First level development outcomes End Users Intermediate development outcomes System level development outcomes RTB – Impact pathways Adoptable innovations ( = outputs) of research options Adoption estimates Estimates of: economic surplus, poverty reduction; nutrition and health benefits Benefit estimates: Changes in costs, productivity, income, health, etc. RTB Priority Assessment
  • 25. Key points for discussion • What will be the role of priority assessment in the development of the second phase? • When do we do the next priority assessment? • What are key areas for improvement for the next time and how to we build the data bases?
  • 26. Thank you for your attention!

Editor's Notes

  1. Shall we highlight names of people who have left? And/or include Ricardo?
  2. Introduce the “success indicators” NPV and IRR, as well as adoption ceiling or number of beneficiaries reached Results can be used to “test viability” of a research project (positive returns?) and to compare different alternatives if resources are limited. Results obviously determined by parameters used (garbage in – garbage out?!)  BUT: once model structure exists, parameters can be modified if more/better information/data become available. Parameter tables need to be provided together with results so that stakeholders can see what assumptions went into the assesssment. Results are “to the best of our current knowledge” – improvement over less structured or ad hoc decisions for allocation of research funds.
  3. Estimated number of households and persons who will benefit from each of the research options is based on adoption ceilings and assumptions on average crop area per HH and number of persons per HH (following assumptions used in RTB proposal; roughly 0.2 to 1 ha of banana area and some 4-6 family members – different for each country included in the assessment). These figures are determined by the adoption ceiling in each of the countries, the number of countries included, and the production area within those countries. Similar to the NPV results, this information should be interpreted with respect to the different magnitude of the investments required/assumed across research options. For the calculation of the estimated poverty reduction effects of the different research options we followed the methodology described in Arega et al. (2009), which predicts poverty reduction based on estimated growth in the agricultural sector of a given country. To this end, the NPV of the benefits generated by the surplus model is interpreted as agricultural growth. The poverty model uses the country-specific poverty level, the relative size of the agricultural sector (% GDP from agriculture), and the total national population as inputs. Country-level data were obtained from the World Bank’s World Development Indicators database
  4. Estimated number of households and persons who will benefit from each of the research options is based on adoption ceilings and assumptions on average crop area per HH and number of persons per HH (following assumptions used in RTB proposal; roughly 0.2 to 1 ha of banana area and some 4-6 family members – different for each country included in the assessment). These figures are determined by the adoption ceiling in each of the countries, the number of countries included, and the production area within those countries. Similar to the NPV results, this information should be interpreted with respect to the different magnitude of the investments required/assumed across research options. For the calculation of the estimated poverty reduction effects of the different research options we followed the methodology described in Arega et al. (2009), which predicts poverty reduction based on estimated growth in the agricultural sector of a given country. To this end, the NPV of the benefits generated by the surplus model is interpreted as agricultural growth. The poverty model uses the country-specific poverty level, the relative size of the agricultural sector (% GDP from agriculture), and the total national population as inputs. Country-level data were obtained from the World Bank’s World Development Indicators database
  5. Estimated number of households and persons who will benefit from each of the research options is based on adoption ceilings and assumptions on average crop area per HH and number of persons per HH (following assumptions used in RTB proposal; roughly 0.2 to 1 ha of banana area and some 4-6 family members – different for each country included in the assessment). These figures are determined by the adoption ceiling in each of the countries, the number of countries included, and the production area within those countries. Similar to the NPV results, this information should be interpreted with respect to the different magnitude of the investments required/assumed across research options. For the calculation of the estimated poverty reduction effects of the different research options we followed the methodology described in Arega et al. (2009), which predicts poverty reduction based on estimated growth in the agricultural sector of a given country. To this end, the NPV of the benefits generated by the surplus model is interpreted as agricultural growth. The poverty model uses the country-specific poverty level, the relative size of the agricultural sector (% GDP from agriculture), and the total national population as inputs. Country-level data were obtained from the World Bank’s World Development Indicators database