Where to Invest Project Efforts for Greater Benefit: A Framework for Management Performance Mapping with Examples for...

Area of Science:

• Agricultural Science
• Development Economics
• Information Science

Background:

• Policymakers and donors require methods to identify optimal locations for agricultural interventions to maximize benefits.
• Effective targeting is often challenging due to limited information, necessitating a framework to assess the value of information (VOI).
• Previous studies on seed degeneration in potato systems highlight the need for geographically informed strategies.

Purpose of the Study:

• To present a management performance mapping framework for evaluating the VOI in geographic prioritization for regional agricultural interventions.
• To apply this framework to case studies of Andean and Kenyan potato seed systems.
• To demonstrate how assessing VOI can guide targeted development programs and foster continuous improvement.

Main Methods:

• Utilized recursive partitioning, XGBoost, and Bayesian network models to analyze relationships between seed health, yield, and environmental/management predictors.
• Developed a framework for management performance mapping to evaluate VOI in decision-making for intervention strategies.
• Applied the framework to case studies in the Andes and Kenya, focusing on potato seed systems.

Main Results:

• In the Andes, positive seed selection from asymptomatic plants was most effective at high altitudes in Ecuador.
• In Kenya, targeting interventions to areas with higher technology adoption and greater potato cropland connectivity showed potential.
• Geographic targeting of training to high management performance areas is likely more beneficial than random selection.

Conclusions:

• Assessing the value of information is crucial for effective geographic targeting in agricultural development programs.
• Management performance mapping provides a valuable tool for optimizing intervention strategies and resource allocation.
• This approach supports evidence-based decision-making and continuous improvement in agricultural extension and development efforts.