Research Design & Data Framework Development for Data-Scarce Systems

RESEARCH DESIGN | DATA FRAMEWORK | VALUE CHAIN | FISHERIES | WORLD BANK | FAO

This project focused on designing a structured research and data framework to support decision-making in a fragmented fisheries value chain, enabling reliable data collection, analysis, and investment prioritisation.

  • Client Situation

    Fragmented and inconsistent data with no clear framework to guide fisheries investment and policy decisions

  • What Was Done

    Designed a structured research and data framework linking data collection to decision-making

  • Outcome

    Clear, actionable system for identifying inefficiencies and prioritising high-impact interventions

The Challenge

  • No structured framework to understand value creation across the value chain
  • Fragmented, inconsistent, and largely informal data
  • Limited ability to identify inefficiencies or value loss
  • Difficulty linking data to investment and policy decisions
  • Complex multi-stakeholder environment with limited existing data

Our Approach

1. Define clarity before data collection
Unstructured data leads to unclear decisions. A framework was designed to define what data to collect, why it matters, and how it informs strategy.

2. Prioritise system-level understanding
The value chain was analysed across interconnected layers rather than isolated components.

3. Treat data as a decision-making tool
All data collection and analysis were structured to directly inform investment and policy decisions.

What We Did

  • Conducted a structured desk review of existing reports, data, and sector frameworks
  • Designed data collection frameworks across landing sites, markets, and MSMEs
  • Developed and implemented survey tools using KoBoToolbox for scalable field data collection
  • Developed methodological protocols for consistent and scalable data collection
  • Structured sampling approaches to capture representative insights across value chain actors
  • Defined key variables across infrastructure, markets, governance, and socio-economic factors
  • Built analytical flow linking raw data to insights and recommendations
  • Integrated gender, youth, and stakeholder dynamics into the research design
  • Designed stakeholder validation processes to ensure findings were actionable
  • Supported synthesis of outputs into a structured, decision-ready format

The project transformed fragmented and inconsistent data into a structured framework, enabling clearer identification of inefficiencies and high-impact intervention points. By aligning data collection with decision-making needs, the work supported more targeted investment strategies and improved the reliability of policy-relevant insights.

  • Why This Matters

    This project demonstrates how research design directly determines the usefulness of data in complex environments.

    Without a structured framework, data remains fragmented and difficult to translate into action.

    By aligning data collection with decision-making, the work enabled clearer insights, reduced uncertainty, and more targeted investment strategies.

Have a Similar Challenge?

If you're working in complex or data-scarce environments and need clarity before making strategic or investment decisions, we can help design the structure behind it.

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