• Home
• Site Map
• Foreword
  • Foreword
  • Contributors & Copyright
• Introduction
  • Introduction
  • Methods
  • Sites
    • Why Pando and East Kalimantan?
    • Municipal Governments and Decentralisation in Bolivia
    • Municipal Governments and Decentralisation in Indonesia
• Part I. Concepts
  • Wellbeing and Poverty
    • Poverty is More Than Low Income
    • Poverty is a Lack of Wellbeing
    • Poverty and Wellbeing Have Many Dimensions
    • Further Reading
  • Local Governments and Poverty
    • How can Local Governments Reduce Poverty?
    • Four Steps to Improve Local Governmental Action
    • Further Reading
  • Forests and Poverty
    • How do Forests Influence Poverty?
    • What is Poverty in Forest Communities?
    • Are Forests Safety Nets, Poverty Traps or Escape Routes?
    • Further Reading
• Part II. Tools
  • Monitoring
    • What is monitoring?
    • Types of Monitoring
    • Indicators
    • When to monitor?
    • Who conducts monitoring?
    • Linking monitoring to planning
  • Participatory Planning
    • What is participatory planning?
    • Why is participatory planning useful?
    • When and where is participatory planning done?
    • Who should participate?
  • Tool 1: Interactive Mapping
    • What is interactive mapping?
    • Interactive mapping step-by-step
    • Use interactive mapping for monitoring
  • Tool 2: Wellbeing Monitoring
    • What is a local wellbeing monitoring system?
    • Wellbeing monitoring step-by-step
    • Step 1: Define purpose, develop plan and budget
    • Step 2: Develop local poverty indicators and formulate survey questions
    • Step 3: Design the sampling strategy
    • Step 4: Train staff and perform the survey
    • Step 5: Analyse and present the data
    • Step 6: Present findings
  • Tool 3: Community Evaluation
    • Evaluating local government programmes through community focus groups
    • Steps 1-3
    • Steps 4-6
    • Steps 7-8
    • Community evaluation step-by-step
  • Tool 4: Scenario-based Planning
    • What is scenario-based planning?
    • Scenario-based planning step-by-step
    • Visioning
    • Pathways
• Final Remarks
• Acknowledgements
• Additional Resources
• PDF Version

Step 4. Train staff and perform the survey

A. Train staff

Develop a staff training programme. Training should cover interviewing techniques as well as data handling. The type of training depends on the detail of data collection, and the methods used.

If the number of communities and respondents is small, it may be sufficient to train just one survey team. For surveys covering a large number of communities, a large area and a large number of respondents, plan a ‘training of trainers’. These trainers can then prepare multiple survey teams to carry out the data collection.

Timing is important. If too much time elapses between the training and the surveys, the data quality diminishes. If the sampling is conducted regularly, conduct a refresher training session before every survey to maintain quality.

B. Assign responsibilities for data collection, processing and analysis

Clearly define responsibilities within the team. This is essential to ensure smooth implementation of the survey. Carefully supervise the use of funds. Research existing prices for transport, accommodation and other expenses. Often the budget for surveys is limited, so the efficient use of available funds is crucial.

For the survey team, incentive-based compensation can be helpful. For example, in Kutai Barat, data collectors received payment for each completed questionnaire. However, be sure to follow up in the field and crosscheck data collection to minimise misuse of incentives and to verify quality.

Once the data collection is completed, arrange for data processing and analysis. Local government may not always have the technical know-how for data processing. In that case, either provide additional training or outsource the data entry and analysis. However, one problem may be that the trained staff may change jobs or be transferred to other parts of the government. Try to provide training for local community members as well, for instance, to become monitoring assessors. This will increase local capacity.

If data processing and analysis is outsourced, clearly define what information the data analysing party should provide. Carefully supervise the process.

© 2007 Center for International Forestry Research (CIFOR)
Contributors and copyright information