1 June 2012

Health Baseline within Different IAs - Presentation 2

Before the Beginning: "intelligent" health baselines

There is the project development process, the ESHIA process and we use also the business intelligence process.

 

BI refers to computer based techniques and analyses methodologies for identifying extracting and analysing ...

 

ESHIA tends to come in after concept design is almost complete and hence does not have as much influence as the project design related process.

BI aims to map technical, economic, logistics, health and social data that feed into the early phase of the project development process.

 

Case A already started and entered the concept phase:

  • Time and resource constraints
  • There is appraisal of the available data and identifying gaps in the data
  • Stakeholder availability was not ascertained
  • Led to much of the data being obsolete
  • The above biased the baseline data collected
  • Also made monitoring planning more difficult
 

Case B:

 

Data gathering: what and how

  • social and health risks
  • ecosystem services
  • ...
Appraisal of data and gap identification

  • Classifying data as relevant to project or not
  • Is it accurate or not
  • Is it sufficient
  • Logistic, engineering, production, etc...
Data analysis

  • Identifying hotspots and criticalities
  • Classifying by how critical or not an aspect is e.g. Agricultural land,
  • Both risks to the project and risks of project to communities
 

Advantages:

  • Encourages communication ESP in IA teams
  • Truly avoidance first because it happens early rather than just mitigation and compensation
  • Two fold input base data to both project and ESHIA
  • two way identification of risks to project and communities
  • ID of critical gaps
  • ...
Conclusion:

  • Time and resource constraints
  • Leads to win win situation
  • Can help to buil intelligent and effective baselines
 

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