the challenge

Our client is responsible for the building of a hydroelectric dam which will support transmission lines and optimize future river flows. This construction, of a 2-year duration, is key for future territorial development. With that in mind, our client ambitions to measure and communicate around the positive impact of the project. To that end, Ksapa has been asked to support them in the development of their social-impact methodology. This impact methodology will later on be used on other projects, so as to communicate at company-level on social impact related to its projects. 


In order to better understand the social context and project priorities, Ksapa led a variety of exchanges to include different points of view and expertise: site manager, technical director, human resources, financial director, works manager, environment, health and safety, CSR, etc.

This entire process, held exclusively in remote mode, made it possible to identify the priority themes and indicators to be monitored, as well as the points of vigilance.

The indicators identified were refined using definitions and standards from an internationally recognised database (IRIS+). This made it possible to rely on consensual definitions ensuring comparability and alignment between stakeholders (donors, project owners, local institutions, local authorities, etc.). The proposed parameters were also matched with the relevant SDGs. 


Ksapa identified specific social issues for which, taking into account the specificities of the context and the company, impact indicators were identified and prioritised by the project’s internal stakeholders.

Each indicator was then specified, taking into account the well-known IRIS+ methodology specifying metrics, definitions and complements – all elements needed to achieve alignment between stakeholders. The difficulty of implementation was assessed in terms of data model, data type and sources.

Ksapa recommended its client to assess these elements in order to better prepare the next phases:

  • Mobilise an expert resource on the type of data identified
  • Implement the data project
  • Sources: internal, external
  • Data definition: taxonomy, calculation methods, data model…
  • Quality: completeness (missing data), consistency, conformity (expected format), uniqueness…

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