Analyze Data

The process of model specification and technique selection process depends on benchmarking objectives, data availability, and the team’s willingness to adopt specific assumptions for each type of model. There are four specific analytical techniques, which will be discussed in more detail. The typology of methodologies is summarized as follows

  • Partial Indicators These indicators combine partial indicators of operating or financial performance;
  • Total Factor Productivity (TFP) This is an index number approach that considers output per unit input—where multiple inputs are taken into consideration to gauge efficiency levels and changes;
  • Data Envelopment Analysis is a non-parametric technique that makes no assumptions about the functional form of production or cost functions;
  • Statistical Techniques are parametric approaches that involve assumptions about functional relationships.

These methods are arrayed in terms of the technical quantitative skills required for implementing the different approaches. Summary indices allow analysts to review trends of core indictors over time. Total factor productivity indices provide more comprehensive characterizations of trends over time and of relative performance across a set of water utilities. More sophisticated methods such as DEA and parametric methods require econometric expertise that is not commonly available in many countries. These more sophisticated techniques are not necessarily the most useful in the context of benchmarking. Sometimes simple partial indicators can provide useful comparisons that are intuitive, whereas credible performance comparisons require that the results be communicated in a manner convincing to stakeholders. As a result, methods like Data Envelopment Analysis and parametric methods will only be cursorily discussed.

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