Determination of Benchmark Classifications. “Benchmark classes” are normally chosen to reflect a broad spectrum of class levels. In addition, those that are selected normally include classes that are most likely to be found in other similar agencies, and therefore provide a sufficient valid sample for analysis. Internal relationships will be determined between the benchmarked and non-benchmarked classifications and internal equity alignments will be made for salary recommendation purposes. Because we find that the labor market typically yields reliable data, we typically recommend using 60-65% of classifications as benchmarks.
Determination of Benchmark Classifications. In the same collaborative manner as described in Step 1 above, we will work with the District’s stakeholders to select those classifications that will be surveyed. “Benchmark classes” are ordinarily chosen to reflect a broad spectrum of class levels. In addition, those that are selected normally include classes that are most likely to be found in other similar agencies, and therefore provide a sufficient valid data sample for analysis. Internal relationships will be determined between the benchmarked and non-benchmarked classifications and internal equity alignments will be made for salary recommendation purposes. Due to the fact that the labor market typically yields reliable data, we recommend using approximately 60-65% of all classifications as benchmarks but we are happy to use a different model. Due to the District’s relatively small number of total classifications, we will survey the majority. The District does have several class series with multiple levels, for which we typically only survey one level as the benchmark for the series.
Determination of Benchmark Classifications. In the same collaborative manner as described in Step 1 above, we will work with the City’s stakeholders to select those classifications that will be surveyed. “Benchmark classes” are ordinarily chosen to reflect a broad spectrum of class levels. In addition, those that are selected normally include classes that are most likely to be found in other similar agencies, and therefore provide a sufficient valid data sample for analysis. Internal relationships will be determined between the benchmarked and non-benchmarked classifications and internal equity alignments will be made for salary recommendation purposes. Due to the fact that the labor market typically yields reliable data, we recommend using approximately 60-65% of all classifications as benchmarks but we are happy to use a different model.
