SANTA CRUZ COUNTY
PERSONNEL ADMINISTRATIVE MANUAL

PURPOSE:

To define the labor market used by the County for salary setting purposes.

REFERENCE: 

Board Action: November 6, 2001, item No. 62.2.

POLICY:

The County will use the following eight county sample for salary data comparisons: Contra Costa, Marin, Monterey, Napa, Solano, Sonoma, San Mateo, and Santa Clara.

As available, the County will also use other salary surveys of public and private industry (e.g., U.S. Department of Labor Area Wage Survey). This includes salary surveys which operating departments obtain through industry or professional associations; copies of such surveys should be forwarded to the Employee Relations/Salary Administration Division staff in the Personnel Department on a routine basis.

Employee Relation/Salary Administration staff in the Personnel Department will participate in conducting local salary surveys, resources permitting.

BACKGROUND:

1. The County has historically relied upon salary data from nine  comparison counties for negotiations of salary adjustments. These nine counties included the counties listed above as well as Fresno. The origin for use of these nine counties is not known but their use dates back to the 1960's. Personnel staff updated the comparability analysis in October 2001. Fresno County was removed from the list by Board action on November 6, 2001. 
   
   
2. The primary reliance on other county data has been dictated by several factors.
   
   
   1. Equivalents to a majority of the County's benchmark classes are only found in other counties.
      
      
   2. Counties in California have developed salary survey and data links which make the compilation and analysis of compensation data less labor intensive than other means.
      
      
   3. There are limitations on the collection and use of compensation data from other sources, as elaborated below.
      

3. Selection criteria for the eight comparison counties:
   
   
   1. The data must be reliable and consistent. The County's established data base and understanding of the organization of the established counties maximizes benchmark matches and minimizes time devoted to data collection and analysis. 
      
      
   2. The selected counties are comparable to Santa Cruz in one or more of the established criteria: similar economic base, size, workforce and structure. Consideration is also given to median home sales price as well as rental housing.
      
      
   3. The County uses all of its surrounding counties, except San Benito, because a significant amount of the available workforce pool includes candidates from these immediate surrounding counties. San Benito was not included because it does not offer similar breadth and scope of county services and therefore does not provide adequate benchmark information. 
      
      
   4. Five of the eight counties presently use Santa Cruz as a point of comparison for labor negotiations. These counties also include several other counties, and thus the actual data base becomes much broader than it appears. 
      
      
   5. The historical acceptance by employee organizations to the use of a standardized list of comparative counties for all represented units is important. Deviation from this on a negotiation by negotiation basis could result in anomalies.
      

4. The County periodically uses local public agency salary data in conjunction with market data from the comparison counties. This is done only when insufficient comparative data is available within the eight comparable counties for the benchmark positions. 
   
   
5. Use of data from local private industries and firms is limited by its insufficiency and reliability. There are only a handful of positions that match the benchmark positions.
   
   
6. Public and private industry information from other areas (e.g., San Francisco area) and resources (e.g., U.S. Department of Labor surveys and industry surveys obtained directly or through department heads) have been used. There are limitations to the use of this data due to time lags in data collection and survey benchmarks frequently do not match county classes.