Sustainable Infrastructure

Maintain the average age of fleet vehicles at or above national age/mileage standards.

This goal is measured by tracking the average age of all fleet vehicles including those assigned to Sheriff, Fire, Public Works and other departments.Explore the data
average years of age
Final
10average years of age
Jun 2016 Target
Goal Period ended June 2016

            Why is this goal important?

            This measurement helps ensure vehicles are safe, durable and economical. It helps lower and stabilize fleet operating and purchasing costs and provides the necessary data to help maintain a reliable fleet.

            How is this goal measured?

            Our Fleet Division tracks vehicle and equipment life cycle costs including:

            • Utilization
            • Fuel consumption
            • Service and repair
            • Procurement
            • Disposal

            What progress are we making towards this goal?

            Through diligent management of our fleet, we are accomplishing:

            • Lower parts and labor costs
            • Replacing vehicles on a more consistent basis
            • Right-sizing our fleet size
            • Reducing idle time

            FOR MORE INFORMATION:

            What standard do we use?

            We use the American Public Works Association's recommendations and the Federal Vehicle Standards which classify various types and sizes of commercially available vehicles from large construction equipment, law enforcement vehicles, fire equipment all the way to small sedans and establishes minimum technical, quality and optional equipment specifications. The standards ensure vehicles are safe, durable and economical, and help provide uniformity in the acquisition process.

            You can also call Carson City Public Works at (775) 887-2355 for more information.

      Data Governance

      describes the quality of the data itself. Governance issues generally indicate that the data source is considered incomplete or unreliable.

      Model Health

      describes the quality of the predictive model. If the model health is poor, the trend prediction should not be trusted.

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