AASHTO EFM-1
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AASHTO EFM-1: Decision Making for Outsourcing and Privatization of Vehicle and Equipment Fleet Maintenance
AASHTO EFM-1 presents a framework for conducting systematic analysis and making decisions on outsourcing and privatization of vehicle and equipment fleet maintenance.
The framework defines a decision process model that can be applied to a wide range of outsourcing decision alternatives. The process is presented as a step-by-step logic process that focuses on the unique features of state department of transportation fleet maintenance.
Outsourcing is a key component of the state department of transportation’s (DOT’s) strategy for delivering services. NCHRP Synthesis of Highway Practice 313: State DOT Outsourcing and Private-Sector Utilization documented that either the legislative or executive branches of state government can mandate outsourcing directly, although more commonly they act to limit or reduce the number of state employees, resulting in a de facto mandate to outsource.
Not surprisingly, the most common reasons cited for outsourcing were lack of sufficient staff or improper combination of skills. These reasons were followed by cost cutting and/or improved service quality. The decision to outsource is not an easy one, and how the outsourcing decisions are made is of great interest to state DOTs.
While several best-practice outsourcing models are available in the private sector, caution should be exercised while translating those models directly for use in the public sector. The profit and business development considerations in the private sector should be balanced against the legal, economic, public service, and political mandates of government.
Also, a variety of factors should be considered in the decision process, such as the criticality of the outsourcing candidates to the organization’s mission and goals, availability of third-party vendors, cost, and service quality. Outsourcing public-sector fleet and equipment maintenance offers certain unique challenges that require such decisions to address additional and more complicated considerations.
AASHTO EFM-1: Decision Making for Outsourcing and Privatization of Vehicle and Equipment Fleet Maintenance
AASHTO EFM-1 presents a framework for conducting systematic analysis and making decisions on outsourcing and privatization of vehicle and equipment fleet maintenance.
The framework defines a decision process model that can be applied to a wide range of outsourcing decision alternatives. The process is presented as a step-by-step logic process that focuses on the unique features of state department of transportation fleet maintenance.
Outsourcing is a key component of the state department of transportation’s (DOT’s) strategy for delivering services. NCHRP Synthesis of Highway Practice 313: State DOT Outsourcing and Private-Sector Utilization documented that either the legislative or executive branches of state government can mandate outsourcing directly, although more commonly they act to limit or reduce the number of state employees, resulting in a de facto mandate to outsource.
Not surprisingly, the most common reasons cited for outsourcing were lack of sufficient staff or improper combination of skills. These reasons were followed by cost cutting and/or improved service quality. The decision to outsource is not an easy one, and how the outsourcing decisions are made is of great interest to state DOTs.
While several best-practice outsourcing models are available in the private sector, caution should be exercised while translating those models directly for use in the public sector. The profit and business development considerations in the private sector should be balanced against the legal, economic, public service, and political mandates of government.
Also, a variety of factors should be considered in the decision process, such as the criticality of the outsourcing candidates to the organization’s mission and goals, availability of third-party vendors, cost, and service quality. Outsourcing public-sector fleet and equipment maintenance offers certain unique challenges that require such decisions to address additional and more complicated considerations.
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