The transport of goods is essential for the economic growth of cities and regions. Urban freight transportation makes up a very small percentage of the total transportation time for goods, but it can represent up to 28% of total transportation costs. To reduce overall costs and increase revenue from this operation, one common methodology used by decision makers is the optimization models. This paper proposes a new methodology for evaluating the effectiveness of urban freight transportation systems using the OEE (Overall Equipment Effectiveness) metric, a well-known rate used in the Lean Manufacturing framework. The methodology uses a mathematical model with several objective functions, two of which are multi-objective, to explore the relationships and trade-offs between economic development, quality, performance and availability (partial rates of the OEE). The final objective is to optimize the OEE metrics and the profitability of a transportation system. This methodology was tested using real data from the city of Bogota, Colombia. Experiments were run with different companies, costs, demands and travel times in order to validate the proposed approach. The results show the benefits of using multi-objective functions to optimize both OEE (quality, performance and availability metrics) and profits. The proposed methodology provides an 'ex ante' evaluation of the tactical and operational decisions made by companies in configuring an urban freight transport system.