Análise exploratória da eficiência de sistemas produtivos utilizando o Benchmarking interno e a DEA Window - Hamdan, Yuri Dias (Universidade do Vale do Rio dos Sinos, 2025)
Efficiency is a key indicator for assessing the performance of an organization's production units. Analyzing efficiency allows managers to assess how companies are operating in comparison with the productivity targets set for different periods of time. The aim of this study is to analyze efficiency over time by means of internal benchmarking and the DEA Window of the production process of a company in the metal-mechanics segment. The DEA Window is a non-parametric panel approach that is suitable for measuring the level of efficiency of various decision-making units (DMUs) in relation to their own performance over time. A case study is carried out, seeking to obtain the efficiency scores of the DMUs, as well as comparing the efficiency scores and the targets and gains of the DEA and DEA Window models with windows of three and six periods. The main results show that the conventional DEA model obtained an average efficiency of 75.93%, while the three- and six-period window approaches had average efficiencies of 98.64% and 97.11%, respectively. Furthermore, in the comparative analysis of targets and gains, the conventional DEA model indicated gains of up to ten times the value of certain inputs, when compared to the DEA Window models, highlighting the Window models' discrimination problems. The main contributions of this work indicate that, when a longer time series is available, the window approach associated with internal benchmarking can be an alternative for evaluating efficiency over time. In addition, the DEA Window model allows for a dynamic analysis of efficiency, since the use of moving windows makes it possible to follow the evolution of efficiency over time.
Keywords: Indústria metalmecânica; Eficiência ao longo do tempo; Análise Envoltória de Dados; DEA Window; Benchmarking interno; Metalworking industry; Efficiency over time; Data Envelopment Analysis; Internal benchmarking; ACCNPQ::Engenharias::Engenharia de Produção