Data Envelopment Analysis (DEA) is one of the widely used methods in measuring the technical efficiency of organizations. Data envelopment analysis is a classical non-parametric technique based on mathematical programming, which is used to compare the evaluation of the efficiency of a set of similar decision-making units. Its significant advantage is that it does not need to determine parametric specifications (such as the production function) to get performance points. Data envelopment analysis is known as a valid and stable tool used in performance evaluation, which provides a single measure of performance for each unit relative to its peers. Even though the number of data envelopment analysis models is constantly increasing and each one has a specialized aspect, the basis of all is a number of main models, among which we can refer to the "Charnes, Cooper and Rhodes" models (1978) as CCR, in which the assumption of constant returns to scale (CRS) has been used in the analysis. There are different approaches to determining the effective factors on efficiency and productivity and how to measure the productivity of production factors. Among the investigated companies in the years 2019 to 2019, it was found that the technical efficiency of the companies decreased, the technological changes of the companies increased, the managerial efficiency of the companies decreased, the efficiency of the scale of the companies decreased, and the overall productivity of the companies faced a decrease.