The current growth of the economy, the opening of markets and the trend of the same level, make a series of challenges for organizations which demands a greater effort to remain productive and thus achieve greater competitiveness in the market.

In the logic of the growth of the companies, these need efforts to increase their market share, financial efforts in human resources and efforts in fixed assets that may affect the level of efficiency of the companies and assist with compliance of organizational objectives. In this regard, it is necessary an effort not alien to the growth of the company, which from a broad point of view should cover the efforts mentioned above and in this way improve the logistics processes. Free trade treaties create a series of challenges in which in addition to the improvement of quality and price, the quality of the acquisition processes from the raw materials up to the delivery of the products and/or services must be improved.

As previously mentioned, it is necessary the implementation of a management system to ensure the safety of the processes that integrate the supply chain; and for this reason standards for secure commerce are implemented, as it is the BASC certification (Business Anti Smugling Coalition), which seeks answers to the issue of control management and safety of the trade. According to, processes in the international trade require formality and timely responsiveness, guarantees on the transactions and assurance of the supply chain, which is precisely achieved with the BASC certification.

For the measurement of how effective the BASC model is, in this research work is defined a structure of input and output variables, with which it was measured the efficiency of the DEA CCR-OR model in this group of companies that assumed that standard in the city of Cali - Colombia.

The data envelopment analysis (DEA) is a tool that allows the measurement of efficiency in the public or private organizations through a linear programming model. Charper, Cooper and Rhodes originally proposed this tool of analysis of efficiency in 1978. It is important to note that this tool proposes models for the evaluation of efficiency, one model oriented to entries (CCR - I) and another aimed at the outputs (CCR - O), the latter one seeks to maximize the outputs from the resources available. Maximize the efficiency seeks a fractional programming solution which has multiple solutions, in this sense, it is necessary the implementation of a linear programming model, and this is achieved by leaving the numerator constant (assuming a value of 1) and maximizing the numerator; this is called CCR oriented to the outputs or commonly called CCR - O.

This model is expressed mathematically as it follows, if Yo = (ylo, y2o, y3o.....yso) and Xo = (xlo, x2o, x3..... xmo), represent the inputs and the outputs of the DMUo respectively, the measure of efficiency of the unit being evaluated can be obtained with the optimal solution of the following model:

Being u _ro y v _ro the group of DMU more favorable, the previous model can be converted to:

Where n is the number of DMU, m is the number of input variables and s is the number of output variables.

The DEA tool is one of the most used in the evaluation of performance of public and private organizations (Nijkamp, Suzuki 2009). Within the logistics processes, its use is necessary to assess the efficiency, productivity, and observe the units that can be improved as a measure of competitiveness. The use of the technique has many applications within the logistics processes, for example, evaluation of the efficiency with a focus on the suppliers (Azadeh, Alem 2010; Çelebi, Bayraktar 2008; Farzipoor Saen 2009; Jong Joo, Min 2006; Kontis, Vrysagotis 2011; Min, Joo 2009; Mohammady Garfamy 2006; Narasimhan, Talluri, Mendez [no date]) in the evaluation of manufacturing (Shorouyehzad, Lotfi, Aryanezhad, Dabestani 2011), in the evaluation of reverse logistics (Haas, Murphy, Lancioni 2003; Tonanont, Yimsiri, KJ Rogers PhD 2009; Tonanont, Yimsiri, Jitpitaklert, Rogers 2008).

The data envelopment analysis (DEA) is a parametric tool that allows the evaluation of efficiency; it is important to note that the Data Envelopment Analysis looks for the obtaining of an efficient frontier, which is estimated by maximizing the outputs with a certain level of income; and the estimate of the inefficiency, which depends on the orientation and is calculated in the same way as the efficient frontier (Morollón, Morán, Cuervo 2005)

Below, the variables considered in the study and their description are shown, this was established by the Superintendency of corporations.

The results of this research article make reference to: 1) the efficiency scores of the certified companies with BASC in the city of Cali, 2) the study of the correlation between the variables in the rese arch, 3) the classification of the different organizations by types of efficiency, 4) as well as to the projection of improvement of the output, i.e. operating revenues, with the aim of improving the relationship of input/output with the purpose of making an inefficient firm, efficient. To finally analyze the relationship between the organizational efficiency of the sector and the standardization with the standard for secure commerce BASC in the city of Cali.

Initially the correlation between the variables of the study is presented, used to analyze the technical or administrative efficiency. As seen in Table 2. The data shows a high positive correlation between the input and output variables, allowing to analyze the causality between the items.

Table 2

Social Reason	(I) Subtotal Inventories	(I) Total Current Assets	(I) Properties Plant And Equipment	(I) Suppliers	Operating Revenues (Annex 1)
Subtotal Inventories	1
Total Current Assets	0,75	1
Properties Plant And Equipment	0,70	0,55	1
Suppliers	0,92	0,67	0,68	1
Operating Revenues	0,83	0,71	0,88	0,82	1

Source: The autors.

It can be seen that there is a high correlation of SUBTOTAL OF INVENTORY with suppliers (0.92), with OPERATING REVENUES (0.83); PROPERTY PLANT AND EQUIPMENT with OPERATING REVENUES (0.88) and SUPPLIERS with OPERATING REVENUES (0.82), on the other hand, the input variable with less correlation with output variables is PROPERTY PLANT AND EQUIPMENT. What evidence the relevance and correspondence between the selected variables.

It is important to emphasize that there is a high correlation between the internal variables of the organizations with the generation of operational income. This is consistent with the fact that the processes of standardization BASC, have as intentionality, the generation of efficiency and operational effectiveness, which requires a series of domestic conditions and availability of current assets, property plant and equipment; and resources available for the improvement of the logistical processes of organizations where it's deployed.

After evaluating the efficiency of the 42 companies certified with BASC in Cali, the CCR-O efficiency scores for each organization were obtained, as shown in Table 3. It is important to remember that a DMU is efficient if the score of efficiency is equal to 1 and has no gaps (the clearance in all the variables is equal to 0), in this case of study all the DMU's whose score of efficiency is one (1) did not show gaps in its variables, therefore to determine if a company is efficient, it is enough to observe that the efficiency score is equal to one (1). It was found that 5 of 42 companies are efficient, this leads to see that 11% of the total number of companies assessed are efficient.

Table 3

No.	DMU	Score	1/Score	No.	DMU	Score	1/Score
1	Comestibles Aldor S.A.	0,22	4,53	22	Cadbury Adams Colombia S.A.	0,20	5,04
2	Ocupar Temporales S.A.	1	1	23	Transportes Centro Valle Ltda.	0,30	3,35
3	Coral Vision Ltda. Sociedad de Intermediación Aduanera	0,14	7,13	24	Transportes Rodríguez - Gonzalo	0,17	6,06
4	Sociedad de Intermediación Aduanera S.A.	0,12	7,8	25	Industrias del Maíz S.A. Corn Products Andina	0,26	3,89
5	Adhesivos Internacionales S.A.S.	0,14	6,7	26	Eternit Pacífico S.A.	0,16	6,06
6	Agraf Industrial S.A.	0,31	3,16	27	Colombina S.A.	0,29	3,49
7	Acción del Cauca S.A.	1	1	28	Laboratorios Recamier Ltda.	0,14	7,38
8	Globalog S. A.	0,31	3,14	29	Plásticos Especiales S.A.	0,14	6,94
9	Cristar S.A.S.	0,22	4,38	30	Industria de Aluminio India Ltda.	0,15	6,57
10	Grupo Empresarial Apparel Solutions Ltda.	1	1	31	Acción S.A.	1	1
11	Colombiana del Cauca S.A.	0,93	1,07	32	Agecolda S. A.	0,25	4,07
12	Compañía Internacional de Alimentos S. A.S.	0,49	2,02	33	Empresa Andina de Herramientas S. A. S	0,18	5,53
13	Genfar S.A.	0,15	6,31	34	Protécnica Ingeniería S.A.	0,16	6,41
14	Centro de Mecanizados del Cauca S.A.	0,1	9,25	35	Productos Yupi Limitada	0,37	2,72
15	El Dorado Air Cargo S. A. S.	0,07	12,78	36	Vallecilla B Vallecilla M & Cía. S.C.A. Carval De Colombia	0,12	8,06
16	Bridgestone Firestone Colombiana S.A.S.	0,48	2,05	37	Carvajal Internacional S. A.	1	1
17	Ups Scs Colombia Ltda.	0,49	2,02	38	Ingenio del Cauca S A	0,33	3,02
18	Carvajal S.A.	3,00E-02	29,08	39	Ingenio Providencia S.A.	0,59	1,70
19	Laboratorios Baxter S.A.	0,13	7,52	40	Harinera del Valle S.A.	0,11	9,33
20	Cartón de Colombia S.A.	0,21	4,65	41	Ingenio Pichichi S.A.	0,36	2,80
21	Colgate Palmolive Compañía	0,1	9,70	42	Riopaila Industrial S.A.	0,26	3,86

Source: The autors.

To the results of efficiency of the model used there was a classification in efficient enterprises (efficiency = 1 and zero slack), companies with high efficiency (1 > efficiency =0.80), companies with average efficiency (0.80 > efficiency =0.70) and companies with low efficiency (efficiency <0.70).

According to this classification Table 4 was built.

Table 4

Source: The autors.

For each inefficient Company, DEA suggests the combination of inputs and outputs that are necessary to achieve efficiency (projections of the inefficient DMU on the efficient frontier), in the case of the output variables, for an efficient DMU, the magnitude of these should improve (increase). The magnitude of the increase in the magnitude of each output variable for each company is presented in Table 5.

Table 5

No.	DMU	Score	Increase In Operating Revenues
1	Comestibles Aldor S.A.	0,22	654126542
3	Coral Visión Ltda. Sociedad de Intermediación Aduanera	0,14	21785393
4	Sociedad de Intermediación Aduanera S.A.	0,13	13421919
5	Adhesivos Internacionales S.A.S.	0,15	78603562
6	Agraf Industrial S.A.	0,32	59893312
8	Globalog S.A.	0,32	46393477
9	Cristar S.A.S.	0,23	603355680
11	Colombina del Cauca S.A.	0,93	216061055
12	Compañía Internacional de Alimentos S.A.S.	0,50	171447569
13	Genfar S.A.	0,16	1378975007
14	Centro de Mecanizados del Cauca S.A.	0,11	226521870
15	El Dorado Air Cargo S. A. S.	0,08	15298622
16	Bridgestone Firestone Colombiana S.A.S.	0,49	227348114
17	Ups Scs Colombia Ltda.	0,50	129225103
18	Carvajal S.A.	0,03	2811178790
19	Laboratorios Baxter S.A.	0,13	4116087338
20	Cartón de Colombia S.A.	0,22	3462087225
21	Colgate Palmolive Compañía	0,10	2886451510
22	Cadbury Adams Colombia S.A.	0,20	1508569097
23	Transportes Centro Valle Ltda.	0,30	44520541
24	Transportes Rodríguez - Gonzalo	0,17	25481239
25	Industrias del Maíz S.A. Corn Products Andina	0,26	2000985700
26	Eternit Pacífico S.A.	0,16	339555124
27	Colombina S.A.	0,29	2376524462
28	Laboratorios Recamier Ltda.	0,14	693032147
29	Plásticos Especiales S.A.	0,14	580741997
30	Industria de Aluminio India Ltda.	0,15	77294489
32	Agecolda S.A.	0,25	2834769
33	Empresa Andina de Herramientas S.A.S	0,18	208242285
34	Protécnica Ingeniería S.A.	0,16	183290419
35	Productos Yupi Limitada	0,37	406056345
36	Vallecilla B Vallecilla M & Cia S.C.A. Carval De Colombia	0,12	627013051
38	Ingenio del Cauca S. A .	0,33	1857019676
39	Ingenio Providencia S.A.	0,59	772431596
40	Harinera del Valle S.A.	0,11	3371890866
41	Ingenio Pichichi S.A.	0,36	512953015
42	Riopaila Industrial S.A.	0,26	2608223207

Source: The autors.

It was considered only the outputs variables taking into account that the CCR - O model was used, and this model determines which outputs would be the ideal to optimize the efficiency of the DMU.

The company Grupo Empresarial Apparel Solutions LTDA. was used 30 times as a reference parameter for assessing other organizations. Followed by the companies Ocupar Temporales S.A. with 26, Acción del Cauca S.A. with 6, Carvajal Internacional S.A. with 2 and Acción S. A. with 1 organization as pair evaluators, for other companies under research.