## 3 Results: Verification of the Proposed Methodology
### Application Outputs by Industry
#### 3.2.4 Comparison of Companies by Industry  
In the analysis according to the industry criterion, the individual sectors were compared at the level of the overall readiness of internal logistics, which is shown graphically, including a description in Figure 16. The best-rated industry was automotive, which had a similar value to electrical engineering; however, this field was affected by a smaller sample of companies. We focused mainly on the fields of automotive and mechanical engineering, with the latter having a significantly lower readiness for internal logistics compared to automotive. Figure 16: Comparison of average values of dimensions according to industry. Figure 15: Number of occurrences of level values—electrical engineering. * **Comparison of average readiness levels** The average level of preparedness in the automotive sector was 2.59. If we look deeper into the lower parts of the internal logistics structure (subdimensions), the individual subdimensions were relatively balanced in a range between levels 2 and 3. The average level of preparedness in the mechanical engineering sector was 1.67. After a more detailed analysis of the lower parts of the internal logistics structure, it can be stated that almost all subdimensions were between levels 1 and 2. Across all five dimensions, automotive companies had a better average level of preparedness than mechanical engineering. This statement is shown graphically with figures and color-coded columns given by industry in Figure 17.  
* **Comparison of the total number of occurrences of level values** The industries were compared on the basis of a total number of occurrences of level values. Thirteen companies were evaluated in the automotive sector and 11 companies in the engineering sector. Frequencies were compared on the same basis while the number of enterprises was not the same (Figure 18). The field of engineering scored mainly at lower levels, especially at level 1, and then the number of occurrences decreased (red part). The automotive sector scored mainly at levels 2 and 3 (green bar). Interpolation of regression curves are shown for both sectors. Analyzing the output data from methodology verification of average values of the level of preparedness of both sectors, the engineering sector had a significantly lower value than the automotive sector after comparing the number of occurrences with a graphical representation of values with regression curves. Figure 17: Comparison of average values of dimensions in the automotive and mechanical engineering industries. Electronic processing of documents for a structured interview with subsequent analytical evaluation results. The benefit for business practice is the creation of a comprehensive independent evaluation tool in the form of a methodology, which is mainly a diagnostic method for determining the level of readiness of internal logistics processes in the company. The task is to analyze the current state and evaluate readiness. It is also appropriate that companies can use the assessment with this tool repeatedly. It is therefore possible to compare the results in a certain period by repeated evaluation. This is already individual to each company and due to the measures and implementation of new equipment. Another partial benefit of this tool is the evaluation proceeding from the lowest elements to the entire area, seeing the structure of internal logistics. The resulting evaluation also reveals the so-called narrow places. These are areas in which the assessment is at low levels. It is therefore possible to do a detailed analysis with the detection of the weakest points in any dimension and to identify the worst evaluation of a sub-area. These areas are the so-called factors that most affect the entire dimension. Therefore, in sub-areas where the level is low, it is possible to start and take measures that will subsequently increase the level.