## 4 Results
### Results of Expert Interviews
#### 4.2.1 Approach to Industry 4.0  
The surveyed companies had opinions on what Industry 4.0 meant to them:  
\"An information revolution in the industry.\" (V1 interview, 2017)  
\begin{table}
\begin{tabular}{c c c c} \hline  & **CPS** & **Big Data** & **CPPS** \\ \hline
**Q1** & 15.624 *** & 5.931 & 10.552 *** \\
**Q2** & 13.854 *** & 5.311 & 7.875 * \\
**Q3** & 9.092 * & 5.244 & 6.729 \\
**Q4** & 4.211 & 4.814 & 5.547 \\
**Q5** & 10.685 ** & 1.611 & 9.568 * \\
**Q6** & 9.286 * & 2.289 & 5.443 \\
**Q7** & 13.333 *** & 5.932 & 6.446 * \\ \hline \end{tabular} Source: Author’s own research, 2017. Note: \(N=43\), * \(p<0.1\); ** \(p<0.05\); *** \(p<0.01\).  
\end{table}
Table 4: Utility of IoT tools and solutions (results of Pearson’s \(\chi^{2}\) tests).  
\"To use and interpret the enormous amount of data, and use it to predict the future. This is the secret of success.\" (V2 interview, 2017)  
\"Industry 4.0 Data and Behavior. Everyone gets all the relevant information, enabling them to react and decide on it in different ways.\" (V3 interview, 2017)  
\"Linking to a smarter network that encompasses the industry\" (V4 Interview)  
The companies interviewed have differing degrees of affinity to Industry 4.0. One company makes the necessary improvements but does not move forward, does no piloting, and takes advantage of what is afforded by cheap and easily accessible technology. There are two companies where the Hungarian factories in the group of companies are pilot factories creating ideas, transformations and developments, and what works is transferred to other factories. These are local, stand-alone initiatives, and it can be stated that a lot depends on dynamic leadership. The innovative activity of one company has led to the development of digitalization before the launch of the German High Tech Strategy.  
Among the companies asked, we identified three behavioral patterns. In one approach progress can be achieved by taking only the \"low-hanging fruit\"; alternatively, there can be intense internal motivation, which can even help a subsidiary of an international group of companies; thirdly, the company can socialize into an innovative environment where a high degree of innovation is expected, in which all members of the group participate and the results are applied globally.  
There was a question in the interview about what phases a company goes through to actually exploit Industry 4.0's potential.  
The first step is that the companies start collecting data. They install the technological tools or software that can capture the desired observations and collect data: \"performance immediately increases by 30% if we start observing a process by cameras and sensors\" (V1 interview).  
The _second step_ is to transform this data into decision support information: \"we need to build up a serious IT infrastructure to store and handle the data produced in the manufacturing processes\" (V2 interview). This is a critical point; in many places there is lack of capacity for data analysis and interpretation, so there is a lack of professional skills in this area. It is not only necessary to run the analysis; other tasks--from the preliminary cleaning of the database, through to the knowledge of algorithms, the recognition of errors and distorting effects, to the transparent presentation of the results--are important.  
The _third level_ is the use of the results gained from data: \"we have specialists at group level who develop machine connectivity and big data analytics software\" (V2 interview). To do this, well-trained personnel are needed who can re-program software and hardware, and write new software or algorithms, and who are able to further develop the systems. There is also a need for decision-making algorithms and decision-makers who can build this information into their decisions and achieve goals using real-time data access and analysis (V1 and V2 interviews).