###### Abstract
From a socio-technical perspective, it is acknowledged that the adoption of the emerging technologies of the Industry 4.0 need at least three complementary socio-technical dimensions: organization of work, human factors and external environment [21]. For implementing Industry 4.0 in a standardized way, one of the biggest challenges is how to turn data into valuable information that will facilitate decision making and how Industry 4.0 can be operationalized in manufacturing. With this goal, systems theory appears as a formal way to analyze this challenge as it is, mainly, focused on the interaction between the main components of the system, and considers organizations as whole and integrative entities [12]. Moreover, there is a need for research in terms of the analysis of the return on investment (ROI) of advanced technological innovations of Industry 4.0 in organizations [12]. The definition of a proper strategy to implement I4.0 technologies, and the opportunities in business models are two major trends that need to be further explored in new studies [15]. Furthermore, there is also a need to study the effect of Industry 4.0 related technologies on industrial performance; although there are studies at the industry-level, there is still a need to study how these technologies impact on industrial performance at the firm level [4]. Based on the literature, the main research gaps can be summarized as follows:  
1. Integration models of improvement strategies and Industry 4.0 technologies [7; 16];
2. Models and sequences for the successful implementation of Industry 4.0 technologies within manufacturing organizations [4; 15; 16];
3. Models for maturity assessment to standardize the introduction of Industry 4.0 technologies including the impact assessment after their implementation [4; 16];
4. Models for the evaluation of optimization alternatives under Industry 4.0 environments [4; 12; 16];
5. Quantification models for specific use case evaluation under Industry 4.0 environments [4; 12]. Based on the above-mentioned research gaps, as well as taking into account that some of these gaps have been analyzed for decades [12], the research that is to be performed acquires greater relevance and significance. Thus, the aim of the study is to tackle these challenges with a unique approach ranging from the generic perspective of the strategic integration of various methodological and technological optimizations to specific use cases through a model for continuous business transformation based on the current functional maturity level of the manufacturing organization. Currently due to the advent of the Industry 4.0 concept and digitizing initiatives, many managers and companies act as \"technology fans\", forgetting any other strategies and methods and focusing only on developing and implementing new technologies. As a result, they have initiated and implemented Industry 4.0 related technological projects without considering a \"360\" evaluation, therefore lacking a real need and purpose and not contributing more than the implementation of a \"interesting technological gadget or system\" and incurring a waste of different company resources, such as time, money, etc. Thus, the research aims to develop a model for the assessment attending to real organizational needs and based on the main areas and factors for each manufacturing function, as well as on market that enables continuous business transformation that are aligned with the required current and future manufacturing organizational capabilities. Furthermore, the conceptual model provides also a description of production areas and factors to be assessed to determine the current maturity level of organizational capabilities. Even with a business transformation model and areas and factors to identify capability gaps, practitioners are often confused with regard of how to integrate improvement strategies and new technologies, as well as how to evaluate their convenience.