Industry 4.0 Framework Based on Organizational Diagnostics and Plan–Do–Check–Act Cycle for the Saudi Arabian Cement Sector

Abstract

Industry 4.0 (I4.0) is an extension to the three stages of industry that reshapes it into a combination of physical and digital worlds. The I4.0 paradigm shift coupled with emerging technologies, such as artificial intelligence (AI), robotics, the internet of things (IoT), autonomous vehicles, and digital twins (DTs), have brought and will continue to bring profound changes that impact entire systems across all industries. Despite I4.0’s many advantages, it also brings a host of problems and disruptions. These problems and disruptions must be identified to maximize its potential. Saudi Arabia is undergoing significant transformation as it has initiated several plans to develop the industrial sector and enhance its contribution to the national economy. Despite Saudi Arabia’s 2030 vision, the industrial sector has still not fully grasped the breadth and depth of the new revolution due to its novelty. This is particularly true in the cement industry, one of the most vital industries in the region. Due to its many unique systemic complexities, the cement industry has faced numerous challenges due to the lack of a comprehensive framework for mitigating disruptions and leveraging I4.0 benefits. Accordingly, the paper conducts an exploratory study on I4.0 for Saudi Arabian cement companies. Therefore, this paper provides an overview of I4.0 for Saudi Arabia’s cement companies. The paper analyzes key findings and proposes a plan–do–check–act (PDCA) framework for I4.0 implementation based on a system thinking approach to guide cement companies to strategically embrace the new phenomenon and maximize their key performance indicators.

1. Introduction

I4.0 was realized and originated at Hannover Fair in 2011 as a strategic initiative to enable the transformation of industrial systems through digitization and emergent technologies [1]. The arrival of this revolution is rapidly changing the landscape of industrial and manufacturing systems, creating a world in which both digital and physical systems collaborate with each other in a flexible manner. In the era of I4.0, several technologies have become the center of this transformation. Cyber-physical systems (CPSs), IoT, cloud computing, and smart factories (SFs) are the landmarks that drive the new revolution [2]. These new technologies are becoming realities in newly constructed factories, facilitating the development of digital innovation ecosystems to ensure long-term resilience in a rapidly changing geopolitical and economic context [3].

The arrival of I4.0 transforms the industry in terms of efficiency, productivity, and flexibility. This puts manufacturing companies at the forefront of technological adaption to enhance and optimize their processes, considering its best practices. It creates more innovative ways of conducting business and generates more value by providing collaborative communication from the top management level to the field level. For example, I4.0 advantages include accelerating economic growth rates, reducing costs, improving quality, and providing broader customer service.

The adoption of I4.0, however, poses many challenges and uncertainties for organizations around the world. It is mainly due to a lack of talent and capabilities, poor alignment of digital strategies, and, more importantly, a lack of a step-by-step framework that drives implementation from the big picture.

I4.0’s fundamental changes affect the economic and social systems of many developed and emerging nations worldwide. The simple paradigm for the industrial sector has changed on multiple levels; the network of stakeholders has grown, the variety of communication channels has increased, and the boundaries of organizational systems have become less distinct, making management and control orders of magnitude more difficult. Due to these factors, Saudi Arabia is seeking efficient models to accommodate I4.0 integration within their existing organizational structures [4].

Saudi Arabia’s cement industry, one of the country’s most thriving industrial sectors, stands at the crossroads of this revolution. Furthermore, the sector is negatively impacted by some challenges, such as high transportation costs, the waste of energy, and the increased capacity that has prompted many prominent players to demolish and upgrade their factories and production lines. Such bottlenecks and incidents impeded Saudi cement companies’ search for more efficient and structured methods to achieve a long-term competitive advantage in the era of I4.0. Due to the sector’s expansion, steady growth, unique system complexity, and demands for flexibility, quality, and technology, the sector is encouraged to be efficient by adopting new I4.0 technologies and solutions to deal with such challenges on an organizational level. Making the cement production process and plant operations more predictive and self-sufficient could very well be the answer to these problems. The cement industry is expected to undergo a paradigm shift in order to make it intelligent and sustainable, which is something that can only take place through digitization in the direction of I4.0. All of these challenges make the need for an I4.0 framework for the cement industry clear—a framework that leads the cement industry towards a fruitful transformation to take advantage of I4.0.

The cement industry is constantly reinventing itself by improving energy efficiency, resource conservation, and commitment to sustainable practices. The same patterns of industrial restructuring are becoming increasingly apparent now; nevertheless, there is some solace in the fact that the obstacles may be overcome and the goals may be accomplished if the sector commits itself wholeheartedly to the path of I4.0 maturity, and yet, few cement manufacturers have implemented I4.0 innovations in a systematic manner. Although empirical studies on I4.0 applications in the sector are provided, there is an abundance of a holistic framework to implement I4.0 in a cement ecosystem, from the organizational level to the operational level. This new fact poses a new challenge to the cement sector, mainly because the lack of a holistic framework could make it difficult for the cement companies to respond to the I4.0 system disruptions, which is the main motivation of this paper. Therefore, this study is aimed at developing a holistic I4.0 framework based on organizational diagnostics and the continuous improvement PDCA cycle.

Cement manufacturers should implement I4.0 solutions methodically. For this reason, unique characteristics are incorporated into the proposed model. Firstly, the framework needs to be holistic and consider the organizational system as a whole; in other words, it must be holistic and system-oriented. A second requirement is that it should be iterative, providing emerging cement organizations with action plans to move from their current state to their desired state. In addition, it should be understandable and not overly complex, enabling organizations with low maturity levels to use it. The main contribution of this study is to help cement companies recognize their readiness and strategically lead themselves to an effective transformation in terms of I4.0.

The remainder of the paper is structured as follows. In the first section, a background and introduction to I4.0 are presented. Then, a state-of-the-art literature review regarding the organization’s diagnostic models with an overview of I4.0 system disruptions is introduced to highlight the gaps and construct the theoretical framework of the proposed model. Section 3 discusses the research phases and methodology, including data collection procedures, sample size demographic information, and the target population. In Section 4, questionnaire data and results analysis are presented, followed by a discussion of the findings in the same section. Section 5 describes the proposed I4.0 framework. This paper’s conclusion is discussed in the final section.

2. Theoretical Framework

2.1. I4.0 System Disruptions

I4.0 will transform the industrial and manufacturing landscape, bringing new ways to increase efficiency and engagement. However, technology is a double-edged sword that will also bring rising expectations and, on the other hand, more security challenges. Technological breakthroughs are also responsible for business model disruption in established organizations; they will change the way they operate with horizontal and vertical integration across the value chain and real-time optimized networks. The scale and scope of the I4.0 revolution will make humankind hardly differentiate between artificial and natural. [5]. The speed of innovation in terms of both its development and diffusion is faster than ever, having a disruptive effect on many organizational aspects such as organizational structures, supply chains, production processes, dominant technologies, talent, and the employment market. In order to develop a holistic framework, it is important to have a system view that covers multiple factors in an organization. For this reason, this section will describe and analyze the potential system disruptions of I4.0 on different organizational variables to create the “system view” of the proposed framework.

The customer experience and expectations are two of the main sources of disruption. I4.0 technologies will create entirely new ways of meeting existing requirements that will significantly disrupt existing value chains [6]. The operating models will be transformed into entirely all-digital models that require companies to respond in real time, wherever they are or their customers or clients may be.

An additional significant I4.0 organizational system disruption is likely to be caused by a single force: empowerment. Today’s discussion concentrates largely on the role of technologies in creating or destroying jobs, as well as the impact of I4.0 on professional skills and competencies. The destruction effect occurs when technology-driven disruption and automation supplant labor with capital, causing workers to lose their jobs or reassign their talents elsewhere. On the other hand, organizations must recognize the opportunities for job creation that I4.0 presents. In the era of I4.0, many categories of work have already been automated, particularly those involving repetitive and precise manual labor activities. In the not-too-distant future, an increasing number of occupations, including financial analysis, consultation, and decision-making roles, will be fully or partially automated. Innovations and technologies brought about by I4.0 tend to increase the number of labor-free products.

In addition, I4.0 technologies will bring new solutions for organizations to predict their performance, enabling the establishment of new business models. For instance, an ERP software can be deployed in collaboration with I4.0 technologies to have a real-time flow of information between enterprise-level and shop floor systems [7]. This collaboration will make it easy for managers to have timely information for optimum decision-making. A cement production company could install an ERP system that gives them instantaneous visibility on production, quality measures, overall throughput, machine uptime and downtime, and other important operational variables to achieve optimum and effective operations. Moreover, the amount of data needed to process it has increased exponentially as a result of the fast growth of IoT-based applications and the advent of 5G networks [8].

I4.0 will also change the style of leadership in organizations. The increased real-time-oriented control structures and the changes in the nature of work and its content will change the operative and management routines. Therefore, new leadership styles should be adopted [9]. Another significant challenge for organizations is not only to find or implement the right technology, because technology is already there and readily available, but the lack of digital culture and skills needed in organizations requires radically different generation of workers [10]. Companies need to develop a robust digital culture and ensure that clear leadership drives their I4.0 vision and transformation strategies. Figure 1 summarizes the I4.0 system disruptions.

All these different system impacts and disruptions require organizations to rethink their operating models. Strategic planning and execution in the I4.0 era are being challenged by the need to operate faster and with greater agility. Successful organizations will increasingly shift from hierarchical structures to more networked and collaborative models. Motivation will be increasingly intrinsic, driven by the collaborative desire of employees and management for mastery, independence, and meaning.

2.2. Literature Review on Organizational Diagnostics and I4.0 Maturity Models

The disruptive I4.0 technology has left organizational leaders challenged in terms of adaptation to its new norms. Nonetheless, the renewed attention to new customer expectations and requirements, such as innovation, speed and quality of services, and efficiency of operations, has forced leaders to rethink, redesign, and reimagine their business models and strategies to remain competitive. These organizational disruptions support the use of diagnostic models or frameworks for assessing organizational effectiveness, change, and renewal as a building block for designing the proposed I4.0 framework, which has the ultimate goal of being holistic, comprehensive, and iterative. The purpose of this section is to examine several organizational diagnostic models that have been conceptualized in the literature to determine the main dimensions of the proposed framework.

The dimensions of these organizational diagnostic models were analyzed considering the context of each model and the description of the dimensions, as well as the assessment items available for analysis. The purpose of this analysis was to determine the main dimensions of the proposed model, dimensions that were chosen to achieve the desired vision of designing a comprehensive model with systemic thinking.

Table 1. Organizational diagnostic models.

Model	Focus and Main Dimensions
Leavitt’s Model	Strategic tool used to understand what is needed for change in both corporate and personal environments. Considers the driving forces and the restraining forces as a source of management challenge [11].
Weisbord’s Six-Box Model	According to this model, the success factors required for a successful transformation are structure, tasks, people, and technology [12].
Nadler and Tushman’s Congruence Model	This model has an important diagnosis step, which is determining the “gap” current organization status and what it ought to be. Its main dimensions are: purposes, structure, rewards, leadership, helpful mechanisms, and relationships [13].
McKinsey 7S Framework	According to this model, an organization will only be successful if these components work and align with each other: culture, work, people, and structure [14].
Galbraith’s Star Model	The model is to depict how effectiveness can be achieved in an organization through the interactions of seven key elements—structure, strategy, skill, system, shared values, style, and staff [15].
Nelson and Burns’ High-Performance Programming	This model includes five design policies as follows: strategy, structure, and processes, which have to do with the flow of information; rewards and reward systems, which influence the motivation of people to perform and address organizational goals; and lastly, people [16].
Falletta’s Organizational Intelligence Model	This model offers the organization an assessment tool to determine the kind of an organization at four levels: reactive, responsive, proactive, and high-performing [17].
Leavitt’s Model	This is an open systems model depicting 11 variables or factors: environmental inputs; leadership; strategy; culture; structure and decision rights; information and technology; direct manager; measures and rewards; growth and development; employee engagement; and performance outputs [18].

below summarizes the organizational diagnostic models found in the literature.

A selection of different I4.0 maturity and industrial assessment models were also studied and analyzed. These models are presented to provide a comprehensive analysis and to determine common I4.0 dimensions. On the other hand, the analysis will discuss how these models tackle the concept of an organizational system as a whole.

In [19], the authors provide a model containing 62 maturity items in a group of nine dimensions: strategy, leadership, customers, products, operations culture, people, governance, and technology. While the model provides a solid point of reference for manufacturing companies to assess and improve their I4.0 maturity, the authors acknowledge the limitations and suggest potential further developments such as company-specific target states, improved accuracy of maturity items, and defining strategic steps to reach higher maturity levels.

The paper of [20] introduced a multi-dimensional indicator framework that can be used to assess the status quo of organizations in terms of I4.0 readiness. The model is focused a practical diagnosis and prognosis of systems and processes for its future adoption.

In [21], the paper delves into I4.0 technologies and their adoption patterns in manufacturing firms. The study proposes a framework dividing the technologies into front-end (smart manufacturing, smart products, smart supply chain, and smart working) and base (IoT, cloud services, big data, and analytics). However, the study has limitations, and the authors call for future research to study the impact of these technologies on industrial performance. Despite this, the study provides an empirical base for comprehending the adoption patterns of I4.0 technologies and their interrelation, which is one of the gaps of this research.

Although the models from the reviewed literature provided the best practices in terms of maturity and readiness assessments, they still lack the step-by-step procedure to guide organizations towards successful I4.0 implementation. The iterative structure is a concept used as a methodology to guide organizations towards continuous improvement. It is important to think of I4.0 evolution as a continuous improvement process rather than an eruptive one. Hence, the adaptation process needs to be undertaken with this mentality. Therefore, the proposed model is based on the methodical approach of the PDCA iterative cycle to shape this process in an adequate way. The PDCA is selected as a philosophy for the proposed model due to the fact that it is a continuous improvement tool that is widely used in the market [22]. It begins with a small assessment of the organizational systems and eventually progresses to the desired result of an improvement [23]. The PDCA cycle can provide a checklist with four stages that one must go through to traverse from “problem faced” to “problem solved”. The proposed model is derived from the PDCA cycle in the sense that it should cover the span from the determination of the organization’s objectives on the strategic management level up to the I4.0 implementation, supported by the assessment of the chosen dimensions. When an organization uses the proposed model, it should start by diagnosing the dimensions; the results of this initial assessment will determine their status regarding their progress towards I4.0. Then, they must go through the PDCA stages, which will lead them to the desired I4.0 readiness.

2.3. Cement Sector within I4.0

Saudi Arabia’s interest in and support for the industrial sector plays a key role in achieving the strategic and economic goals to put the country on the path of economic growth as a part of its Vision 2030. The efforts to support the industrial sector include several basic dimensions, such as providing the necessary infrastructure for different industrial cities, industrial development funds and programs, and other industrial incentives. In addition, Saudi Arabia has established a strategic partnership with the World Economic Forum (WEF) to develop mechanisms and applications of I4.0. The number of facilities benefiting from the stimuli of I4.0 in Saudi Arabia is 10, with an aim to increase it to 43 by 2025. Saudi Arabia is also aiming to increase technical infrastructure readiness by 50% through digitally enabled I4.0 projects in mining, industry, logistics, and energy through a USD 453 billion fund [24].

The Saudi Arabia’s cement sector has been a critical player in developing the industrial infrastructure in the country. The annual production capacity of this sector is around 72.4 million tons, making Saudi Arabia the highest among other Gulf Cooperation Council (GCC) countries [25]. The study provides direction for inefficient companies to become efficient by contracting their inputs, ultimately increasing their potential for becoming significant players on the efficiency frontier. Despite some positive findings, the overall efficiency level remains at a depressing level, highlighting the importance of this study in the cement sector in Saudi Arabia.

In recent years, the sector has been negatively affected by some challenges, such as the lack of an alternate source of energy, high transportation costs, the underutilization of capacity, etc. These challenges hampered the Saudi cement companies’ path to achieving a sustainable competitive advantage over other giant players in the region.

The study presented in [26] focuses on the methodical approach to implementing various components of digital solutions. It also investigates the transformation that is occurring within many of the existing on-premises solutions, such as control systems and machine control, as well as the newly developed cloud-based solutions, in order to support increased cement plant asset availability and performance. In addition to this, it is the primary force behind the connected cement plant ecosystem, which consists of connected assets, connected insights, connected operations, connected people, connected processes, and connected innovation. Nevertheless, it does not provide a framework for the step-by-step implementation of low cement plant I4.0 maturity requirements.

The study [27] provides a road map for the implementation of a data-driven thermal energy management concept that maximizes the use of alternative fuels and raw materials for sustainable cement production. The thermal process of the cement industry faces numerous obstacles as a result of environmental and economic demands from all parties involved. Utilizing waste materials as alternative fuels and raw materials to enhance operational excellence and sustainable cement production is the most effective strategy for addressing these challenges. This can be accomplished by implementing cutting-edge technology, innovations in process equipment, and data-driven I4.0 technologies. Cement plant real-time and historical data are utilized by I4.0 instruments. The plant’s data must be securely transmitted over the network, stored in the cloud, and intelligently analyzed by algorithms based on artificial intelligence and machine learning principles. These technologies will serve as the foundation for tools that will provide efficient prediction and process optimization of the manufacturing process to achieve an overall improvement in cement manufacturing efficiency and sustainability.

Digitization and AI are increasingly being used across various industries, and early adopters often gain a competitive edge. The cement industry is one that could benefit from the widespread adoption of these technologies, as the industry faces several challenges, including rising energy consumption, inefficient use of raw materials, logistical problems, emissions, and overall process complexity. While some companies are already adopting these technologies, a significant research gap still exists, and leaders should encourage their entire organization to adopt these technologies to achieve a mindset change that promotes rethinking the current way of working. The cement and aggregate industry is crucial to the growth and development of modern civilization, and it is time for this industry to embrace digital solutions to enhance productivity, cost-effectiveness, and more efficient operation.

The article in [28] emphasizes the importance of implementing I4.0 solutions in the cement manufacturing industry. By integrating digital technologies like robotics, artificial intelligence, and the IoT, the process can become more efficient, productive, and cost-effective. One major benefit of I4.0 solutions is improving internal collaboration among staff. This enables faster problem solving and improved decision making by utilizing support functions and experts to manage real-time deviations. To implement these solutions, a structured approach is necessary. This includes conducting a digital health check to understand the current situation and setting a vision for what the company wants to achieve.

The cement industry is recognizing the advantages of process control and automation in achieving trouble-free continuous operation, leading to improved productivity and efficiency. With the use of automation, optimal operation in mining can lead to a longer mine life and consistent desired cement quality while also ensuring human and equipment safety, monitoring equipment health, and implementing preventive maintenance in the manufacturing facility. Upgraded automation has helped plants achieve continuous improvement targets and sustainability goals, as proven by different instances.

The case study of [29] has shown that automation can solve and prevent problems, leading to higher plant capacity, improved product quality, plant availability, and decreased consumption of utilities and consumables. Automation is critical to optimizing production and quality control in cement manufacturing, leading to significant advantages for plants that adopt this technology.

Traditional construction methods that require cement products have a significant environmental impact, with the use of reinforced concrete being a primary driver. As such, the industry faces an increasing responsibility to tackle climate neutrality. Digital fabrication with concrete (DFC) has emerged as a promising method to reduce the environmental impact while being compatible with the multifaceted requirements of construction work. However, DFC has yet to penetrate the mass construction market, which is essential to making a significant difference towards improving the industry’s environmental impact.

The authors of [30] propose a value-driven ideation process to identify relevant mass-market levers of DFC in the construction industry. They acknowledge the current limitations of DFC in complying with fundamental design code requirements regarding structural safety and durability. Still, they present a methodology that includes assessing traditional construction and digital fabrication on a value-driven basis, identifying and summarizing their inherent strengths and challenges, and proposing a value-driven ideation process to identify relevant mass-market levers of digital fabrication in the construction industry. The article provides two exemplary applications of how traditional construction and digital fabrication processes can be combined to tackle the persistent environmental sustainability challenges facing the industry.

Embracing I4.0 solutions is crucial for cement manufacturers to stay competitive in the industry. By doing so, they can improve efficiency, reduce costs, and enhance product quality. However, a structured approach and strong holistic framework are necessary for successful implementation, and that is what drives the motivation for the proposed framework.

The preceding literature review provides a theoretical framework that highlights evidence about I4.0 system disruptions in organizations. This leads to the hypothesis that in order to implement I4.0 in an organization, a holistic I4.0 framework with organizational aspects and dimensions is needed so they can be ready to embrace the challenges created by the I4.0 paradigm shift. Some literature gaps can also be identified in the current scientific debate surrounding I4.0. First, attention is mainly paid to technology implementation and only partially to its impacts on organizational systems. Secondly, there is an abundance of step-by-step frameworks that guide the organization to a meaningful I4.0 implementation. Therefore, this model will have an iterative feature that is based on the PDCA cycle to shape this process in an adequate way. This highlights the main contribution of this research to the literature.

3. Materials and Methods

The results from the previous section will establish a conceptual framework that guides the exploratory phase of the study and contribute to the design of the proposed framework. The diagram below Figure 2 illustrates the research phases.

3.1. Data Collection Procedures

For data acquisition, a structured questionnaire was developed and utilized. Several iterations of revisions were made to the questions based on the feedback of academic and industry experts on I4.0. The questionnaire encompassed a variety of topics, such as the level of awareness regarding I4.0, aspects of relevance to the company, IT infrastructures, potential benefits for the business, key performance indicators (KPIs), investments, and future plans and strategies for implementing I4.0. It is worth noting that these questions were linked to dimensions in the proposed model. In the sense that the questions are intended to give an idea of the companies’ progress at the selected dimensions of the proposed model. For example, a series of questions pertaining to investments and strategic support processes will give insights into what measures should be implemented in order to raise the maturity of the strategy dimension.

Internal consistency is a prevalent concern in survey studies before data analysis is carried out. Cronbach’s alpha coefficient is used to assess internal consistency; a score greater than 0.7 denotes the survey element’s homogeneity and consistency with research objectives. The Cronbach’s alpha for the survey was 0.9287.

Semi-structured interviews are also used to understand attitudes, opinions, and decisions. As a result, the questionnaire provides a valuable opportunity for further exploration and discussion of areas of significant interest that were not considered earlier. These areas include regional issues and localization in the era of I4.0. Elaborations on the impact of I4.0 on the cement sector are further discussed. Companies also allow access to important data through annual reports and financial statements, which indirectly opens the way for observation and data collection.

3.2. Sample Profile of the Study

The sample was selected using a random stratified sampling approach based on the number of workers in cement companies in the Saudi Arabia cement sector, which is 10,591 employees within 17 local cement companies, with 95% confidence and a 5% margin of error, and assuming a population proportion $\stackrel{\wedge }{\mathrm{p}}$ is 50% as a conservative value. The Z score of the 95% confidence interval is 1.96. Therefore, the sample size is 371. The selected case companies are shown in

Table 2. Case companies.

No	Company	Headcount
1	A	1670
2	B	800
3	C	686
4	D	268
5	E	910
6	F	650
7	G	123
8	H	208
9	I	550
10	J	758
11	K	520
13	L	361
14	M	498
15	N	95
16	O	123
17	P	410

. The companies’ names were replaced by incremental alphabetical letters to protect their confidentiality.

A web-based questionnaire was distributed to 371 practitioners in the cement sector with multiple job titles such as CEOs, directors, engineers, technicians, and job functions as follows: finance, IT, operations, planning, engineering, production, and management. It is, therefore, justified to use a sampling technique because the population is heterogeneous and includes a diversity of specializations, qualifications, and job descriptions. At this point, the questionnaire is answered directly by the respondents. A total of 261 responses were received, which represents an acceptable response rate of 70.35%, with 13 of them excluded because they were unanalyzable.

Table 3. Sample size characteristics.

	Frequency (%)
Job functions
Management	3.5
Finance	6.29
Engineering	18.6
Operations	15.01
IT	25.07
Other	31.53
Gander
Male	80.05
Female	19.95

shows the sample size characteristics.

4. Results and Analysis

4.1. Proposed Model Diminisnions

Our next step will be to discuss the details of the dimensions that were selected separately and explain why each dimension was selected within our model.

• D1—Environmental inputs: Refers to the ability of an organization to understand the outside conditions and situations that affect it. This includes customer needs, the economy, policies, and their competitive position. The arrival of I4.0 will surely influence these inputs and create more organizational prerequisites for adopting I4.0 technologies. Organizations must manage multiple internal and external factors to increase business value and establish a sustainable competitive advantage in order to achieve I4.0 alignment within the organization context. Specific factors include horizontal, vertical, and digital integration, as well as competitive position analysis. Organizational performance in this evolving era necessitates the management of teams of highly specialized technical specialists. In addition, it requires employees trained to operate using I4.0 enablers, with profiles that do not yet exist [31].
• D2—Strategy: This dimension concerns the extent to which strategic measures are adopted to achieve objectives for improvement and innovation initiatives to increase competitive advantage. Organizations should map out an I4.0 strategy with measurable targets to close the gap in their I4.0 readiness. Organizations use strategic planning to define their direction and guide resource allocation decisions [32]. Strategic planning provides an organization with direction, defines measurable objectives, and guides day-to-day decisions. In addition, strategic planning is concerned with the definition of changes that may be influenced by fluctuating market conditions, competitor activity, and technological advancement—elements typically constituting I4.0. Moreover, alignment must be achieved at both enterprise and departmental levels across four domains of decision-making choices, namely digital strategy execution, technology innovation potential, competitive business models, and the level of investments and support for organizations to manage all the multiple internal and external factors described in D1.
• D3—Leadership: Leadership at the senior level must establish a forward-looking, innovative, and technologically advanced organizational culture. Faced with I4.0, leadership has to adapt to the changes; the guidance of teams and organizations toward impactful transformations demands leadership that supports innovative visions. Leadership must adapt to I4.0 to guide teams and organizations toward meaningful transformations. This requires strategic ways to realize new ambitions [33]. Responsive leadership has a special role in fostering an organization’s change in the perspective of a learning and innovation-oriented culture, learning from and managing various situations, while supporting the transition to I4.0. Leader 4.0, however, should not be mistaken for a technological leader; in fact, what transforms a leader into a 4.0 is not just the application of technologies, but also the capacity to foster a novel culture focusing on people, technologies, and innovation while being cognizant of how technologies would affect people and the business line of the organization. Digital leadership should be quick, cross-hierarchical, and team-oriented to digitize operations inside an organization and business ecosystem. A digital leader must implement many business strategies and models, including IT strategies, more adaptable and flexible enterprise platforms, an innovative mentality, skills, and workplaces, to face the challenges of digital transformation. Additionally, leadership needs to exhibit a few qualities to deal with disruptive developments that are continually evolving, including being connected, responsive, collaborative, and network-experienced, as well as encouraging learning toward innovation [34].
• D4—Culture: Refers to the underlying values, beliefs, and norms that drive the organizational behavior towards I4.0 implementation [35]. This is a critical dimension of our proposed model. This is because, since the proposed model will be applied in Saudi Arabia, it should consider cultural values and other problems related to the region. Regional markets have been significantly impacted by the current shift in trend toward digitization and the extensive application of digital transformation methodologies and strategies. Businesses must now join the I4.0 transformation bandwagon to survive globally. In terms of evolving technologies and ideas infiltrating the workplace, cultural acceptance and willingness to transition are the most significant factors. As the majority of a cement corporate employees in Saudi Arabia, particularly in the GCC countries, are predominantly male, cultural changes would impediment digital transformation. As workplace values and working conditions undergo numerous changes and modifications, passive resistance to new technologies is readily apparent. The digital environment of a company must promote and strengthen digital technology, culture, skills, and talent.
• D5—Information Technology (IT): Refers to the organization systems, IT infrastructure, and communication systems. The organization should facilitate and reinforce its systems and infrastructure to unlock more I4.0 capabilities.
• D6—Structures: Refers to how an organization is designed. There is no doubt that I4.0 design principles will affect an organization’s structure. For instance, the decentralization design principle demands many organizational roles and functional structure changes. The restructuring of facilities in light of I4.0 transformation requirements is very important whereas the main objective is to determine whether the existing administrative organization of the facility accomplishes the requirements of I4.0 or whether this requires a restructuring of the administrative apparatus. And by virtue of the fact that restructuring is a process that requires time, human, and material resources to implement it, this leads us to the need to conduct a study of the economic feasibility of this change, given that preparing a feasibility study reduces risks and increases confidence in the possibility of the restructuring project’s success. The feasibility study usually includes all the information and statistics that help decision makers decide whether to move forward with restructuring or leave the situation as it is, perhaps only re-engineering work procedures or creating digital teams within the organization chart.
• D7—Growth and development: This refers to the level of organization support to the growth projects such as employee skill development and enhancement, including development planning, training and learning, to achieve I4.0 strategic goals. Our capacity to reduce adverse effects on the environment and the economy as a whole will be considerably enhanced by I4.0. Consider carbon emissions—a primary type of undesirable externality. Until recently, the only way for green investing to be profitable was with substantial government subsidies. This is becoming increasingly rare. One of the key worldwide issues now is climate change, and rapid technology advancements in renewable energy, fuel efficiency, and energy storage make investments in these industries increasingly profitable, driving the Gross Domestic Product GDP growth. This dimension is particularly concerned with the extent to which the company exploits modern technologies for expansion and growth, and the extent to which there are plans for continuous development towards I4.0.
• D8—Engagement: This is for both the customer and employees. The organization should make an effort to meet their requirements and keep them loyal. I4.0 will unlock the potential for a lot of engagement possibilities that must be considered.
• D9—Performance outputs: This dimension covers an important aspect of the proposed model, which is the convergence between I4.0 and measurable outcomes and KPIs. The organization must determine the decision variables that give them the ability to achieve measured goals through I4.0 technologies.

Figure 3 shows the proposed model with selected dimensions. It can be noted that the model dimensions interact holistically in each PDCA cycle; this explains why the model dimensions are embedded within the PDCA cycle, which works iteratively to reach the desired output. The premise of the model is structured on the idea that even if we assess each dimension on its own, they interact with each other holistically within the cycle. Moreover, the model reflects the organization as an open system in the sense that it allows repeated cycles of input and output. At each iteration, the evaluation criteria will be based on these dimensions, which should be improved during each cycle in terms of maturity.

4.2. Survey Analysis and Findings

This analysis aims to comprehend the current readiness status of the cement industry for I4.0 from the perspective of the proposed model dimensions.

D2 and D3 dimensions will be assessed using the following aspects: investments in I4.0 projects, the alignment of digital strategies, the availability of strategic support procedures, and attempts to change business models in line with I4.0 requirements.

Figure 4 shows Saudi Arabia’s cement companies’ investments and spending on I4.0 projects. I4.0 projects have not yet received significant budgets from the companies, at least for now. This is due to multiple reasons.

• The companies have spent a lot of their budgets in the last 5 years updating or expanding their production lines. They have also replaced their old kilns and baghouse filters. This was during the emergence of I4.0. So, cement companies need several more years to invest again in future projects.
• The cement market is currently experiencing many fluctuations and changes. Some companies cannot spend money on new technologies now.
• Few companies have realized the benefits of the I4.0 implementation; as we can see in the figure, only approximately (30%) have realized they need to allocate a percentage of their budget for future projects related to the I4.0 implementation. Around (5%) have approved targets and objectives for future digital transformation projects that are I4.0-related.
• Under the current market conditions, top managers think that I4.0 is a big change, and spending money on the transformation right now is risky, especially since some companies have spent significant budgets on applying some basic new technologies to storage and laboratory testing operations recently. It is too early to bring in more technologies to reach total transformation.

Figure 5 illustrates the outcomes of the congruence between digital strategies and core business strategies. Participants were asked about any business and prospective plans and strategies related to I4.0 implementation within their respective organizations. Approximately (45%) of companies have yet to demonstrate the value creation potential of I4.0, while 35% are just beginning to recognize its value proposition. Approximately 20% of businesses have begun to identify the business benefits of I4.0. The results for “digital strategies” indicate the existence of any digitalization plans within the context of I4.0. (75%) of companies have little support from upper management for digital solutions or strategies related to I4.0, while (20%) are still analyzing and formulating new plans. The same holds true for digital policies and procedures. This is reflected in the amount of support for innovations, as only a limited number of businesses are encouraged to investigate and experiment with I4.0 implementations and solutions.

Individuals who connect on digital networks may replicate tangible world cultures or build new trains of cultural thought and practice relevant to digital networks. This phenomenon is called digital culture. It refers to the knowledge, beliefs, and practices of these individuals regarding digital tools. D4 is assessed in terms of the knowledge, awareness, and involvement of participants in the rapidly evolving transformation of working environments. This is within the context of I4.0 information technology implementation and application. To identify the level of knowledge of respondents in cement sector companies, they were asked to answer a five-point Likert scale based on the “level of knowledge” criteria. The level of knowledge was categorized as: (0 = no knowledge at all, 1 = limited knowledge, 2 = intermediate knowledge, 3 = excellent knowledge, 4 = deep knowledge, 5 = innovative knowledge). It is imperative to note here that innovative knowledge means that the respondent can generate additional knowledge and value-based innovation projects based on I4.0 best practices.

It is also a necessity to know and understand the changes brought about by this industrial revolution from a historical point of view. Through this process, companies will be able to identify the triggers and innovations that made I4.0 a reality. This understanding will help companies determine where they are now. Surprisingly, Figure 6 shows that around (27%) of the respondents are lacking in terms of defining I4.0. It also indicates that (36%) of them have limited knowledge of it, while (20%) of them have intermediate knowledge. Around (11%) of the respondents had good knowledge when asked about Industry 4.0. Only a small percentage of the respondents were distributed between the two categories “deep knowledge” and “innovative knowledge“. Regarding historical context, (35%) of the respondents have limited knowledge while (25%) have comprehensive knowledge and (3.3%) have a deep understanding of how I4.0 was actually triggered. (21%) of the participants lack knowledge about I4.0’s historical context and origins. However, (2.4%) believe they can generate and create meaningful and relevant knowledge in this regard.

Table 4. Statistical values of I4.0 knowledge evaluation.

I4.0 Knowledge Items	Average	Mode	Rank
I4.0 definitions	1.34	1	3
I4.0 historical context	1.48	1	2
I4.0 events	1.51	1	1

shows the statistical values of I4.0 knowledge among the respondents; an overall average of (1.44) and a mode of 1 would indicate a low level of knowledge.

The way an organization conducts business determines its culture. It is a compilation of staff members’ individual and group experiences, beliefs, values, and their resistance to change. The following Figure 7. I4.0 barriers shows that cultural challenges were among the most important barriers that prevent the implementation of I4.0.

The cultural barriers can be summarized as follows:

• There is an evident resistance towards new technologies.
• I4.0 may increase labor inequality and may be limited to a range of advanced and technical skillsets.
• I4.0 may contribute to the empowerment and disempowerment of middle-class jobs as well.
• I4.0 may affect the sense of privacy, both on an organizational level and individual level.
• Language barriers.
• The human versus machine dilemma: there are still fears and untrust of giving some tasks to a machine or AI.

The D5 dimension is assessed in terms of I4.0 technologies’ level of application. As shown in Figure 8, the I4.0 application degree, sensors are one of the most applied technologies within Saudi Arabia’s cement companies, with around (82%) of manufacturers. The use is generally concentrated in the packaging and shipping phases, in which there are machines embedded with sensors and a high degree of automation. The machines also have an automatic microcomputer control that has intelligent identification techniques.

About (60%) of companies implement robotics in manufacturing. The vast majority of companies use them for receiving and inspecting raw materials, which is the first step in cement production. Robots are used for quality control, with quality personnel monitoring raw material samples. Robots perform remote analysis by inspecting raw materials and transmitting data to a server via a computer interface. It is also essential to note that these quality control laboratories operate with little to no operator, which shows a striking illustration of how I4.0 is altering the nature of work and can lead to labor substitution.

Around 10 factories of the participants have these sensing devices and devices connected to the plant’s “control room”. The fully connected system can detect and report the machines’ behavior and send the data to the control room. It can also detect and report potential failures, enabling the plant operator to act on predictive maintenance before faults occur.

Cloud services have an application rate of (29%). This service provides a web-based platform for partners and customers to submit requests and queries. The web-based portal system is managed from remote offices and headquarters. For this reason, it was noticed that the majority of those who use it are companies with main offices in the central region. The cloud service used here to maintain customers and partners’ data can manually back up portal data when they need it. The cloud service is connected to a main computer.

It was observed that simulation in its various forms is still considered preliminary in the sector. Only a few companies use it, and the features are still limited to 3D model interfaces for computers in control rooms. The interface does not allow interaction between the user and the model. It only provides traditional rendering.

In total, (25%) of companies use big data services, and nearly six factories use commercial big data analytics. Most of them are designed to manage massive data loads shared by customers and partners; they are also used for quality control purposes to provide process analytics and keep records of their KPIs. The companies are still in the preliminary stages of utilizing AI other than the previously mentioned applications. There are still no machine learning solutions or any type of algorithmic application or optimization based on AI solutions.

Questions about additive manufacturing are asked. So far, there are no actual applications in the sector for this technology. However, there are proposals and improvement consultations regarding the future use of this technology for cement–concrete products.

The companies were also investigated for what departments are engaging and embracing I4.0 technologies. It was found that sales and marketing widely employ I4.0 concepts in sales and marketing. Most of them are planning to implement digital platforms and web-based portals to facilitate sales and marketing aspects.

Dimensions D7 and D8 were investigated in terms of people working at the companies, their customers, and growth projects. Figure 9 illustrates that workers at the companies tend to be beginners, or at most, still learners. Participants were found to be most skilled in robotics operation as it had the fewest nonqualified workers; this is due to the fact that this is one of the most employed I4.0 technologies in the companies. Therefore, a lot of workers are engaged within a robotics ecosystem. It also indicates that additive manufacturing is the one technology that has the lowest number of nonqualified workers since they are not involved in any projects that benefited from it.

Table 5. Statistical values of I4.0 skills.

I4.0 Skill Items	Average	Mode	Rank
System thinking	1.72	2	4
Data analytics	2.04	2	3
Operatorial excellence	2.56	3	2
Programing	1.29	1	5
Cybersecurity	1.06	1	7
Simulation (VR and AR)	1.01	1	8
Robotics	3.01	3	1
Additive manufacturing	1.10	1	6

shows the statistical values of available I4.0 skills among the respondents; an overall average of (1.8) indicates that further skills development is needed. This is justifiable due to the novelty of some I4.0-related technologies and applications in Saudi Arabia.

To find out whether there were statistically significant differences in the responses of the study individuals in terms of skills, the analysis of variance (ANOVA) with a (5%) significance level was used with different scenarios:

• The test was performed for different departments (job functions) in the companies and showed a p-value = (0.007 < 0.05), indicating a statistical difference between the means.
• A p-value of 0.004 was found when the test was performed based on the level of investments in I4.0 technologies and training plans, indicating a statistical difference between the means of skills and the organizations’ activities towards I4.0.

It is also essential to contextualize the potential effects of I4.0 on growth in light of recent economic trends and other growth-promoting factors. I4.0 will definitely trigger major growth within the companies when its technology is exploited effectively.

Figure 8 shows that around (43%) of the respondents presented a basic level of awareness regarding the impact of I4.0 on company growth, while (25%) of them presented minimal awareness, and it also indicates that (32%) had high awareness.

Another aspect assessed is the simple fact that increased levels of automation and digitalization will inevitably lead to the loss of particular sorts of jobs as manual labor gives way to automated machines. On the other hand, this does not mean that those workers should be left out in the cold. As a direct consequence of this, novel occupational categories will come into existence, the value of “soft” or “human” talents will grow, and, ultimately, the global quality of living will improve, just as it has after each preceding industrial revolution. The awareness of I4.0’s impact tends to be moderate among the respondents as shown in Figure 10. This result can be justified by a simple concept. The prevailing perception is that digital transformation will only replace routine jobs. However, what has been noticed recently is that it is able to replace jobs that require analytical, technical, and advisory skills.

Table 6. Frequencies related to the I4.0 impact awareness.

Impact Scope	None		Basic		High
	Frequency(%)	Count	Frequency(%)	Count	Frequency(%)	Count
Labor substitution	30.8	134	51.3	80	17.9	47
Gander parity	15.4	159	61	40	23.6	62
Localization	46.2	74	28.2	121	25.6	67
Nature of work	43.6	88	33.8	114	22.6	59
Companies’ growth	25.6	116	44.6	67	29.8	78
Organizational charts	28.2	118	45.1	74	26.7	70

shows the details of impact awareness frequencies.

4.3. Intreviews Thematic Analysis

• Theme 1: general awareness

Lack of knowledge is one of the challenges facing organizations in general awareness. Companies do not require technology-only specialists to ensure the success of their I4.0 transformation; rather, they need external experts who can provide support and guidance toward an effective transformation. Resistance to change is one of the reasons for limiting awareness-raising. Most employees prefer stability over new challenges and opportunities, especially without financial and encouraging incentives.

• Theme 2: I4.0 framework and the proposed model

The interviewees were presented with and questioned about the proposed model. These discussions ensured that useful supplementary data could be gathered to enhance the framework. We came to some interesting conclusions as a result of the discussions: First, that envisioning an outcome means realizing the value and level reached through this model. This is performed by focusing on customer or business value. In addition, a number of items that should be prioritized and may be affected by this transformation were identified. For instance, business models impact I4.0 transformation, competitive position, and collaboration efforts.

• Theme 3: I4.0 challenges and problems

Financial: Any future project is affected by the financial stability of the company. As discussed in the survey analysis, companies that have spent money on replacements of production lines in the past five years need more time to invest again in bringing in new technologies, which is a big challenge for companies. One of the companies mentioned that I4.0 requires “huge investments in the research and development are needed ”. This is something that most companies may not be able to carry out in the current period given the current fluctuations in the sector as discussed previously in Figure 4.The amount of spending on bringing in new technologies in the last five years, starting from 2018 to 2022 inclduesmoney spent on technological improvements such as, changes to production lines, computers, machinery, and equipment.

Organizational: The biggest organizational challenge is empowerment. Company A mentioned that “there are fears about the increasing rate of labor substitution”. This is because machines have replaced most employees; for instance, sales departments have been replaced by web-based portals. Another example is that employees in raw material laboratories have been replaced by robots that inspect and report. Automation substitutes labor on production lines. Furthermore, company B stated that “I4.0 requires the complete transformation of entire systems.” This change calls for new and specialized manpower”. The impact of emerging technology on employment is broadly divided into two opposing camps: those who believe it will create increased job opportunities and those who believe it will lead to progressive social and political Armageddon by creating massive technological unemployment. Company Q stated that “about 30% of total employment in the sector is at risk; perhaps over the next decade or two, the cement plant will be fully operated with only 30 to 50 operators or less; in a modern type of cement plant, it will require a limited number of workers”.

Another major challenge in organizational strategy is strategic alignment. Every organization must develop a digital I4.0 strategy to reap the benefits of its implementation. A digital strategy needs to align with the organization’s core business plans. It needs to set the direction of the enterprise, inform priorities and scarce resources, and guide their decisions towards the I4.0 era. The strategist’s challenge in the I4.0 era is to balance the intersection between three critical factors: values, opportunities I4.0 brings, and capabilities required to fully operate a modern cement factory. Company C stated that I4.0 adoption depends on “market demand and what is required to satisfy customer requirements”. Company E also mentioned that I4.0 will influence business strategies due to the rapid development it brings. This will increase businesses’ global reach, the multinational distribution of labor pools and supply chains, and stakeholders’ worldwide interest and influence.

5. Discussion

5.1. Proposed Model Guidlines

This section describes the steps of the framework and how to use them to achieve the appropriate level of I4.0 readiness. The outcomes of the literature review and the data analysis led to a number of significant discoveries. Based on a number of key elements drawn from the first two phases of the study, the most essential detail of the proposed model is to reach a desired state, or best practice, of I4.0 implementation after multiple iterations of the PDCA cycle. An explanation and instructions for each stage of the proposed model are provided in the subsequent sections.

Plan stage: At this stage, the organization will literally plan what needs to be carried out. Depending on the project’s size, planning can take up a major part of the effort. It will usually consist of smaller steps so that the organization can build a proper plan with fewer possibilities of failure. The dimensions related to this phase are D1, D2, D3, and D4. The guidelines for evaluation at this stage are shown in

Table 7. Plan stage maturity items.

Plan	I4.0 Maturity Evaluation Items
D1	Level (1): requirements that may arise due to I4.0 are not specified; I4.0’s major trends are not analyzed. Level (2): I4.0 context studies have been started; market analysis in terms of I4.0 is initiated. Level (3): the organization knows its place in the market in the I4.0 race. Level (4): processes have been aligned with I4.0 technologies; new I4.0 opportunities are being identified. Level (5): dynamic process to study internal and external I4.0 issues.
D2	Level (1): no investments towards I4.0 projects; little buy-in from top management to I4.0 strategies. Level (2): a value proposition of digital strategies is starting to be acknowledged. Level (3): an I4.0 strategy is formulated; funds are allocated; and business model change plans are in place. Level (4): the I4.0 digital strategy is integrated into all of the organization’s strategic objectives. Level (5): the I4.0 digital strategy is embedded in the organizational vision and mission.
D3	Level (1): there is little or no appetite from leaders to adopt I4.0. Level (2): there is on–off collaboration within different departments regarding I4.0 implementation. Level (3): leaders understand the opportunities in I4.0; I4.0 initiatives are being introduced. Level (4): leaders involve team members in I4.0 training projects and provide support. Level (5): leaders understand and fully embrace I4.0 projects.
D4	Level (1): there is a bottom-up drive by staff to embrace a digital culture; there is resistance to change. Level (2): a small number of staff are engaged in I4.0 projects. Level (3): the staff understand the benefits and opportunities, and can introduce creative ideas for I4.0. Level (4): the staff fully embrace the digital strategy and are driving cultural change. Level (5): the staff are digitally savvy and aware of how to utilize I4.0 technologies proactively.

.

Do stage: At this point, action must be taken. The organization will initiate the implementation of the I4.0 strategy developed in the preceding stage. The organization will take action beyond organizational design, processes, technology, and human resource management. The organization must be aware that unanticipated complications may arise during this phase. This is why, in an ideal circumstance, the organization would first attempt to implement the plan on a limited scale and in a controlled environment, or conduct a pilot project, and then expand the scope in the subsequent iteration. The dimensions related to this stage are D5, D6, and D7. The guidelines for evaluation at this stage are shown in

Table 8. Do stage maturity items.

Do	I4.0 Maturity Evaluation Items
D5	Level (1): there is no integration of any I4.0 technologies or solutions; legacy systems are still used. Level (2): I4.0 technologies are starting to be utilized. Level (3): the infrastructure for deployment is ready. Level (4): I4.0 technologies are operated and fully integrated within the organization. Level (5): there is full implementation.
D6	Level (1): there is no change in the organizational structure according to I4.0 integration and no I4.0-related roles. Level (2): there is some cross-organization awareness of digital opportunities. Level (3): the digital team is embedded in the organizational structure; the nature and methods of work are changed. Level (4): new types of jobs emerge from the organization. Level (5): the structure is fully oriented around I4.0.
D7	Level (1): no training plans regarding I4.0 are initiated. Level (2): there are I4.0 training initiatives. Level (3): there are training opportunities and projects. Level (4): the staff is constantly being developed. Level (5): I4.0 is in alignment with the core business portfolio for any growth and development programs.

.

Check stage: monitoring KPIs and performance outputs with the selected I4.0 plans and enforcing them as necessary form the next step. This stage should have outlined what should be inspected and how they should be evaluated. This is one of the crucial proposed model characteristics. The dimensions related to this stage are D8 and D9. The guidelines for evaluation at this stage are shown in

Table 9. Check stage maturity items.

Check	I4.0 Maturity Evaluation Items
D8	Level (1): there is minimal knowledge and awareness towards I4.0, and no engagement with interested parties. Level (2): customer engagement solutions have been introduced. Level (3): the staff are qualified and can lead I4.0 projects; there is proactive engagement. Level (4): the organization is service-oriented; the staff are experts. Level (5): all interested parties outside and within the organization can always be connected.
D9	Level (1): there is no realization of I4.0’s benefits to KPIs. Level (2): the potential I4.0 benefits to KPIs are acknowledged. Level (3): the digital team is embedded in the organizational structure; the nature and methods of work are changed. Level (4): KPIs can be advanced with I4.0 implementation. Level (5): the organization can generate innovative solutions to advance KPIs.

.

Act stage: This is the concluding phase of the plan–do–check–act cycle. Previously, the organization designed, implemented, and evaluated the I4.0 implementation strategy. It is now time to act.

If everything appears to be in order and the company has achieved the original I4.0 objectives, then they may proceed with the current situation as the new standard. Consequently, the PDCA paradigm results will become the new baseline. However, every time a standard plan is repeated, the company must retrace all steps and strive for improvement. Therefore, D9 can be input for the new iteration, which can generate new context for D1.

5.2. Case Study

A conceptual cement DT model in Figure 11 was developed for a selected company based on the ISO 23247-1:2021 “Automation systems and integration—Digital twin framework for manufacturing”, which provides standards for DTs [36]. Suppose this is the desired state that the company wants to reach in terms of I4.0 implementation and readiness. The aforementioned guidelines and evaluation criteria can be used to reach this level. The company needs to self-assess themselves at all stages by identifying and providing the following at each stage.

Plan stage

• How many teams must be assembled? For example, the company may feel compelled to create a digital team and invest in their training.
• What are the major DT trends impacting the industry?
• How should the company position itself in the market relative to its rivals when it comes to DT technological progress?
• What policies are needed? Such policies authorize the digital teams to make decisions on behalf of the organization.
• What are the most important goals of using DTs in the company’s unique case (e.g., to make cost-effective use of technology, to improve productivity, to cut labor costs, etc.).

Do stage

• How is the company’s structure likely to evolve to meet DT standards?
• Can the organization leverage their infrastructure to deploy DT?
• How is the company using their resources?
• What are the possible advantages of using I4.0 technologies, and what are the best DT technologies that suit the organization?
• After implementing the DT project, can the people, customers, and other interested parties absorb the changes and realize the value?
• Is there any resistance to change?

Check stage

• What goes wrong during the DT implementation process?
• What are the benefits gained from the implementation? Any improvements in the KPIs should be stated.
• Are there any issues or obstacles that prevent the implementation?

Act stage

Decisions here are made based on each stage’s results, and the current values are the new benchmark for another PDCA cycle.

Having described the proposed model, we now compare it to a select number of other I4.0 maturity models in

Table 10. Comparative analysis with I4.0 maturity models.

Model	Focus and Main Dimensions
The proposed model	Includes nine dimensions as follows: environmental inputs, strategy, leadership, growth, infrastructure, culture, engagement, and outputs. Embedded with a PDCA iterative cycle.
Smart Factory Implementation and Process Innovation [37]	Includes four maturity levels with three organizational dimensions: people, process, and technology.
Acatech Industry 4.0 Maturity Index [38]	Includes six levels of maturity with structure, culture, information systems, and resources-related dimensions.
Development of an Industry 4.0 maturity model for the delivery process in supply chains [39]	Includes five stages of maturity that focus on supply chain aspects of the organizations.

to determine what differentiates it from them.

6. Conclusions

6.1. Outcomes

This study presented an exploratory analysis of the Saudi cement industry from an I4.0 perspective. The purpose of the study was to develop a framework for the cement industry to implement I4.0 and highlight the significance of employing a systematic framework. This was accomplished by presenting in detail the disruptive changes this revolution may bring to organizations. Therefore, a holistic framework that provides guidance to strategically lead cement companies for an effective I4.0 implementation in organizational systems, enabling them to see through chaos and understand complexity, was proposed. We utilized the best practices found in the scientific literature as well as analyzing the market and collecting enormous amounts of data. These activities added significant results to this research and integrated systemic, diagnostic, and vision features into the proposed model.

The developed I4.0 implementation framework adds to the body of knowledge and contributes to a deeper comprehension of the I4.0 paradigm shift from an organizational and global perspective. The PDCA cycle tool was employed to provide a model that focuses on inclusiveness, continuous improvement, and development. This study evaluated and studied the local cement sector and provided an insight into its readiness to embrace this revolution.

6.2. Future Research

This paper emphasizes the need to include an experimental or small-scale project in the PDCA cycle’s Do stage. After implementing new I4.0 technologies, additional analysis can be conducted. Also, it would be interesting for future research to apply and validate the implementation framework and maturity model in additional companies and industries to determine if the dimensions and steps are applicable in these contexts. This development would also further demonstrate and support the framework’s generalizability.