The Impact of Smart Information Technology on Competitive Advantage in Logistics Companies

Amid the rapid technological transformations that our current era is witnessing, data has become a fundamental base for making strategic decisions in organizations. The concepts of “Industry 4.0” and “Logistics 4.0” refer to the integration of digital technology and logistics processes, enhancing companies’ ability to analyze data to improve efficiency and build a competitive advantage. This article discusses the impact of intelligent information systems, specifically “Business Intelligence” (BI) systems, on enhancing competitive advantages in logistics companies, through a case study in a specialized Portuguese company. We will explore how these technologies can contribute to improving decision-making processes, enhancing performance, and meeting changing market needs. By surveying the opinions of the company’s employees, we aim to understand the factors influencing the successful use of BI tools and how to invest resources optimally to achieve sustainable advantages.

The Technological Changes and Their Impact on Data Effectiveness in Organizations

In the face of the increasing competitive environment that organizations are experiencing today, data and information have become essential elements for maintaining organizational success. The shift towards digital systems has led companies to increasingly rely on modern technologies such as Industry 4.0 and Logistics 4.0, facilitating the process of collecting and analyzing vast amounts of data. These modern technologies not only help speed up processes but also enhance the quality of decision-making by providing accurate and reliable information.

The digital transformations encompassed by these technologies are characterized by their ability to facilitate access to information, allowing organizational leaders to respond to challenges and support strategic decision-making. For example, Business Intelligence (BI) systems can convert raw data into valuable insights that aid companies in monitoring their performance and analyzing market trends. Advanced technologies such as Big Data and Cloud Computing can provide deep insights to improve operational performance and increase competitiveness.

Moreover, the push towards automation and digitization makes the data processing more effective and faster, thus reducing human errors and increasing the overall efficiency of processes within the organization. Therefore, intelligent systems today are among the fundamental aspects that help companies face the complex market challenges.

The Importance of Information Technology in Enhancing Competitive Ability

Good planning and the application of information technology have a direct impact on the level of institutional performance. Today’s managers recognize the importance of investing in information technology as a primary source of competitive advantage. The rapid developments in information technology require organizations to make IT a cornerstone of their strategies and future objectives.

We find that Business Intelligence systems are a vital system for achieving these advantages, enabling companies to analyze data effectively, which facilitates making decisions based on reliable data. For instance, companies can use analytics to predict future trends and improve internal processes, translating into increased profits and enhanced service levels provided to customers.

Studies indicate that the use of information technology, such as Business Intelligence systems, has led to significant improvements in operational efficiency and productivity. By promoting the effective use of data, companies can significantly enhance their logistical operations and reduce operational costs.

Challenges of Using Business Intelligence Systems in Logistics Companies

Despite the numerous benefits of information technology, there are serious challenges facing organizations when implementing Business Intelligence systems. One of these challenges is the need for substantial investment in technological infrastructure and training. Reports have shown that many information projects are terminated before completion or exceed their budgets, raising concerns about the effectiveness of these investments.

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to the integration of business intelligence tools to more informed decision-making processes and ultimately better business outcomes. By leveraging data analytics, companies can gain insights into operational inefficiencies, customer preferences, and market trends. This allows organizations to respond proactively to changes in the environment, thus maintaining a competitive edge in the market.

As companies embrace business intelligence technologies, they must also ensure that their staff is equipped with the necessary skills to utilize these tools effectively. This involves ongoing training and support to foster a data-driven culture within the organization. Overall, the adoption of business intelligence is not merely a technological upgrade; it represents a strategic shift towards becoming more data-centric in all aspects of business operations.

Using BI correctly to improve work methods within companies, stimulate innovation, and respond quickly to changes. Through precise data analysis, companies can predict demand levels and adjust their resources accordingly, reducing costs and enhancing efficiency. Having an integrated data analysis system simplifies and streamlines operations, helping to make faster and more accurate decisions.

Information Sources and Their Role in Decision Making

Data collection and analysis is a vital part of successful business strategies. Data is a rich source of information that can impact decision-making at all levels. This is where BI technologies come into play, transforming raw information into actionable insights. Organizations use BI systems to understand business performance and identify trends, enabling them to make informed decisions based on clear evidence.

BI systems offer real-time analysis capabilities, which help in making quick decisions based on accurate information. For example, a BI system can provide insights into product sales, enabling companies to effectively adjust their marketing strategies or production processes. Thus, relying on data gives companies a competitive edge by improving their response to market changes.

The modern business environment requires companies to be flexible and able to respond quickly to market changes. By using BI systems, companies can continuously analyze data and discover any deviations or unexpected trends. This can have a long-term impact on how they manage risks and achieve growth and innovation.

Modern Technology and Its Impact on Logistics Efficiency

Modern technology plays a vital role in enhancing the efficiency of logistics operations. With the development of what is known as “smart logistics” or L4.0, organizations have begun to implement IT solutions to streamline processes and control the flow of goods more effectively. Technologies such as the Internet of Things (IoT) and robotics contribute to improving transportation, storage, and distribution, leading to an overall enhancement of operations.

Transitioning to smart logistics provides significant opportunities for business leaders to enhance efficiency, reduce costs, and promote transparency in operations. Modern technologies enable remote control of logistics processes and help provide real-time information. This type of data allows for quick analysis that enables companies to respond to challenges in a timely manner.

For instance, companies can use artificial intelligence applications to analyze data and improve logistics operations. By adopting tools like big data analytics, organizations can track shipments and manage inventory more effectively. This type of data enhances companies’ agility in facing sudden market changes and enables business leaders to plan strategically accordingly.

The Relationship Between Modern Technologies and Market Competition

Companies in various business fields face increasing challenges that require continuous innovation and the ability to adapt to current changes. Technologies such as big data analytics and business intelligence are critical tools that enhance company performance and provide a competitive advantage. By utilizing these technologies, companies can analyze market and customer data more effectively, helping them make strategic decisions that strengthen their competitive position.

Discussions around Industry 4.0 technologies highlight how they enable companies to leverage data and improve their operations in alignment with their strategic goals. Adopting new digital and technological methods can lead to faster and more efficient services, attracting more customers and enhancing brand reputation. Companies that invest in modern technology will not only experience transformations in operations but will also allow themselves to completely reimagine their business models.

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of implementing business intelligence systems can also present a significant barrier, especially for small and medium-sized enterprises. It is crucial for organizations to understand that investments in these systems can lead to long-term advantages and improved performance. Additionally, integrating business intelligence into existing workflows often requires significant time and effort, which may further complicate the transition.

Moreover, the quality of data plays a vital role in the effectiveness of business intelligence. Poor data quality can lead to erroneous insights, which may negatively impact decision-making. Therefore, companies must prioritize data governance and ensure that the information collected is accurate, complete, and timely.

In conclusion, while the implementation of business intelligence offers numerous advantages, organizations must be aware of the challenges and barriers they may encounter. By addressing cultural resistance, managing costs, and ensuring high-quality data, businesses can maximize the benefits of business intelligence and enhance their overall performance.

The challenges associated with the implementation of business intelligence systems are among the obstacles that can hinder the execution of these technologies, as decision-makers struggle to assess the return on investment. Moreover, the lack of understanding among organizational leaders regarding the importance of business intelligence and its impact on performance can impede the adoption process. Therefore, building an organizational culture that values analysis and collaboration mechanisms can play a pivotal role in facilitating the implementation process.

The challenges faced by business intelligence systems may also include data integration issues due to departmental silos, which prevents the formation of an effective data warehouse. Consequently, this represents a significant challenge that requires a radical overhaul of data collection and analysis systems. Studies have shown that improving data quality is a focal point, as the type of information available to users is an integral part of implementing business intelligence systems.

The Importance of Business Intelligence Analytics and Its Application Areas

Business intelligence analytics are powerful tools that can be used across various business cycles. Among the most common BI analytics is profitability analysis, where historical sales data across products, customers, and regions is analyzed. This helps companies evaluate the profitability of products and services, contributing to improved marketing strategies. Through continuous performance evaluation, companies can adopt clear developmental directions that help enhance financial outcomes finance.

Additionally, customer relationship analysis is a fundamental element in strategies for building long-term relationships with customers. By utilizing order history data and surveys, customer retention levels and support service performance can be analyzed. The insights gained from these analyses contribute to taking actions to regain customers and enhance their loyalty, which in turn contributes to positive business outcomes.

Strategic planning is another area that benefits from business intelligence analytics. Companies can model key variables related to their development and measure their strategies concerning their goals. These practices help in forming flexible strategies that can adapt to rapid changes in the business environment. Financial and managerial control analytics are also employed, allowing improvements in budgeting and forecasting processes by focusing on key variances.

Delphi Method: Explanation of the Methodology and Characteristics

The Delphi method is a research approach used to gather and analyze expert opinions in order to reach a consensus on complex issues. This method was designed by Linstone and Turoff in 1975 and relies on organizing a structured communication framework that collects and synthesizes expert opinions through a series of multiple questionnaires. The basic idea is to enhance cooperation among experts and facilitate the attainment of reliable and comprehensive results through repeated rounds of questionnaires, where information is collected, summarized, and reviewed after each round. This approach allows for consensus-building, which enhances the accuracy of forecasts and analyses.

This method is used in a variety of fields, from policy development to business strategies, as it avoids the negative impacts of face-to-face interactions such as group conflicts or the dominance of a single individual, thereby enhancing the quality of dialogue and intellectual exchange. For instance, it may be used to collect opinions on new technological developments or to set priorities in research and development.

The key characteristics of the Delphi method include anonymity, which maintains the identity of the participants, thereby enhancing the freedom of expression; feedback, which helps improve discussion and directs participants to adjust their opinions based on responses; and the interactive toolkit that enhances idea exchange among participants. All these characteristics come together to create an environment conducive to knowledge gathering and achieving widespread consensus.

Study

Case Study: Applying the Delphi Method in a Logistics Company

This section focuses on a case study related to a leading logistics company in Portugal, which recently launched a business intelligence project using Power BI. Power BI is a business analytics service developed by Microsoft, notable for its powerful data analysis capabilities and the provision of interactive visualizations. This tool aims to enhance companies’ ability to make data-driven decisions through reports and interactive dashboards.

In this case, the Welphi platform was used to distribute the survey, an online platform considered effective in increasing response rates due to its simplicity and speed. Participants were briefed through internal announcements and comprehensive explanatory materials, facilitating a good response rate in most cases. The approach involves dividing surveys into multiple sections, making it easier to manage responses and comparisons. For example, in the case of the company concerned, the experiment aimed to explore how BI tools affect various departments, including transportation, finance, and innovation.

Due to the diversity of participants, the study managed to obtain comprehensive opinions reflecting different experiences regarding the use of Power BI, helping to form meaningful and applicable conclusions. Early results, after reviewing the responses from the first round of the survey, indicated a strong understanding of the importance of BI tools but with some reservations about how these tools are actually used in daily operations.

Implementation Process: Steps to Apply the Delphi Method

To implement the Delphi method, several important steps must be considered throughout the process. This includes selecting a group of experts, developing the initial survey, initial communication with experts, and distributing the survey. Each step targets collecting and analyzing opinions in a thoughtful manner. In the case of the logistics company, five main areas were focused on: logistics, transportation, finance, innovation, and central services. Each of these areas played a vital role in shaping the accumulated knowledge around the BI project.

Sixty-one experts from various departments were identified, representing a well-rounded group without compromising the quality of responses. It was essential to structure the survey to include dimensions covering multiple aspects of usage and individual interactions with the new system. The survey employed a Likert scale to understand the extent of participants’ agreement with the statements presented. These scales provided a clear analysis of levels of acceptance and consensus among committee members.

The process followed a scientific approach to data collection, including gap analysis between observations from different rounds. Each response was documented accurately, enabling researchers to see major trends as well as contentious points. This allowed for constructive discussions on how to improve the use of the tool and overcome challenges that employees may face. Ultimately, the success of the implementation depends on adhering to a process of correction and feedback, making it a key performance driver in achieving research objectives.

Understanding English: The Importance of Business Strategies

English is considered a primary communication medium in today’s global business community. Understanding and mastering the English language is vital, directly impacting the effectiveness of business operations and the ability to communicate with customers and business partners. The modern business process requires a high competency in using English, whether for negotiations, report writing, or analysis. In the context of business intelligence (BI) strategies, the English language is treated as an essential part of the utilized technology, highlighting the need for language skills among employees. Linking English language proficiency with effective communication enables organizations to tackle challenges related to competitiveness. Studies indicate that companies with a bilingual or multilingual workforce tend to achieve better outcomes in terms of growth and innovation.

Method

Delphi: Design and Implementation

The Delphi method is one of the techniques used to collect and analyze opinions from experts, applied in various fields including market studies and business strategies. In this study, the Delphi method was employed through two rounds of responses to reach a consensus among experts about artificial intelligence strategies. The first phase of the process involved gathering opinions on statements related to the BI project, which were organized into areas concerning the company’s interests. This approach aimed to balance the depth of responses with the need to manage the time duration to minimize the risk of participant drop-out. The second round focused on enhancing the results obtained in the first round, where some statements were reiterated and discussions were expanded to ensure the acquisition of the most accurate and analytical information.

BI Strategy and Added Value

The business artificial intelligence strategy discusses many areas, particularly regarding the added value this strategy can provide to companies. The elements evaluated in this strategy include value, strategic alignment, and employees’ understanding of the vital factors for project success. Among the statements recorded was: “The BI project will provide value to the business,” reflecting the market’s need to adopt modern technologies as a core concept for staying competitive. The awareness of most employees regarding the importance of this technology indicates the provision of a work environment ready to accommodate new changes and challenges, facilitating the adaptation process to the changing market demands. Data shows that 60% of participants warned of customer loss if these technologies were not adopted, reflecting the necessity for technological strategies to adapt to customer expectations.

Data Infrastructure and BI Platform

An effective data infrastructure is considered one of the key factors for the success of any artificial intelligence strategy. The more integrated and well-organized the data, the greater the ability to make decisions based on accurate information. Statements such as “The BI tool will meet your data integration needs” and “The BI tool will improve the clarity and accuracy of information” were developed through structured meetings. Improving data management through BI technologies contributes to enhancing the quality of information available to management and assists in making quick and smart decisions. Literature indicates that BI technologies can meet business needs and help increase productivity, as evidenced by the responses from experts and the growing consensus in opinions among participants.

User Experience: Evaluating the Effectiveness of BI Technology

User experience relates to using the tool, its complexity, and the challenges associated with its adoption. Statements included at this stage, such as “The skills required to use BI technology will be complex” and “Integrating these technologies into current work practices will be very difficult,” indicate a genuine concern about employees’ readiness to use the new technology. BI technology requires a high level of training and support to ensure successful use. Addressing these concerns necessitates a comprehensive training program that covers how to use the tools seamlessly and encourages senior management to support employees in this process. Collaboration between project teams and users is critical to ensuring ongoing qualification and professional development. Continuous evaluation of user feedback regarding the tool’s effectiveness and its practical impacts is still needed.

External Influences and Investigating Technology Implementation

External factors play a crucial role in determining the success of adopting BI technology in any organization. Interaction with suppliers and customers, who may drive companies to use this technology, is an important element. Statements like “Suppliers will drive the use of this technology as a means of working” highlight this trend. Understanding the feedback and expectations of these external parties contributes to identifying the most effective adoption strategies. Moreover, customer data and information based on their expectations are essential parts of any monitoring success strategy. Companies are required to be flexible and ready to adapt to new areas of business imposed by changes in customer expectations, necessitating integrated data management that considers the opinions of all stakeholders.

Importance

Adapting BI Models to User Needs

Business Intelligence (BI) models are a vital tool in the current information age, as they help companies make informed decisions based on accurate data. For these models to be effective, they must align with the needs of end users. The importance of this issue emphasizes the necessity for both the project team and BI system designers to have a precise understanding of the needs of various departments within the company. Without this deep knowledge, it is possible to develop systems that do not meet user expectations or requirements, leading to misuse of the tool and an unsatisfactory experience. To achieve better adaptation, it is advisable to implement pilot tests, through which the model’s behavior can be evaluated before it is finally adopted. These tests also provide a window of time for making necessary adjustments that ensure compatibility between the tool and the specific demands of users.

Furthermore, collaboration among multidisciplinary teams is an essential element in improving BI models. These teams should continuously interact with both stakeholders and users to update and modify the model according to new developments. Effective communication and flexibility in working facilitate achieving fruitful results, enhancing the tool’s ability to adapt to changing business needs. An example of this is the integration of IT specialists with business experts, which allows for the establishment of qualitative solutions aimed at finding an ideal equation between the end user and the tool being used.

The Necessary Dimensions for Data Architecture and BI Platform

Data architecture and the BI platform are critical factors in the success of any Business Intelligence-related project. A good consensus was reached among participants on the importance of these dimensions, as they expressed agreement on the necessity of updating the infrastructure to align with the demands of the changing business environment. In an era characterized by rapid technological development, it is crucial that the platform adopted by the company is aligned with future market requirements. A comment from one of the participants highlights the need to keep up with technological developments, noting that relying solely on tools like Power BI may become insufficient with the emergence of newer solutions capable of providing advanced analytics.

Data quality is also considered one of the essential aspects, as the accuracy of outputs directly depends on the quality of input data. Even when powerful BI tools are used, the presence of misleading data will inevitably lead to inaccurate reports. This underscores the importance of focusing on data quality, which comes from improving the systems used to acquire data and ensuring its accuracy and reliability. Consequently, a continuous mechanism for monitoring and improving data quality should be in place so that the BI tool can provide reliable and actionable insights for decision-making.

User Experience in Using BI Tools

The relationship between users and BI tools requires facilitating access to information since these tools must be easy to use and interact with. According to participants’ opinions, BI technology is not complex, and its visual and technical range aids users in easily extracting information. However, the challenges return to the system-building process and ensuring data accuracy more than anything else. While “configuring and setting up dashboards” is a simple task, it requires certain technical skills that may be complicated for some, making it essential to provide specialized training to users.

The integration of BI tools with current work environments is an important feature, as 66% of experts believe that effective management will play a crucial role in supporting employees in using new technologies. The existence of a clear and smooth management plan ensures a seamless transition for these tools, requiring collaboration among all parties involved. It provides a detailed vision of how this technology can operate to achieve the company’s strategic objectives and enables employees to benefit from its capabilities in a way that positively reflects on work performance.

Challenges

Implementation and Adaptation to Future Developments

The challenges that arise from implementing BI tools may place companies at a crossroads, as adaptation to changes and the pursuit of modern technological developments is essential. In fact, the opinions of participants in the second round of Delphi surveys reflect an increasing interest in technology and its role in enhancing competitive ability in the market. The notable increase in the level of consensus on the importance of using technology for the nature of business in the future reflects the strategic direction that companies should follow.

The changes in participants’ perceptions regarding some factors, such as awareness of project success and its impact, may be an issue that requires further study. Successful investment in any technology requires a direct connection to the requirements of business operations and ensuring that all management levels are aware of the benefits of this technology. This emphasis on the importance of effective communication and a comprehensive understanding of new tools helps companies maximize the benefits of the system and ensure greater successes in the future.

User Experience with Technology and Its Impact on Organizational Effectiveness

The percentage of users endorsing the experience of using Business Intelligence (BI) tools increased by 11% between the first and second rounds of the study, indicating a significant advancement in employee integration of technology. The results showed that some other statements achieved modest growth rates, with the first increasing by 2% and the last by only 1%. The limited growth results in the last statement reflect participants’ feelings that the tool was not sufficiently presented within the company. This indicates an urgent need for senior management to adopt an effective strategy to better define and train employees on the tool. This strategy should include effective communication, clear rewards, and comprehensive training that helps employees understand how to best utilize technology.

To achieve this, senior management should focus on providing opportunities for employees to use technology in their daily activities and foster a culture of data reliance in decision-making. For example, monthly workshops can be organized where employees share their experiences with the tool, enhancing the exchange of ideas and improving the overall understanding of how to benefit from this technology. Additionally, incentives can be implemented to reward teams that demonstrate tangible achievements in using the Business Intelligence tool, encouraging more employees to adopt it.

The External Image and Its Effect on Technology Adoption

A recent study has shown that there is a modest agreement on certain statements regarding technological innovations and their external impact. Although there has been a slight increase in support for two points, the endorsement for the last point has not changed, reflecting a global feeling that technology may be more beneficial for internal use rather than for improving customer relationships. It is noteworthy that 40% of participants believe that the tool could become a key component in business interactions, but senior management needs to evaluate whether the identity of the tool as beneficial lies in improving business processes or in enhancing customer relationships.

Furthermore, limited external visibility could pose a significant obstacle to marketing strategies and business relationships. Therefore, it is essential for companies to invest in research on how to use Business Intelligence technology to compete in the market, not just to improve internal operations. Channels must be created to communicate with customers to better understand their needs, utilizing Business Intelligence data for analysis and forecasting. For example, data can be used to analyze purchasing trends and assist in improving the offers made to customers with better utilization of this information. This marketing should be built around real experiences to enhance marketing messages and foster closer relationships with customers.

The Importance of Technological Leadership and Strategic Integration

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the implementation of new technologies often requires a cultural shift within the organization. Employees may need to adapt to new tools and processes, which can create resistance to change. Effective change management strategies are crucial to ensure that staff are on board and understand the benefits of the new systems.

Thirdly, data security and privacy concerns are increasingly significant as companies integrate advanced technologies. With the rise of cyber threats, organizations must prioritize safeguarding their data and maintaining customer trust. This may involve investing in robust cybersecurity measures and ensuring compliance with regulations related to data protection.

In conclusion, while Technology 4.0 presents substantial opportunities for enhancing efficiency and innovation in purchasing processes, companies must navigate the associated challenges carefully. By focusing on continuous improvement, fostering a culture of adaptability, and prioritizing data security, organizations can successfully leverage these technologies to stay competitive in a rapidly evolving market.

Cybersecurity is emerging as one of the biggest risks in the digital world. With the increase in data exchanged across networks, the opportunities for cyber attacks are growing. Therefore, companies must understand the risks and implement appropriate security strategies to protect their data and the privacy of their customers.

Additionally, adapting to the rapid changes in technology can be a challenge. Companies need to stay updated with the fast developments in Technology 4.0. This requires a combination of continuous research and development, as well as the ability to adopt rapid innovations. Perseverance in innovation can be costly and difficult, especially in dynamic business environments.

Opportunities for Improvement and Development Through Innovation in Logistics

On the other hand, Technology 4.0 offers tremendous opportunities for enhancing overall performance in logistics. Advanced analytics can be used to increase efficiency in delivery operations. For example, big data management can help companies optimize shipping routes, reducing delivery times and fuel costs. AI technologies enable companies to analyze traffic and weather data to anticipate potential challenges before they occur.

Moreover, robots and drones can be used for short-distance deliveries, significantly speeding up transportation processes. Many companies, such as Amazon, have demonstrated successful experiments in using these technologies to achieve greater efficiency in the supply chain. However, this type of technology requires a significant investment, as well as a comprehensive understanding of logistics operations.

Furthermore, Technology 4.0 allows companies to improve customer experiences by personalizing offers and products based on advanced customer data analytics. Companies can leverage data to enhance their customer experience, increasing customer loyalty and trust. For example, personalized recommendations based on consumer behavior can utilize synchronized data to improve the purchasing process.

The Importance of Digital Transformation in Small and Medium Enterprises

The business world today is witnessing an unprecedented digital transformation, as this transformation is considered a necessity to face increasing market challenges. In this context, small and medium enterprises (SMEs) are moving towards adopting digital technologies to improve their efficiency and increase their competitiveness. Digital transformation involves using modern technologies such as artificial intelligence, big data analytics, and the Internet of Things, which help these companies enhance their operations and provide better services to customers. For example, a small retail store can use a digital inventory management system to avoid product shortages and improve the flow of purchasing and sales operations.

Small and medium enterprises face significant challenges in the field of digital transformation, including a lack of qualified human resources and technological knowledge. While these companies need considerable investment in digital technologies, the return on investment can be significant, as research shows that companies adopting these changes experience improvements in productivity and customer satisfaction. For instance, companies using advanced analytics systems can analyze customer data more deeply, helping them tailor their offerings to better meet market needs.

Moreover, digital transformation is an utmost necessity in the face of rapidly changing economic conditions. During the COVID-19 pandemic, companies that quickly adopted digital technology were able to survive and continue operations. Building resilience through digital transformation can help companies quickly adapt to any changes in the work environment, enhancing their competitiveness in the future.

Therefore, digital transformation is not just an option but a necessity for all companies, especially small and medium enterprises. These companies must evaluate their specific needs and seek appropriate technological solutions that contribute to achieving their strategic goals.

Analysis

Big Data and Its Impact on Decision Making

Analyzing big data has become a vital tool in the modern business world. Companies can improve their decisions based on information supported by numbers and trends rather than relying solely on intuition. Big data provides useful insights into customer behavior, market trends, and the effectiveness of internal processes. For instance, major companies like Amazon benefit from data analysis to enhance the shopping experience by offering personalized recommendations to users based on their previous purchasing behavior.

Furthermore, big data helps companies predict future trends. By modeling and analyzing data, companies can anticipate changes in the market and respond to these changes more swiftly. One example of this is how airlines use data to identify peak times and optimal ticket prices. This assists them in better managing their resources and providing improved services to travelers.

However, analyzing big data is considered a challenge for many companies, especially small and medium-sized enterprises. The process of data analysis requires high competencies and advanced tools that are often costly. Therefore, small companies need to invest in training their human resources or seek strategic partnerships with specialized data analysis firms. Such partnerships can be a significant step towards enhancing these companies’ capabilities and enabling them to make data-driven decisions.

In conclusion, big data analysis demonstrates that it is not just a tool for maintaining competitiveness, but it is also a fundamental element for achieving sustainable success in the modern business environment. Companies that effectively adopt these technologies have contributed to positive outcomes through continuous improvement of their performance.

The Impact of Transformational Leadership on Organizational Success

Transformational leadership is considered a critical element in the success of institutions as it plays a fundamental role in motivating and guiding teams towards achieving common goals. Transformational leadership emphasizes the importance of communication, positive interaction, and building strong relationships within teams. It enhances the sense of loyalty and belonging among employees, which positively reflects on the overall performance of the institution.

Transformational leadership also contributes to developing a work environment that encourages innovation and creativity. For example, leaders who promote the sharing of ideas and discussing different opinions can motivate their employees to present new and innovative solutions to the challenges faced by the institution. This approach can lead to remarkable results, as teams can generate outstanding ideas that help the institution stand out in the market.

Moreover, transformational leaders promote ethical principles and flexibility in the work environment by setting exemplary role models. They work on building a corporate culture that embraces ethics and noble principles, which helps create a more humane and respectful work environment. The shift towards ethical leadership is considered a pivotal part of institutional success in the modern era.

The impact of transformational leadership extends beyond internal influence on teams to include customers and the surrounding community. Leaders who adopt transformational leadership styles understand the importance of fostering strong relationships with customers and working to provide value to them, which enhances the institution’s reputation in the market. This directly contributes to increasing customer satisfaction and trust, which are considered key assets for any organization seeking lasting success.

Challenges and Opportunities Related to Logistics 4.0 Technology

Logistics 4.0 technology represents a giant leap in the field of transportation and supply, integrating advanced technologies such as big data, artificial intelligence, and the Internet of Things. These technologies help improve the efficiency of the supply chain, indicating significant benefits in enhancing service speed and effectiveness. For example, companies can use GPS tracking devices to better manage their fleet, which reduces delivery time and improves customer satisfaction.

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These innovations are not without challenges. These challenges include high-cost technologies, the need for worker training, and dealing with privacy and security issues. The efficiency of logistics 4.0 technology relies heavily on data, which raises concerns about how data is used and protected. Therefore, companies must develop strong strategies to ensure data safety and privacy.

Despite the challenges, companies that adopt logistics 4.0 technology remain more competitive in the market. While these technologies can help reduce costs and increase efficiency, they also provide companies the ability to achieve an enhanced customer experience, which is critical in the financial market. For example, using advanced analytics to forecast demand can assist companies in improving planning and supply, leading to tangible operational gains.

In conclusion, logistics 4.0 technology represents a valuable opportunity for success and growth in an increasingly complex business world. With the shift toward investing in this technology, companies can enhance their adaptability and improve their performance. Therefore, capitalizing on the opportunities presented by logistics 4.0 technology is urgent for competitive markets.

The Importance of Data and Information in Decision-Making

Data and information are essential elements that support decision-making processes and enhance organizational performance. Every day, companies face new challenges that require them to improve their operations to ensure continued competitiveness in the markets. Data is used to generate accurate insights, manage risks, develop new strategies, and reduce costs while improving process flow. In this context, executives recognize the importance of the ongoing “information revolution” and allocate increasing financial resources to information technology, seeking assurances that these investments will yield the desired returns.

Information technology has evolved from a mere supportive role to become a vital source of knowledge and competitive advantage, impacting both operational and strategic levels. One of the most prominent examples of these transformations is business intelligence (BI) systems, which offer powerful tools for data analysis and support for managerial decision-making. These systems work to analyze databases to help managers develop effective strategies by processing and analyzing data. By organizing data and transforming it into actionable insights, BI systems contribute to providing a comprehensive view of business performance using visualization and detailed analysis techniques.

Studies indicate the potential for continued growth in the adoption of BI systems due to their proven benefits in improving decision-making and increasing operational efficiency. Reports such as those released by Gartner predict that global spending on information technology will reach $5 trillion in 2024, reflecting a 6.8% increase over the previous year. IT services are expected to be the largest spending category in this sector, reflecting the increasing focus on improving efficiency within organizations. However, achieving success in such projects requires consideration of several factors beyond just the systems or technology, such as the implementation of these systems, the degree of their adoption, and the efficiency of individuals’ use of them.

The Impact of Industry 4.0 on Logistics Operations

Industry 4.0 represents a digital revolution that combines advanced technologies such as the Internet of Things (IoT) and real-time data management. In this context, logistics companies are adopting these technologies to improve their operations. This revolution presents a significant opportunity to enhance efficiency and reduce costs by integrating smarter digital systems used to monitor performance and flow. Improving logistics operations means reducing the time spent on travel and inspections, which in turn enhances customer satisfaction and reduces extra costs.

The focus on digitization and technology in logistics will not only improve efficiency but will also open up avenues for developing new service delivery models. Companies investing in improving industry 4.0 technology will be able to make their production networks smarter by applying technologies like blockchain, allowing them to enhance transparency and reduce costs.

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estimates suggest that projects related to Industry 4.0 could enhance economic competitiveness and production quality. For example, several countries have developed plans aimed at boosting the manufacturing sector by providing support for digital technology. In Portugal, a plan for Industry 4.0 has been prepared, which includes training 20,000 people in digital skills, alongside an investment of billions of dollars to improve the country’s competitive capabilities.

Business Intelligence Systems as a Tool for Competitive Advantage

Business intelligence systems represent a fundamental pillar in the pursuit of competitive advantage. These systems enable companies to collect and analyze information from multiple sources, allowing them to make decisions based on accurate data. The use of BI systems indicates the ability to develop effective marketing strategies and better understand customer behaviors, which enhances companies’ competitiveness in their specific markets.

Additionally, BI systems are used to analyze performance over time, providing managers with an objective view of what needs improvement. For instance, analytics may reveal that certain products are not accessible to customers due to supply chain issues, necessitating corrective actions to enhance accessibility. Consequently, logistics managers can take practical steps to streamline processes, thereby achieving better on-time results.

Understanding the relationship between BI systems and competitive advantage is becoming increasingly important, as organizations are required to determine how these systems can contribute to achieving their strategic objectives. Research in this field shows that integrating modern technologies with overall strategies can significantly impact how institutions make decisions. Companies that demonstrate a high level of integration may be better positioned to respond to market changes and strive for innovation, thereby enhancing their competitive stance.

Challenges Facing Technology Adoption in Logistics

Technological advancement contributes to enhancing efficiency in logistics operations, but there are also challenges related to adopting this technology. One of the most prominent challenges is the gap in digital skills, as there is still a shortage of expertise needed to effectively use modern technology. This challenge becomes noticeable in work environments with a traditional approach, where it requires time and effort to adapt employees to new working methods.

Alongside the skills shortage, there are also security concerns related to data security. In the information age, data protection has become a top priority, as institutions face significant pressure to ensure the protection of sensitive information from breaches. This is no longer just an issue addressed through traditional means, but requires the establishment of comprehensive strategies for crisis planning and risk management.

Moreover, new technology systems require significant financial investments. Many companies face budget constraints for technology, hindering the smooth implementation of these systems. Even with substantial investment, project success is not guaranteed, as studies indicate that 31.1% of information systems projects are terminated before completion. In many cases, current projects exceed their original budgets, making it essential to adopt a more detailed approach to planning and executing these projects.

Infrastructure Growth and Digital Transformation in Logistics

The growth of infrastructure and digital transformation in the logistics sector involves a comprehensive change process aimed at improving the efficiency of operations and communication between various components of the supply chain. This transformation relies on advanced technologies that assist companies in transitioning from manual processes to digital systems, resulting in reduced communication gaps. Modern technologies such as artificial intelligence and the Internet of Things contribute to enhancing logistics operations, improving supply chain performance, and increasing companies’ ability to respond better to customer requirements.

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For example, using digital inventory monitoring systems can help companies track their products in real-time, enhancing their ability to make quick decisions and adapt to changing market conditions. Digital technology in logistics also represents a step toward providing customized products and services, meeting consumer needs more accurately.

This transformation requires significant investment in business information systems and the development of skills necessary to use them effectively. Business information systems contribute to improving transparency in logistics operations, enabling companies to identify weaknesses and make data-driven decisions to enhance overall performance.

Logistics 4.0: Transformations in Logistics Management

The concept of Logistics 4.0 represents a fundamental shift in logistics management, where material and information flows are integrated within companies. This includes monitoring transportation, storage, and related data to ensure the efficient and cost-effective delivery of products. The essential components of logistics, such as importing, manufacturing, distribution, and reverse logistics, are an integral part of this new concept.

There has been an increasing interest in the sustainable dimensions of logistics, as transportation systems are integrated and provide real-time data about logistics networks. The concept of Logistics 4.0 emphasizes meeting customer needs in a sustainable and cost-effective manner using digital technologies. Research on Logistics 4.0 has increasingly evolved since 2015, indicating a growing academic interest in this topic.

Many studies highlight the impact of Logistics 4.0 on several key elements in business, such as data collection and processing, assistive systems, communication and integration, decentralization, and services and self-relationships. Advanced digital technologies such as artificial intelligence and big data contribute to improving logistics operations and supporting semi-autonomous operating techniques.

Big Data Analytics: The Role in Improving Logistics

Big data analytics is considered a pivotal element in improving efficiency and speed in logistics operations. These techniques contribute to analyzing large and diverse data sets generated by connected logistics systems, enabling organizations to discover patterns, trends, and market behaviors.

Research shows that managing big data enhances the decision-making process, especially in risk management. Additionally, big data analytics demonstrates multiple benefits for the supply chain, including improved accessibility, adaptability, compatibility, control, and coordination. Amid globalization and increasing demand for just-in-time manufacturing and small-batch production, industrial digitization is significantly accelerating.

To overcome the challenges of implementing Logistics 4.0, decision-makers must understand the benefits of digital technologies and their impact on logistics operations. Big data analytics plays a crucial role in achieving this, as it not only improves visibility within the supply chain but also enhances trust among partners in the chain.

Business Intelligence: Supporting Decision-Making in Logistics

In the current competitive landscape, business intelligence systems are vital tools for companies to enhance decision-making processes and address various challenges. The vast amount of available information requires advanced systems to manage and utilize this data effectively. Business intelligence systems help transform raw data into actionable insights, enhancing organizational performance.

The features of business intelligence are numerous, such as improving access to high-quality data, enhancing data analysis, and improving decisions. Business intelligence systems also support the creation of dashboards to monitor key performance indicators, facilitating evaluation and strategic decisions.

However, the successful implementation of business intelligence systems requires effective integration between organizational culture, processes, and technology. These systems are not just tools; they are also processes that contribute to achieving organizational success. The effective use of business intelligence technologies can significantly impact the overall performance of the company.

Decision Making

The Strategic Decision in Implementing Business Intelligence Systems

The process of making strategic decisions is one of the fundamental components in the success of any organization that relies on Business Intelligence (BI) systems. The main challenges in implementing these systems lie in the resistance from organizational culture, which often arises from reluctance to change established practices. This challenge is accompanied by a range of concerns related to employability and job security due to technological advancements. Carvalho (2019) notes that realizing the benefits of BI systems requires a strong analytical organizational structure that can support effective decision-making processes.

It is essential to understand that investing in BI systems can be complex, as the benefits are often intangible, such as improving existing processes, making it difficult to calculate the return on investment. AbuQari and Jook (2003) emphasize the importance of addressing the barriers that hinder the success of BI systems, which include isolated departments that obstruct the formation of a data warehouse, as well as misestimations of the benefits of data and information. For instance, failing to estimate the potential benefits of data analysis by manufacturing companies can lead to the failure of BI projects. Brumac (2008) highlights the importance of good planning to avoid the mistakes of the past, as failure to plan can result in the loss of significant improvement opportunities.

Organizational responsiveness plays a crucial role in the success or failure of systems. If the organization possesses an open culture towards change, the implementation plans will be more successful and yielding. However, if there is significant resistance from employees, the likelihood of project success diminishes, and management must proactively address these obstacles.

Types of Analyses Derived from Business Intelligence Systems

Business Intelligence analytics can be applied in various areas throughout the business lifecycle, providing valuable insights for organizations. Studies conducted by Olszak and Zimba (2007) and Williams and Williams (2007) illustrate how profitability analysis, for instance, can lead to improved marketing and sales strategies. By analyzing historical sales data across specific products, companies can assess the profitability of these products and identify any deviations that may occur in sales compared to what was expected. This analysis is used to enhance marketing campaigns and strategic directions.

Customer relationship analysis provides strong evidence of the potential to improve customer loyalty. By using historical order and satisfaction data, companies can evaluate the performance of customer support services and subsequently improve processes based on the findings. This type of analysis is vital, as it shows how small differences in service delivery can impact customer retention rates.

Strategic planning and financial control are additional components of BI analytics. By utilizing accounting data on income and expenses, analyses can be conducted to reveal budget variances, financial aging of accounts, and revenue trends. These analyses help organizations improve budgeting and forecasting processes, thereby directing financial resources more effectively.

SWOT Analysis for the BI Systems Industry

Conducting a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) is a useful tool for understanding the challenges and opportunities faced by the industry when implementing BI systems. Strengths include data-driven decision-making, improved efficiency, and competitive advantages. For instance, an advanced BI system in a manufacturing company can aid in reducing production costs and thus improve profitability.

On the other hand, weaknesses such as high implementation costs, data quality issues, and employees’ ability to adapt to these systems are tested. This point is crucial, as any system can become an obstacle if a supportive technical infrastructure and trained staff are not available. Therefore, providing adequate training becomes a priority for any organization intending to implement a BI system.

However,
opportunities may relate to the growing demand for data analysis and technological advancements, as well as the opportunity to expand into new markets. Threats relate to issues such as data security concerns, rapid changes in technology, and market competition. All these elements indicate the balanced relationship that depends on how organizations manage these approaches and challenges.

Research Methodology for Data and Information Collection

The research methodology begins with the collection of necessary data and information to understand the fundamental concepts associated with artificial intelligence and modern digital technology. In this context, choosing the research methodology was critical. The Delphi method was chosen due to its effectiveness in analyzing the strategic impact of technology from a future-oriented perspective. The Delphi method is ideal for obtaining reliable insights from a group of experts, allowing the identification of factors influencing the success or failure of BI system implementations.

This methodology requires a repeated process of gathering opinions from a panel of experts, using a set of questionnaires for data collection. Through this process, the most consistent and accurate conclusions can be identified. In this case, there was a case study focused on a leading logistics operator in Portugal, which served as a link for implementing this methodology.

These studies aim to explore the benefits and challenges associated with the application of business intelligence systems. By applying the Delphi method, researchers can reach consensus among experts regarding insights and future directions. This approach ensures the collection of credible and diverse information, enhancing the quality of the research. Ultimately, the derived results contribute to outlining the technologies that companies should focus on to achieve success in information technology and artificial intelligence.

Questionnaire Division and Group Dialogue Management

The platform allows for the division of questionnaires into multiple sub-sections, which enhances the effectiveness of gathering opinions and feedback. A circular system was used to allow anonymous comparison of opinions, contributing to building group consensus among participants without the need for face-to-face meetings. Welphi provides a platform that supports asynchronous and interactive comparisons online, enhancing the sharing of ideas and individual opinions in a comfortable environment. Anonymity allows participants to adjust their initial positions based on group feedback, encouraging greater consensus. Participants can interact without needing to create an account or log in, facilitating access anytime using a link provided in the initial email.

This platform is ideal for gathering opinions from a large number of participants, especially those with busy schedules or geographically dispersed, as in the case of the relevant company. With offices distributed throughout Portugal, it would be challenging to gather all participants in one location on the same day. A distinctive feature of Welphi is the ability to create questionnaires and rounds, invite participants, establish rules for approval and rejection, develop response scales, and share results. Additionally, the platform automatically generates statistics for result analysis, making it easier to understand and analyze the extracted data.

These features help enhance the effectiveness of decision-making processes within organizations, providing a holistic view of employee opinions on various aspects of work. For instance, enabled managers to obtain employee opinions anonymously can open the door to more candid discussions about sensitive issues, increasing managerial effectiveness. This also provides valuable data that can be used to guide future strategies.

Delphi Method Implementation Process

The implementation of the Delphi methodology involves several organized steps, beginning with identifying the expert panel, developing the initial questionnaire, and initiating preliminary communications with experts to invite them to participate in the research. This is followed by distributing the first questionnaire and collecting responses, which are qualitatively analyzed, then preparing and distributing the second questionnaire with comments and feedback. The final step involves collecting and analyzing responses to the second questionnaire and conducting a comparative analysis of the responses from both rounds.

It requires

The first stage involves carefully selecting participants so that each of them represents a specific area within the company, such as logistics, transportation, finance, and innovation. Opting for 61 participants, rather than the 180 originally proposed, is a decision that reflects recommendations for the group of participants in Delphi studies, which prefer numbers ranging from about 10 to several dozens. It is preferable for selected experts to have relevant knowledge and experience and to possess the ability to work effectively and communicate well.

Regarding the development of the questionnaire, previous available literature was used to conduct semi-structured meetings to ensure the comprehensiveness of questions. The questionnaire was designed to take into account the available time and the burden of questions, and the vision was divided into five distinct dimensions, with each dimension containing a set of statements that reflect different aspects of the research. A five-point Likert scale was used to measure participants’ agreement with various statements, facilitating the effective application of the methodology.

Selection of Experts and Development of the Questionnaire

The process of selecting experts begins with understanding the research needs and requirements, identifying the main areas that will be covered by the questionnaire. In this case, five key areas focusing on the development of business intelligence (BI) tools and interaction with them were identified. The goal is to select participants who have the ability to provide important insights on how these tools impact the performance of different departments. Selecting experts requires evaluating criteria such as eligibility, knowledge, and ability to participate.

After selecting the experts, the process of developing the questionnaire arises. Statements for polling opinions are prepared by reviewing literature and communicating with experts in semi-structured meetings. To ensure that participants are not overwhelmed, the questionnaire is divided into sub-dimensions, with each dimension including between three and six statements. The questions are carefully designed to reflect the wishes and opinions of employees regarding the impact of business tools on their various work areas.

The great attention to the details of the questionnaire stemmed from the focus on ensuring that the content of the questions is locally appropriate, thus it was written in Portuguese. This was a step to remove any barriers that might hinder employees’ understanding. The first round of responses was conducted over more than a week, while the second round was condensed within a similar time frame to enhance the ability to gather effective feedback in a reasonable time.

Communication with Experts and the Distribution Process

The process of communicating with experts began with a phone call, followed by an email to the company’s communications department. The purpose of the research and an invitation to participate were clearly detailed. This approach, reflecting professionalism and seriousness in handling the issue, gave the document value to the participants. Through these communication efforts, a channel for dialogue with the interested parties was opened, arranging the necessary meetings to discuss the study’s details and working mechanisms.

As communication approached the final stage, consecutive talks were held using Teams technology to ensure a complete understanding of the procedures. This demonstrates the importance of using modern technology to expedite communication and information exchange between the involved parties. The details of the questionnaire participants were communicated, and their procedures were confirmed, with each participant receiving a carefully crafted electronic invitation to begin completing the questionnaire.

Upon receiving the invitations, there was a need to arrange the surrounding environment for each participant, as different work and professional conditions can affect how they respond to the questions. Therefore, it was important to create a comfortable environment for all participants to help obtain honest and realistic responses. The time and place available for each participant play a crucial role in opening discussion areas regarding their responses. We conclude from this process that effective methods must be used to attract users and guide them on how to provide the required information.

Collection

Data Using the Welfi Tool

The Welfi tool is considered an important instrument used for collecting data from experts participating in the study. This tool was designed to allow experts to complete the questionnaire at a time that suits them, which helps reduce direct interaction and mitigates any potential bias in their responses. The research included 61 participants from a selected company for the study. In the first round, 82% of the questionnaires were completed fully, reflecting a high level of participation. Meanwhile, the second round resulted in a completion rate of 90%, with questionnaires completed from 45 out of 50 distributed among participants.

The participants were distributed across various departments in the analysis, reflecting the diversity of expertise required to understand the overall impact of big data on business. For instance, there were 31 experts from the logistics department, 10 from the transportation department, 4 from the finance department, 4 from the innovation department, and one expert from central services. This diversity allows for multiple perspectives on how tools can report on the role of big data in enhancing managerial performance.

Delphi Survey Results: Round One

In the first round of the Delphi survey, responses from 50 out of 61 experts were examined. The results highlighted a set of statements that received the highest levels of agreement among participants, emphasizing the importance of data infrastructure and the BI platform. There was a consensus that investing in developing a data architecture is vital for leveraging information technologies through BI tools. Accurate data is also considered a fundamental element in achieving the desired success in decision-making. For example, it was emphasized that a lack of adequate communication regarding the internal news about the BI tool could lead to mixed results, affirming the importance of internal communications.

The comments provided by the experts in the survey indicated gaps in training on the use of BI tools, causing delays in adopting new technologies. One expert noted the necessity to manage managers’ expectations regarding the capabilities of BI tools, highlighting the importance of enhancing knowledge and good training to increase the effectiveness of these tools. This requires ongoing collaboration between project teams and qualified users to ensure that success indicators align with the individual needs of each department.

Conclusions from the Second Round of the Delphi Survey

In the second and final round of the Delphi survey, participants were limited to those who completed the questionnaires in the first round. Although the number of participants was reduced to 45, most provided reliable responses. The results showed a significant increase in the level of agreement among participants, reflecting the success of the method in reaching unified conclusions. Discussions focused on the implications of previous results and the foundations of the necessary environmental data architecture to improve the company’s responsiveness to rapid changes in the competitive market.

By tracking changes in participants’ responses over time, there is a tangible advancement in the overall understanding of the company’s relationship with new technology. Recommendations made by some experts centered on the urgent need to handle BI systems with greater flexibility and to leverage user insights to improve existing systems. Techniques such as pilot testing and extended approval cycles play an important role in the credibility and effectiveness of BI models.

Challenges Associated with Implementing BI Tools

Despite the benefits that BI tools can achieve, there are challenges that need to be addressed. These applications are often evaluated according to multiple difficulties related to data management, information inaccuracy, and the internal work environment that hinders overall benefit. Some participants pointed out that using BI in project management can enhance capabilities but requires more support to be effective. For example, organizing multidisciplinary teams and opening channels for effective communication are critical steps towards improving implementation.

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During the evaluation of various experiences, it was found that the impact of big data is not only related to technology but also to how this data is used to enhance different business models. This requires a deep understanding of the company’s strategic goals and how BI tools can support those goals. For example, if users lack the basic knowledge of how to utilize the data aggregated from BI, it will be difficult to achieve the expected benefits. Therefore, education and training provide the necessary foundations for effective use.

The Effectiveness of the Delphi Method in Achieving Consensus

Qualitative research methods, such as the Delphi method, are considered effective tools for gathering opinions and ideas from a diverse group of participants. This approach enables the achievement of consensus among opinions and fosters effective communication around a specific topic. By conducting multiple rounds of surveys, this allows researchers to analyze shifts in perspectives and measure the level of agreement on a specific subject. In this context, the effectiveness of this method is highlighted by deriving the strengths and weaknesses in supporting Business Intelligence (BI) technology across various fields.

The data extracted from the participants in the first and second rounds were analyzed, showing an increasing focus on the importance of BI technology in project management and IT consolidation. The affirmation of participants who use BI tools daily regarding these dimensions reflects the potential positive impact of this technology on institutional performance. The significant progress in the levels of agreement among opinions from round to round demonstrates how organizations can benefit from directing their investments and improvements based on clear data.

Furthermore, the continuous increase in the level of agreement regarding the use of technology as a fundamental condition for market competition, as support rose to 73%. This increase reflects the growing awareness of the importance of technology in maintaining competitive advantage, indicating a shift in the general attitude towards the BI project.

The Importance of Project Management and IT Consolidation

Project management and IT consolidation represent a vital aspect of enhancing the effective use of BI tools. Participants show an increase in agreement regarding the clear benefits of BI technology, reinforcing the importance of the actual application of these tools for various purposes. At this stage, companies are directing their resources towards ensuring a shared understanding of project values among different departments.

In light of the analysis, it is evident that the rising level of support for the statement affirming that “top management will be aware of the benefits of this new technology” indicates a development in leadership concepts in this field. This reinforces the urgent need for executives to recognize the dynamic changes in the business environment. The instability of technology requires top management to be more open and engaged with these areas to enhance the technological domain within the organization.

As evident from the data collection, companies need to work on establishing consistent strategies between current business strategies and future BI projects. Teams across the rounds recognize that this strategic link will lead to improved processes and value generation. Achieving harmony with overall technology through project management consolidation is what makes BI an effective and key element in driving desired outcomes.

Intent to Improve User Experience

User experience sheds light on how employees use the new BI tools within their working environments. Results from the rounds indicate that participants have witnessed an improvement in their attitudes towards the possibility of integrating new technology into their daily work. One key factor is the seamless design of the tool, which has encouraged adherence and extensive use.

However, some issues remain, such as the lack of adequate promotion for the new tool among employees, which has affected their awareness of it. By highlighting the importance of public relations in attracting employees’ attention and convincing them to use the new technology, an opportunity is presented to increase user awareness. Overcoming this hurdle requires developing effective communication strategies and enhancing training courses to maximize the benefits of the technology.

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The order from upper management is not just to support technology but also to ensure the availability of the necessary resources to conduct training. Consequently, enhancing the user experience will lead to improved organizational effectiveness and pave the way for innovation and improved operational methods.

Effects of Smart Technologies on External Relations

External relations, such as those connecting the company with its clients, are expected to be influenced by BI technology, where data and analytics can be used to improve processes. However, teams face some challenges due to differing opinions on the utility of the tool for external use versus internal use.

While some believe that BI can enhance customer interaction, there are concerns about the feasibility of using technology to add value in business relationships. Through critical thinking, upper management should respond to these comments from participants. For example, the values of relationships between internal and external businesses can be enhanced by improving the flow of information and analytical methods.

It is clear that external pressure has become part of updating strategic visions regarding the intelligent application of BI technology. Once partnerships with customers are strengthened, the transformation resulting from these smart systems will have a tangible impact on how businesses operate. Innovating and updating technologies is essential to respond to anticipated customer needs.

Importance of Business Intelligence Indicators in Company Development

In a rapidly changing technological era, Business Intelligence (BI) represents a vital tool that empowers companies to remain competitive. Key Performance Indicators (KPIs) help companies measure performance and make informed decisions. These indicators, such as Return on Investment (ROI) or inventory turnover rate, provide valuable insights into actual performance compared to set goals. If companies effectively rely on Business Intelligence indicators, they can quickly identify areas for improvement and build strategies based on concrete data.

However, the importance of BI indicators is not limited to measuring performance, but also includes their ability to track trends and forecast future outcomes. Companies that effectively utilize BI can benefit from predictive analytics to understand customer needs before they emerge, allowing them to adapt to the market more effectively. Simply put, if historical sales data indicates an increase in demand for a specific product, the organization can ramp up production before its competitors catch on to this trend.

Highlighting the importance of BI also includes the necessity of investing in skills development and training for employees in this field. Training employees on Business Intelligence tools and techniques is a critical aspect of maximizing benefits. If a company views employee skill development as a tool for attracting and motivating talent, it will also lead to improved collective performance.

Additionally, companies face challenges in communication when it comes to using BI. In many cases, a lack of knowledge among employees regarding Business Intelligence techniques can be a significant barrier. In a negative scenario, this could result in ineffective reliance on data or even decisions based on inaccurate information. Therefore, it is important for companies to develop effective communication strategies and train employees on using BI.

Challenges and Limitations Associated with Business Intelligence Studies

Studying the effectiveness of Business Intelligence includes several challenges that require special attention. It is essential to recognize the limitations that may affect research conclusions. For example, research relying on case studies needs to be cautious when generalizing results. Circumstances and contexts may vary among companies, which could provide an inaccurate picture if results are applied randomly.

When

the complexities of supply chain management where opportunities and challenges coexist. As businesses strive to enhance efficiency and responsiveness, they face obstacles that require innovative solutions. One of the key challenges is maintaining a balance between supply and demand, particularly in an ever-changing market.

Furthermore, the globalization of supply chains introduces additional layers of complexity. Companies must navigate varying regulations, cultural differences, and fluctuating economic conditions across different regions. This necessitates a thorough understanding of local markets and strategic partnerships to ensure smooth operations.

On the other hand, advancements in technology present significant opportunities for improvement. For instance, the adoption of blockchain technology can enhance transparency and traceability throughout the supply chain. This fosters trust among stakeholders and mitigates the risks associated with fraud and errors.

Additionally, leveraging big data analytics can empower companies to make informed decisions based on real-time information. By analyzing patterns and trends, organizations can anticipate potential disruptions and proactively address them, thus minimizing their impact on operations.

التوجه نحو الاستدامة في سلاسل الإمداد

في السنوات الأخيرة، أصبح التوجه نحو الاستدامة جزءًا أساسيًا من استراتيجيات إدارة سلاسل الإمداد. تتطلب الضغوط الاجتماعية والبيئية من الشركات إعادة تقييم ممارساتها لتقليل بصمتها الكربونية وتعزيز استخدام الموارد المتجددة. يتطلب ذلك الاستثمار في تقنيات صديقة للبيئة وتطوير شراكات مع موردين يشاركون في نفس الالتزامات.

علاوة على ذلك، تؤدي الضغوط لتحقيق الاستدامة إلى الابتكار في نماذج الأعمال. على سبيل المثال، بدأت الشركات في اعتماد نماذج اقتصاد دائري تتضمن إعادة استخدام المواد وإعادة التدوير، مما يساهم في تقليل الفاقد وتعزيز الكفاءة.

في النهاية، بالرغم من التحديات، فإن الفرص المتاحة في إدارة سلاسل الإمداد تتطلب من الشركات مواجهة هذه التحديات بفعالية من خلال تبني ممارسات جديدة وتعزيز الابتكار. التعاون مع الشركاء والالتزام بالاستدامة يمكن أن يدفع بالتميز التنافسي ويساهم في النجاح على المدى الطويل.

The Fourth Industrial Revolution presents a range of opportunities and challenges facing supply chain management. Supply chains have become more complex, with increased reliance on global partnerships and international e-commerce. This reality requires effective management and integration among various stakeholders, including suppliers, producers, and distributors.

One of the main challenges is the continuous assessment of risks threatening the supply chain. Many companies struggle to identify potential risks such as political changes or natural disasters that could adversely affect the continuity of operations. Therefore, companies need to adopt flexible strategies that allow them to quickly adapt to such crises.

Furthermore, the importance of advanced analytics in risk management is increasing. Companies like Deloitte and Forrester highlight the importance of using data to enhance decision-making processes in supply chains. By utilizing accurate and reliable data, managers can take proactive steps to mitigate risks rather than waiting for problems to occur.

Technology and Business Data as Key Drivers

Data acts as a strategic tool in the information age, serving as a pivotal factor in providing valuable insights regarding a company’s operations. Big data technologies enable organizations to collect and analyze vast quantities of data, offering them accurate information about customers and markets. These modern sciences assist companies in making evidence-based decisions and analytical reports.

This data also supports quality control processes and improves procedures. By using data-driven business management systems, companies can track performance across various departments, making it easier to identify strengths and weaknesses. For example, a food company can use analytical data to gauge customer satisfaction with a particular product and adjust the recipe if necessary.

In parallel, business intelligence solutions contribute to accelerating critical decision-making. For instance, BI (Business Intelligence) tools are not only useful in aggregation but also in providing deep analytics and performance forecasting. Companies that invest in these areas show better performance results compared to those that do not use these tools.

The Importance of Effective Leadership in Organizational Transformations

Leadership is a crucial element in the success of any organizational transformation, especially in complex contexts like the shift to Logistics 4.0. Innovation demands leaders who can motivate teams and create a work environment conducive to creativity and initiative. Leaders must be pioneers not only in guiding change strategies but also in fostering an organizational culture that supports technology adoption.

Research highlights the importance of transformational leadership, which is pragmatic and characterized by the ability to inspire others toward new visions. Leaders who embrace this type of leadership can build teams more capable of meeting market challenges and achieving strategic goals.

Moreover, research shows that encouraging continuous training and skill development is a pivotal factor in the success of technological transformation. Companies that invest in training their teams and enhancing their technical skills position themselves favorably to confront technological challenges. For instance, specialized training courses in big data can enable companies to enhance employee efficiency and increase their loyalty.

Source link: https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2024.1469958/full

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