American Journal of Research in Humanities and Social Sciences ISSN (E): 2832-8019 Volume 30, | November - 2024 P a g e | 5 www.americanjournal.org DATA-BASED LEADERSHIP AND ITS IMPACT ON IMPROVING THE PERFORMANCE OF SPORTS ORGANIZATIONS-ANALYTICAL STUDY HF OR THE OPINIONS OF A SAMPLE OF WORKERS IN THE NAJAF YOUTH AND SPORTS DIRECTORATE Assistant Lect. Murtaza Khachi Hayyawi Department Business of Administration, College of Administration and Economics, University of Misan, Amarah, 62001, Misan, Iraq. murtadha.k@uomisan.edu.iq Assistant Lect. Mohammed Hammadi Jaber AL-bakhati Department Business of Administration, College of Administration and Economics, University of Misan, Amarah, 62001, Misan, Iraq. E-mail: mohammed.hamadi@uomisan.edu.iq Assistant Lect. Afrah Baqer Abdul Jaleel College of Physical Education and Sport Sciences – University of Kufa E-mail: afraib.hashim@uokufa.edu.iq A B S T R A C T K E Y W O R D S This study aims to investigate the impact of data-driven leadership on performance in sports organizations focusing on Najaf's General Directorate of Youth and Sports in particular Questionnaire (100 questionnaires) on leadership practices of data use and impact on performance of sports organizations was distributed to the staff of the General Directorate of Youth and Sports in Najaf (88) questionnaires were collected, (88) validated questionnaires for statistical analysis, (85) . questions were Smart Analyzed using PLS V.4, the study also found a list of results, the most important of which were: There is a relationship between improving performance, and this is an important finding well. Data-driven leadership is not a magic bullet, but it is a powerful tool that can dramatically improve organizational performance and decision- making. By creating a culture of data consumption, putting data insights to good use, and prioritizing data literacy, leaders can overcome today’s challenging business environment and achieve sustainable success Several recommendations are made, including: Educate employees and stakeholders about the importance of data, its use in order to improve performance and performance. Data-driven leadership, sports organization performance. American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 6 www.americanjournal.org Introduction Data-driven approaches in modern sport management have emerged as a key to improving organizational performance. This study focuses on the relationship between data-driven leadership and improvement in the performance of sport organizations, specifically examining the perspectives of officials from the General Ministry of Youth and Sports in Najaf Data-driven leadership has become critical to organizational performance in today’s rapidly evolving business environment. Data-driven decision-making deals with using data and analytics to guide and inform strategic choices, creating a culture where data-driven insights play a central role in organizational design, and manage, and analyze in The game landscape is evolving rapidly, with more leaders guiding their decisions using data analytics. Data-driven leadership refers to the use of data and analytics to inform strategic, operational, and strategic decisions within an organization. In sports, this approach involves using performance indicators, player statistics, and other relevant data to gain insights that lead to more informed and effective decisions This introduction paves the way for exploring the important intersections of data-driven leadership and organizational performance. As we delve deeper into this dynamic relationship, we’ll explore how leaders can effectively use data to improve strategic planning, improve productivity, spur innovation, and ultimately for organizational effectiveness in an ever-evolving business environment. The Youth Sports Agency in Najaf provides an interesting setting for this study, as it provides a snapshot of the broader sport governance environment. By surveying their employees’ perspectives, understand Pay this This is the survey to uncover the ideas, challenges, and potential benefits associated with adopting data-driven leadership practices. The first axis Methodological framework of the study Introduction The study of the relationship between data-driven leadership and organizational performance involves a comprehensive methodology for collecting, analyzing, and interpreting relevant data. The proposed study methodology is as follows: First: The problem of the study Data-driven leadership is a powerful tool that can help sports organizations gain a competitive advantage. By using data to guide decision-making, improve performance, and increase fan engagement, organizations can achieve success on and off the field. From the above, the following question can be raised: What is the impact of data-based leadership in improving the performance of a sports institution? Second: Study objectives That The primary objective of this study is to examine the relationship between data-driven leadership and performance outcomes of sports organizations. Specifically, the research seeks to: 1. Identify the key components of data-driven leadership in the context of sports organizations. 2. Assessing the current level of adoption of data-driven decision-making in sports leadership. 3. Study the impact of data-driven leadership on key performance indicators, such as team success, player development, and financial performance. American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 7 www.americanjournal.org 4. Explore The challenges and barriers faced by sports organizations in implementing and adopting data-driven leadership. 5. Provide recommendations for the effective integration and use of data-driven approaches in sports leadership. Third: The importance of the study The study seeks the findings of this research will shed light on the role of data-driven leadership in shaping the performance of sports organizations, and provide practical insights for the Directorate of Youth and Sports in Najaf. By understanding the perspectives of workers on the ground, the study aims to provide actionable recommendations to enhance the effectiveness of data-driven strategies, and ultimately contribute to the overall success and advancement of sports management practices within the region. Fourth: Study hypothesis The main hypothesis of this study is that “there is a positive relationship between the adoption of data- driven leadership practices in sports organizations and overall performance improvement.” Fifth: Study model The study model consists of two variables: the first is data-based leadership, which represents the independent variable, and the second is the performance of sports institutions, which represents the dependent variable, as follows: Figure (1) Hypothetical study model Figure (1) Hypothetical study model The second axis Theoretical framework of the observe First: The concept of data-driven leadership Data-driven leadership is a technique to selection-making and management that is based closely on the evaluation and interpretation of statistics. In this management style, selections are based totally on facts Data-driven Leadership Analytical thinking and decision-making based on data Continuous learning, adaptation, and technology integration Risk Management Data ethics Management of sports organizations Performance scheduling Cost of performance quality performance Stakeholder satisfaction American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 8 www.americanjournal.org and proof, as opposed to relying completely on instinct and revel in. This method has come to be increasingly more popular as agencies recognize the fee of the usage of facts to benefit perception, make knowledgeable decisions, and power better enterprise effects.(Corsair's 2017: thirteen).Data- pushed leadership is not about putting off intuition and enjoy, however approximately combining the energy of statistics and analytics to decorate selection-making. This requires a cultural shift within an organization wherein records is valued and leaders and employees are empowered to make evidence- based selections. Data-pushed management is defined as a commitment to the usage of information to attach an business enterprise to its clients, pressure measurement and accountability, and guide useful resource allocation. (Hamash, et al, 2022: 24(. As defined Leadership Standa On records On it A management style that leverages data insights to manual selection-making, method, and universal organizational performance.(Schmidt, et al, 2023: 298). Second: Characteristics of a data-driven leader The leader will stand A data-driven person is someone who relies on data and analytics to inform decision-making and drive organizational success. This method entails amassing, reading, and decoding relevant facts to obtain statistics and make informed selections. (Bratasano, 2018: 4). Here are some of the key characteristics and practices associated with data-driven leadership: (Schmidt, et al, 2023: 299-300) 1. Analytical Skills: Data-driven leaders have strong analytical skills to understand and interpret complex data sets. They can identify patterns, trends and interrelationships that are essential for making informed decisions. 2. Data collection and management: Priority Collecting and organizing the right information ought to be prioritised. This involves; Data quality, Data accuracy, Data completeness in order to allow quantitative analysis. 3. Technological proficiency: Technophile means that leaders are not hesitant to work with technologies and tools used for data-driven tasks. They frequently incorporate platforms, including machine learning and artificial intelligence, to get better perspectives. 4. Objective decision-making: Instead of going with instincts or hunches to make the decisions, data driven leaders rely in facts and figures. This reduce bias and subjectivity inherent in most decision making activities and procedures. 5. Continuous Learning: Indeed, technology and data analytical tools are proving to be dynamic, so training is important. These keep up to date with the advances in Data science and analytics. 6. Clear communication: Data-driven leaders are in essence skilled communicators precisely in terms of communicating data in a comprehensible manner to different stakeholders. This helps organizational understanding and acceptance. 7. Risk Management: They employ data to identify threats, and risks and to formulate avoidance or minimization strategies appropriately. Instead of going through uncertainty, they will understand the challenges and opportunities from the data analysis and prevent uncertainties by making necessary decisions. 8. Performance Measurement: Managing processes with data involves defining KPI’sKPI’s and then continually monitoring organizational performance against those indicators. Such enables tracking of the amount of progress and also which strategies should maybe be altered. American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 9 www.americanjournal.org 9. Collaboration: Therefore, when working in a data-tized environment, collaboration is a necessity. Managers collaborate with data scientists, information technology specialists, and others who will be using the data in the organization. 10. Agile Decision Making: Adaptive approach; The leaders who use data in order to make appropriate decisions are able to change their ways of doing things. They are in a position to quickly adapt to change because they can use data from the field in real-time. Adopting a data-driven approach requires a cultural shift within an organization, with leadership playing a pivotal role in driving the importance of data and analytics. By fostering a culture focused on data-driven decision-making, leaders can set their organizations up for greater efficiency, innovation, and success in a data-driven world. Third: Dimensions of data-based leadership Data-driven leadership refers to the use of data and analytics to inform decision-making and guide leadership practices. Leaders who embrace a data-driven approach use information and insights to make more informed, objective, and strategic decisions. (Windt , et al, 2019:8) Here are several key dimensions or aspects of data-driven leadership:(Hamash, et al, 2022:: 27) 1- The thinking the My analysis And take Data-driven decision making Analytical thinking represents Ability to interpret and analyze data to extract meaningful insights. so Data-driven leaders have strong analytical thinking skills, enabling them to understand complex data sets and draw relevant conclusions. and that Make strategic decisions backed by data rather than relying solely on intuition or experience. Where he does Data-driven leaders prioritize data in their decision- making processes, using it to validate assumptions and mitigate risks. 2- Continuous learning and adaptation and Technology integration Embrace a culture of learning and adapting based on insights gained from data.so Data-driven leaders encourage a culture of continuous learning, where teams use data to identify areas for improvement and adapt strategies accordingly. and that Integrating technology tools and platforms to enhance data collection and analysis. As it can Data-driven leaders keep up with technological developments, ensuring their teams have the right tools to efficiently collect and analyze data. 3- Risk management It means Use data to identify potential risks and develop strategies to mitigate them.so Data-driven leaders proactively identify and address risks by leveraging data insights, contributing to more effective risk management. 4- Data Ethics Ensure that data collection and use complies with ethical standards and regulations. so Ethical considerations are a priority for data-driven leaders, ensuring that data is handled responsibly and in compliance with relevant laws and regulations. American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 10 www.americanjournal.org The second topic Theoretical framework of the variable of performance of sports organizations First: The concept of performance Performance is One Administrative terms are almost the most common term in the literature of various administrative sciences, as most writings deal with it directly or indirectly, considering it to represent the basic objective that All departments of public, private and joint organizations sought to improve it. Given Because it is important because it reflects the level of success you achieve or seek to achieve. Organizations, Therefore, defining its concept remains an urgent necessity. And the problem of great importance to managers in these organizations and researchers. Some people link performance to the overall performance of the organization. This is because they only look at performance from the perspective of operational dimension indicators, especially financial dimension indicators, and they overlook indicators that measure profitability and return on investment.(Bahr and Abu Suwairh, 2010: 6). The performance corresponds to the Latin pronunciation language. Performer "that gives shape to something what, Which I derived the English word from it. Performance" that It means the work achievements or how the organization achieves it. Its goals.(cheap,2005: 86) difference (Tomas) when he addressed the concept of performance both as Behavior, And achievement, and performance, Behavior is the activity carried out by agents in one of the organizations. In this regard, Such as holding meetings, Execute the activities and tasks assigned to them, and everything else they do in order to complete the tasks assigned to them, Achievement refers to the impact or the state that persists when people are no longer acting or performing a specific behavior. The job, As the end product of work and their actions, Performance is the relationship between behavior. And achievement, It is not behavior alone or achievement alone, but rather the integration of both (Al-Jihan, 2009: 57). Known (Humaidi, & Asarani, 2012: 770) Performance of the System As it meets cost and time targets and adheres to product specifications.at. As Organizational performance refers to the overall effectiveness and efficiency of an organization in achieving its goals and objectives. It is a broad concept that encompasses various aspects of an organization’s work, including financial health, operational efficiency, employee satisfaction, customer satisfaction, innovation, and strategic alignment. Analyzing and improving an organization’s performance is critical to long-term success and sustainability.(Adula, 2022: 132). Second: Performance dimensions He specifies The dimensions of the organization’s performance are as follows: (Ahmed & Anantatmula, 2017) 1- Performance scheduling Schedule performance has a concrete effect on the projects and its results are critical to evaluating assessed project performance. The schedule is one of the time-related factors that impact project performance since it involves many stakeholders’ interactions during the project and these interactions also, consume time. Schedule performance followers are many and include the schedule estimate, the schedule control mechanisms, the quality estimate, design documents, environmental factors, project management, and leadership skills that result in schedule changes.(Ahmed & Anantatmula, 2017: 3). American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 11 www.americanjournal.org 2- Cost of performance The cost is One The most important goals that most organizations focus on to achieve high and distinguished performance, as they seek through low-cost operations to provide a service or produce a product at the lowest possible cost in order to satisfy external and internal customers. Reducing prices leads to an increase in demand for products or services, but it works to reduce the profit margin if it is impossible to produce the product or service at a lower cost (Krajewski, et al.,2007:51) Costs not only affect project efficiency, but also have a significant impact on project stakeholders. Similar to schedule performance, cost performance is affected by poor project planning, poor cost estimation, and ineffective cost control mechanisms, leading to project budget revisions.(Ahmed & Anantatmula, 2017: 4). 3- Quality performance However, performance quality is another performance characteristic that may affect the performance of a project. The project’s performance quality refers to the aesthetic, functionality and legal conformance of the project and the project outcomes. While project requirements can be simple, they can also be complicated. Quality is realized when: the end product can be described or when the end product actually embodies the specified standard. In exploring how project performance can be enhanced, it will be significant for project managers to pay attention on the quality standards provided by the project activities and processes. (Ahmed & Anantatmula, 2017: 5). Care about Organizations All of them have quality as an important and basic goal as it means "doing things right" but the things that the process needs to do right must be appropriate for the type of process. Perception Customer satisfaction with high quality products and services means that there is a strong possibility of customer return. It is an important and major influence on customer satisfaction. Customer dissatisfaction, and quality within the process means continuing to produce products and services with certain characteristics. This will not only lead to customer satisfaction, but also make the business EasierInside operations (Slack, et al., 2014:45) 4- Stakeholder satisfaction Dissemination of information and cooperation with all levels of stakeholders is highly important in terms of project success. Project managers can only finally assess project performance after the client or customer receives and uses the project results, indicating the successful completion of the project. Beyond cost, time, and quality specifications, it is essential for project managers to prioritize customer benefits, stakeholder expectations, and customer needs. During the initial planning phase, project stakeholders clarify their requirements, while their expectations are clarified throughout the implementation phase. Both cost and time play a critical role in influencing project efficiency and stakeholder interests.(Ahmed & Anantatmula, 2017: 6). The third axis The applied aspect of the study The first topic Coding variables and dimensions The variables and dimensions will be coded for ease of analysis of the research sample data. My agencies: American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 12 www.americanjournal.org Variable code The dimension code Data-driven leadership X Analytical thinking and decision making based on data X1 Continuous learning, adaptation and technology integration X2 Risk Management X3 Data ethics X4 Performance of sports organizations Y Performance scheduling Y1 Cost of performance Y2 Quality performance Y3 Stakeholder satisfaction Y4 The table was prepared by researchers Descriptive analysis of study variables Table (1) gives a descriptive analysis of the scale where the measure of central tendency used is the weighted arithmetic mean, along with the standard deviation to assess the dispersion of the data. The results from the weighted arithmetic mean indicated that each paragraph related to the independent variable, data-driven leadership, exceeded the hypothetical mean (3) on a three-point Likert scale. This means that all paragraphs and the overall variable are prevalent within the organization under study, although still below the required level. Similarly, the paragraphs related to the dependent variable, sports organization performance, also exceeded the hypothetical mean, indicating their prevalence within the organization under study, while remaining below the required level. Furthermore, admittedly, in the descriptive analysis, there were very low figures of standard deviations and variation reducing the variability of the scores indicating the respondent’s good understanding of the paragraphs. Table (1) Descriptive statistics for study variables Variable The dimension Paragraphs Arithmetic mean standard deviation variance Data-driven leadership Analytical thinking and decision making based on data X11 3.34615 1.43521 2.06 X12 3.26923 1.54509 2.387 X13 3.13462 1.4549 2.117 Continuous learning, adaptation and technology integration X21 3.28846 1.48086 2.193 X22 3.51923 1.66893 2.785 X23 3.36539 1.56418 2.447 American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 13 www.americanjournal.org Risk Management X31 3.51923 1.59923 2.558 X32 3.25 1.48086 2.193 X33 3.25769 1.52172 2.316 Data ethics X41 3.26923 1.5858 2.5203 X42 3.15385 1.4627 2.1521 X43 3.11923 1.29958 1.689 Performance of sports organizations Performance scheduling Y11 3.01923 1.38659 1.923 Y12 3.19231 1.29958 1.689 Y13 3.26539 1.39514 1.946 Cost of performance Y21 3.15385 1.50211 2.256 Y22 3.26923 1.54509 2.387 Y23 3.15385 1.4627 2.1521 Quality performance Y31 3.19231 1.66893 2.785 Y32 3.26923 1.5858 2.5203 Y33 3.25769 1.52172 2.316 Stakeholder satisfaction Y41 3.25 1.48086 2.193 Y42 3.21154 1.68569 2.842 Y43 3.10385 1.70369 2.903 Source: Prepared by the researcher based on the program outputs Smart PLS V.4 The second topic Structural model evaluation and hypothesis testing Based on the data collected in this study, the researcher aims to test the hypotheses advanced in the current study which encompass the hypotheses of association and those that pertain to direct and indirect effects on the key variables and their sub-constructs. To test the hypotheses, the researcher used a set of precise educational methods. Therefore, this section is organized into two main paragraphs: the first paragraph focuses on testing the hypotheses of association, while the second paragraph deals with examining the hypotheses of direct effect, as shown below: Firstly: a test Relationships Link This paragraph consists of testing the first main hypothesis, which is as follows: It says it: There is a direct relationship between data use in management and organizational performance. Institutions Sports To prove the validity of this assumption, Table No. (2) indicates that. The correlation analysis depicts that data-based leadership has a strong positive relationship with the performance of the sports organization, and that the value of the correlation coefficient between the two reaches (0.01) at a significant level of (0.741). From the acceptance of the first main hypothesis and with rejection of the null hypothesis, there are five sub hypotheses which can be derived from this hypothesis, which are: American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 14 www.americanjournal.org 1. Having a relationship correlation Positive and significant between Analytical thinking and decision making based on data and performance of sports organizations: The correlation matrix in Table (2) shows that there is a significant positive correlation between data- based analytical thinking, decision-making, and the performance of the sports organization. The value of the correlation coefficient reached (.676). The significance level was (1%), which From the above indications, it can be concluded that the availably of all the key research requirements affirms the hypothesis. First Always reject the null hypothesis. 2. There is a positive relationship between continuous learning, diversity, technological integration, and performance in sports companies. Table No. (2) of the correlation matrix also indicates that there is a meaningful positive relation between continuous learning, adaptation, technological integration, and the performance of sports organizations, as the value of the correlation coefficient reaches (0.629) at a significance level of (0.01), This one also supports the second sub-hypothesis along with the non-acceptance of hyp Zero. 3. having a relationship correlation Positive and significant between Risk management and Performance of sports organizations: Table (2) of the correlation matrix shows a significant and positive relationship between risk management and the performance of sports organizations, as the value of the correlation coefficient reaches (0.690) at the significance level (0.01), which supports the validity of the third sub-hypothesis and rejects the hypothesis Zero. 4. having a relationship correlation Positive and significant between Data Ethics and Performance of sports organizations: The correlation matrix in Table (2) shows a significant and positive relationship between data ethics and the performance of sports organizations, as the value of the correlation coefficient reaches (0.648) at the significance Level (0.01) indicates that the third sub-hypothesis is correct and rejects the null hypothesis. Table No. (2) Correlation matrix between data-driven leadership and its dimensions and the performance of sports organizations X X1 X2 X3 X3 Y Pearson Correlation .741** .676** .629** .690** .648** Sig. (2-tailed) .000 .000 .000 .000 .000 N 60 60 60 60 60 Source: Program results SPSS v.26. 1- The impact Hypothesis is the second main hypothesis of the study. To test the hypothesis on any direct or indirect effect of any variable in this study, a Structural Equations Modeling was developed based on the participants’ responses, as revealed in Figure (2). American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 15 www.americanjournal.org Firstly: To test the second main hypothesis. The second major hypothesis is that (H2) that “there is a positive impact relationship between data- driven leadership and the performance of sports institutions.” In order to examine this hypothesis, the structural model presented in Fig (2) was constructed and the result was formed. They are shown in Table (3). Figure 2 shows the path model used in testing the second major hypothesis. Source: Program Outputs Smart PLs V.4 Table (3) The findings of assessing the second main hypothesis of the structural model Hypothesis Track Path parameter tValue pValue The result The coefficient of determinationR2 Adjusted R2 H2 X→Y 0.796 8.702 0 Acceptance 0.63 0.55 Source: Program Outputs Smart PLs V.4 Table No. (3) present the outcome of the evaluation of the structural model of the third main hypothesis with the path coefficient of 0.796, which complied with the value restrictions (T and P) and the adjusted coefficient of determination R2 (0.63) for the purpose of show Explanatory power. This indicates that the leadership variable in the database explains 63% of the sport organization performance variable (the rest are other factors not addressed in the model). Seconddly: The hypothesis is being tested. At Sub-hypothesis derived from the second main hypothesis. Below are the sub-hypotheses derived from the second main hypothesis.(H2-1, H2-2, H2-3, H2-4): H2-1: Product advertising has a positive effect on the performance of sports organizations. H2-2: Price deception has a positive effect on the performance of sports organizations. H2-3: There is a positive influence relationship. To deceive in promotionIn the performance of sports organizations. H2-4: There is a positive influence relationship. To deceive in promotionIn the performance of sports organizations. In order to test these hypotheses, the structural model in Figure (3) was built and Table (4) presents the test of structural model hypotheses against these hypotheses. American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 16 www.americanjournal.org Figure (3) The structural model for assessing the sub-hypotheses developed from the second main hypothesis. Source: Program OutputsSmartPLs V.4 Table No. (4) Analysis of the results of the evaluation of the structural model of the hypothesis as at Sub-hypothesis stemming from the second main hypothesis Hypothesis Track Path parameter tValue pValue The result The coefficient of determinationR2 Adjusted R2 H3-1 X1→Y 0.243 5.009 0 Acceptance 0.63 0.58 H3-2 X2→Y 0.225 4.243 0 Acceptance H3-3 X3→Y 0.269 6.875 0 Acceptance H3-4 X4→Y 0.263 5.975 0 Acceptance Source: Program OutputsSmartPLs V.4 Table No. (4) shows the results of evaluating the structural model for the sub-hypotheses derived from the second main hypothesis, where it was shown that the path coefficients for the three hypotheses (H2-1, H2-2, H2-3, H2-4) are significant and meet the required limits for T-value, P-value) (For the purpose of explanatory power, the adjusted R2 (0.63) indicating that the dimensions of data-based leadership variables explain (63%) of the performance of sports organizations (the rest are other factors that were not taken into account in the model). American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 17 www.americanjournal.org The fourth axis Conclusions and recommendations First: Conclusions The results of the study on data-driven leadership and its impact on improving the performance of sports organizations summarize the main findings and implications of the study, with a particular focus on the opinions of the employees of the General Directorate of Youth and Sports in Najaf. They are as follows: 1. This analytical study examines the role of data-driven leadership in improving the performance of sports organizations, with a particular focus on the General Directorate of Youth and Sports in Najaf. Responses gathered from the self-administered questionnaire provided important information from various aspects of the opinions of the organization’s employees. 2. It was seen that the practitioners have a certain level of understanding about the role of data in decision-making with specific reference to sports management. Survey participants agreed that data can be effective for providing information, planning, and generally improving the management and leadership of sports organizations. 3. Hence, the leadership of the sports organizations and the effects on performance drives the researchers to focus on data analysis. DD is not the panacea for leadership struggles, but it is a great tool that may have a considerable impact on the performance and decision-making of organizations. Three idea points for practical applications for the executive are to create a culture where data is valued, managing data properly as an essential business tool and focusing on improving data competency. Second: Recommendations In this context, data-driven leadership in sports organizations can be defined in simple terms as the exercise of managerial and administrative functions of an organization together with the proper utilization of data and analytics. Here are some recommendations for incorporating data-driven leadership to improve the performance of sports organizations: 1. The necessity for an organizational culture that encourages the use of analytics for decision-making at each company level. 2. It is also acknowledged that there is a need to educate the employees and other stakeholders concerning the value of data and how improvement can be achieved using data. 3. Investing in data infrastructure: 4. Build the organization’s data foundation for collecting, storing, and analyzing the related data. 5. Use adoption of technologies for the consolidation of information from divergent sources including player statistics, fan analytics, and financial performance. 6. It also contains elements in the determination of main indices which are oriented to the goal and/or objectives of an organization. Some of such components are; The efficacy of players, the level of participation by the fans, and profits that are realized. 7. TRegularly assess the relevance of key performance indicators and align them with organizational goals. 8. map out the relevance of the analytic approach to the process of players’ selection and acquisition. Player statistics, injuries, and other features to understand what players benefit the team and that it is worth using them in a team. American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 18 www.americanjournal.org 9. Necessity Employing predictive statistics to find top talent and possible future celebrities. 10. Importance Use technology and other work-related tools in assessing the performance of your players during training sessions and practices as well as during every match. 11. How evaluation can be useful Apply the data obtained to reveal possible weak points for the specific members of the team, and the team in general. 12. Compulsion Employ data to keep a record of the amount of work done by the players, potential risk of injury, and ways of preventing the risk of injury. 13. He should Implement injury prevention and rehabilitation measures that is gathered from data analysis to ensure efficient turnaround time in healing and/or minimizing player repeated injuries. 14. Many should be analyzing the Analyze fan data to develop a profile understanding of Analyze fans and their evaluative criteria, Analyze behavioral tendencies, and measure engagement levels. 15. Utilise advanced analytics in the marketing strategies and concepts to improve fans’ satisfaction and hence make fans loyal to the firm. 16. Use data while making optimal choices of which of the programs to support with funds, which sponsorships to embark on, and what ticket prices to charge. 17. He should Analyze data to identify revenues and analyze data to look for potential cost-saving avenues. 18. Necessity Foster a culture of change proactivity driven by data. 19. There is a need to undertake a coordinated check on the steps undertaken, measures accomplished and together with, and successes and failures, and change the strategies based on these findings. 20. This call implies putting in place strict measures for handling and disseminating data, especially sensitive information. 21. Should As sure as shooting to adhere to any applicable regulations that have been put in place on data protection for credibility with stake holders. References 1. forHarr, Yousef and Abu Suwairh, Ayman Salman, (2010), The impact of the organizational climate on the job performance of administrative workers at the Islamic University of Gaza, Islamic University Journal, Human Studies Series, Vol. 18, No. 2, pp. 1147-1214, Palestine. 2. Mazhouda, Abdelmalek, (2005), Performance between efficiency and effectiveness, concept and evaluation, Journal of Human Sciences, Issue 1, Publications of the University of Biskra, pp. 85- 100. 3. Al-Jihan, Dina Salman Abdul Rahman, (2009), The relationship between emotional intelligence and the level of performance of leaders in a private institution in the city of Riyadh, a field study, unpublished master’s thesis, Arab Open Academy, College of Arts and Education. 4. Schmidt, D. H., van Dierendonck, D., & Weber, U. (2023). The data-driven leader: developing a big data analytics leadership competency framework. Journal of Management Development, 42(4), 297-326. 5. Corsair's. (2017, June 17). What is Data-Driven Leadership? Medium. https://career- accelerator.corsairs.network/what-is-data-driven-leadership-e97f0e123f39 6. Datnow, A., & Park, V. (2014). Data-driven leadership. John Wiley & Sons. 7. Windt, B., Borgman, H., & Amrit, C. (2019). Understanding leadership challenges and responses in data-driven transformations. American Journal of Research in Humanities and Social Sciences Volume 30 November - 2024 P a g e | 19 www.americanjournal.org 8. Bratasanu, V. (2018). Leadership Decision-Making Processes in the Context of Data Driven Tools. Quality-Access to Success, 19. 9. Ahmed, R., & Anantatmula, V. S. (2017). Empirical study of project managers leadership competence and project performance. Engineering Management Journal, 29(3), 189-205. 10. Krajewski, Lee, et al., 2007, Operations Management Processes And Value Chains, 8th ed., Prentice Hall, New Delhi. 11. Slack, Nigel, et al., 2014, Operations Management, 4 ed., Printice Hall, London 12. Adula, M., Kant, S., & Birbirsa, Z. A. (2022). Systematic Literature Review on Human Resource Management Effect on Organization Performance. Annals of Human Resource Management Research, 2(2), 131-146. 13. Humaidi, N., & Asarani, N. A. M. (2012). Investigation on Project Management Performance UsingKnowledge Project Management PerformanceAssessment Model: A Pilot Study. International Journal of Innovation, Management and Technology, 3(6), 769. 14. Hamash, M., Mohammed, H., & Ghreir, H. (2022) EFFECTIVELY PROMOTING DATA- DRIVEN LEADERSHIP AMONG EDUCATION LEADERS. Published in December 2022, 24.