Financial Management Information system salient features in relation to public organisation performance
- 1. UNIVERSITY OF DAR ES SALAAM DISSERTATION PRESENTATION FINANCIAL MANAGEMENT INFORMATION SYSTEM SALIENT FEATURES IN RELATION TO PUBLIC ORGANIZATION PERFORMANCE. THE CASE OF VOCATIONAL EDUCATION AND TRAINING AUTHORITY. NAME:BAHATI L MOSHA REG NO:2021-06-01734 PROGRAMME:MASTER OF ENGINEERING MANAGEMENT-PM DEPT:MECHANICAL AND INDUSTRIAL ENGINEERING,(COeT) DECEMBER 2024
- 2. Presentation Outline INTRODUCTI ON Background of the study Problem statement Research Objectives Research Questions Significance of the Research LITERATURE REVIEW Theoretical Framework Coneptual Framework METHODOLO GY Research approach,design ,data source and type Sampling technique and sampling size DATA ANALYSIS CONCLUSION AND RECCOMEND ATIONS
- 3. Introduction • Background of The Study To enhance Government Management Support Services in Tanzania, several backend systems like HCMIS, MUSE, GMS, TANePS, ERMS, Integrated Planning and Budgeting System, e- office, and e-Mrejesho need improvements and integration. These systems support financial management, human resources, procurement, electronic communication, resource management, planning, and feedback handling. The Tanzanian Vocational Education and Training Authority (VETA) implemented MUSE in 2021 for efficient financial management. MUSE is a government- owned web-based accounting software with features like GSF Code, COA, Cash Management, Accounts Payable/Receivable, General Ledger, Purchasing, Inventory, Asset Management, Reconciliation, EFT, multi-company and multi-currency support, and extensive reports. Despite its use in key institutions, its influence on public organization performance details remain unclear.
- 4. Problem Stetement • The Financial Management Information System (FMIS-MUSE), introduced in 2021 by Tanzania’s Vocational Education and Training Authority (VETA), aims to optimize financial processes, resource allocation, and organizational efficiency. However, the system faces challenges such as limited customization, underutilization of essential features, and misalignment with VETA’s strategic objectives. While existing research underscores the importance of system design and functionality in FMIS performance, there is limited focus on FMIS-MUSE's specific role in vocational education. This study seeks to analyze FMIS- MUSE’s key features, evaluate their impact on organizational performance, and provide actionable recommendations to improve system efficiency and sustainability, ultimately enhancing financial resource management at VETA and contributing to broader insights on FMIS applications in vocational education.
- 5. Objectives Specific Objectives To identify and analyze the key features of the FMIS-MUSE. To assess the influence of FMIS-MUSE on VETA performance. To recommend strategies for optimizing FMIS- MUSE to enhance organizational performance (VETA). To examine the Financial Management information system (FMIS-MUSE) salient features in relation to public organization performance. Main Objective
- 6. Research Questions What are the salient features of VETA’s FMIS-MUSE, and how are they currently utilized? How do the FMIS-MUSE features influence VETA’s accountability, transparency, and decision making? What specific enhancements can be proposed to optimize FMIS-MUSE functionality and better support VETA’s performance?
- 7. Significance and Scope of the Research • Significnce Knowldege contributions to Vocational Istitutions (VETA) and Government of Tanzania (Ministry of Finance). Indication the relationship between FMIS-MUSE and Organizational perfomance. Shading lights on the features of the FMIS-MUSE and their usefulness in Enhancing Organizational perfomance • Scope The scope of this research is the salient features of FMIS- MUSE within the Tanzanian Vocational Education and Training Authority.focusing various regions of Tanzanian Mainland.
- 8. Theoretical Framework • Institutional Theory Institutional theory highlights how organizations conform to external norms, rules, and expectations to gain legitimacy and maintain stability. In the context of a Financial Management Information System (FMIS), institutional theory explains how the adoption and use of such systems align with regulatory requirements, industry standards, and stakeholder expectations. This ensures transparency, accountability, and efficiency in financial processes, reinforcing the organization’s legitimacy and fostering sustainable performance. • Contingency Theory Contingency theory posits that there is no one-size-fits-all approach to management; organizational effectiveness depends on aligning structures and processes with specific environmental factors. In the context of a Financial Management Information System (FMIS), this theory suggests that the system's design and functionality should be tailored to the organization’s unique goals, regulatory environment, and operational needs. A well-aligned FMIS enhances decision-making, resource management, and adaptability in dynamic conditions, ensuring optimal organizational performance.
- 10. METHODOLOTY Population The study population includes 109 respondents comprising management, cashiers, accountants, procurement officers, system administrators, support teams, and financial department staff, as these groups directly interact with or oversee the FMIS Research Design, research approach, Source and type of data This study used a mixed-methods approach, collecting both quantitative and qualitative data to identify and analyze the salient features of the Financial Management Information System (FMIS-MUSE) in the Vocational Education and Training Authority (VETA) The study utilized both quantitative and qualitative research approaches. Quantitative techniques involved statistical analysis of data collected through questionnaires using a Likert Scale. Qualitative techniques emphasized interviews with open-ended questions, resulting in narrative data. The qualitative data was analyzed using content analysis. This study collected both quantitative and qualitative Primary data form FMIS-MUSE Users.
- 11. Sampling Technique and Sample size • Sampling Technique • To determine the sample size for a study involving a known population using Yamane's formula, the following formula is used: • • Where, n is the sample size, N is the population size, and e is the margin of error (usually 0.05 for a 95% confidence level). Given: Population size N and Margin of error e=0.05. Sample Size • In the case of VETA, the population size (staffs who interact with FMIS-MUSE) is approximately 150, Management (Vocational center principals and Financial zonal managers), Cashers, accountants and procurement officers, System Administrators, Supporting team and Financial Department VETA Head office. • = • Sample size is 109
- 12. DATA ANALYSIS • Method of Data Analysis. • The study analyzed data using descriptive statistics and multiple regression analysis in order to show the relationship between variables. After the data was collected, it was coded and entered into SPSS. Correctness of data entry was checked. The scale-based variables were checked for internal consistence after which the scores are aggregated to obtain mean scores for each respondent per scale variable measure. • Descriptive Statistics • The study utilized descriptive statistics, including frequencies, percentages, mean, and standard deviation, to summarize data and identify trends. Descriptive statistics simplify complex datasets by highlighting key features and offering an overview of the sample. The mean represented the central tendency, showing the average value, while the standard deviation measured variability, indicating how much values deviated from the mean. This method provided insights into the magnitude and patterns within the data. Overall, it offered a clear and concise summary to meet the study's objectives.
- 13. DATA ANALYSIS…….. • Method of Data Analysis……. • Linear Regression The study used multiple regression analysis to assess how Financial Management Information System (FMIS) features influence public organization performance. Multiple regression expands traditional regression by analyzing several variables simultaneously. This method captures the comprehensive relationship between dependent and independent variables. It is particularly useful for examining how multiple explanatory factors impact a single outcome. Multiple linear regression effectively tests the linear relationships within the model. • Content Analysis • Qualitative data from interviews was analyzed to identify key patterns and themes. For Objective One, FMIS-MUSE features were identified and categorized into themes like functionality and usability. Recommendations for Objective Three were developed by aligning identified challenges with best practices. Strategies to optimize FMIS-MUSE were created by triangulating data with stakeholder input. This approach ensured that recommendations were well-informed and actionable.
- 14. Data Analysis…….. Reliability and Validity of the Data • Reliability • The study used the Kaiser-Meyer-Olkin (KMO) test to assess the adequacy of the data for factor analysis. Measures were taken to ensure the reliability and validity of the data through accurate data collection, pilot studies, and established methodologies. Essentially, the KMO test checks if the variables in the dataset share a common factor structure. • Validity • The validation processes include content, construct, and predictive validity (Mayunga, 2009). Mayunga employed both content and construct validity in his evaluation, testing the research instruments in a pilot study to ensure they accurately collected data. This testing allowed for adjustments to be made to the data collection instruments before the main data collection began.
- 15. Methods of Data Analysis • A sample of 109 respondents were selected for this study. Table 4.1 shows that only 92 out of 109 respondents were responded and provided accurate answers to this study. Therefore, the study analysis based on response rate of 84.40% which is fair and representative according to (Mugenda, 2003) stated that, a response rate of >50% is required for analysis and representation of data.
- 17. Methods of Data Analysis • Identification and Analysis of key Features of FMIS-MUSE. • Individual perception on features of the FMIS-MUSE. Respondents generally agreed that FMIS-MUSE is easy to navigate, with a mean score of 3.96 and a standard deviation of 1.120. • General Perception of FMIS-MUSE's Functionality Findings show that, the majority of users (24.1%) regard FMIS-MUSE as an "Excellent" or "Best system," highlighting a strong positive perception among nearly one- fourth of participants. A notable proportion (14.5%) also views it as a "Good" system, while 13.3% emphasize its effective cash management capabilities. Additionally, 10.8% recognize its ability to simplify work, suggesting that FMIS-MUSE significantly supports routine tasks. • Difficulties While Using FMIS-MUSE The findings reveal that while a substantial proportion of users (24.1%) reported no difficulties, a significant number (15.7%) highlighted connectivity issues, specifically that FMIS-MUSE struggles during poor internet connectivity. Moreover, 10.8% noted that the system should be more institution-specific, suggesting that the generic nature of FMIS-MUSE may hinder its effectiveness in meeting the unique demands of certain institutions
- 18. Methods of Data Analysis • Familiarity and Utilization of FMIS-MUSE Features • The results reveal that users are most familiar with core financial management features, such as report generation (mean = 4.40) and general ledger (4.20), which indicates these functionalities are well-integrated and align with user requirements. Conversely, features like purchasing (2.50), helpdesk (2.30), and loan management (2.20) reflect lower familiarity, suggesting limited utilization or inadequate integration into users' daily workflows.
- 19. Methods of Data analysis • Influence of FMIS-MUSE on VETA performance. The findings show that FMIS-MUSE enhances financial tracking and monitoring within VETA, with a mean score of 3.59 (Std. Dev. = 1.298). It provides reliable tools for overseeing transactions, improving control and efficiency. Users rated it positively for enhancing accountability, promoting transparency and responsibility, and received a high score for improving financial data accessibility (mean = 3.73, Std. Dev. = 1.001). Respondents agree that FMIS-MUSE supports better decision-making, with a mean score of 3.59 (Std. Dev. = 1.298). However, the budgeting process received a neutral rating (mean = 3.25, Std. Dev. = 1.314), indicating room for improvement. The availability and clarity of financial information also received a neutral response (mean = 3.18, Std. Dev. = 1.471), suggesting enhancements are needed for better accessibility and clarity. • Influence of FMIS-MUSE on Service Quality to Stakeholders. Results from Table 4.9 indicate that FMIS-MUSE has significantly enhanced transparency, with 43.4% of respondents noting improved visibility in financial operations. Additionally, 14.5% observed better support in student-related financial management, such as timely payments and efficient cash handling. While 10.8% reported a moderate improvement in service quality, 8.4% felt the system's impact on service quality was limited, reflecting diverse experiences with FMIS-MUSE. A smaller group (4.8%) mentioned faster reporting capabilities as a benefit. Overall, these results suggest that FMIS-MUSE has improved transparency and certain aspects of service quality, but there is room for further enhancement in its overall service effectiveness.
- 20. Methods of Data analysis • Strategies for optimizing FMIS-MUSE to enhance organizational performance (VETA). • Areas where FMIS-MUSE Functionalities Could be Improved The majority of respondents (54.2%) believe that the tools available in FMIS-MUSE need enhancement to better support their financial management tasks. Another significant group (36.1%) highlighted the need for optimization in the budgeting process to improve efficiency. Additionally, 9.6% of respondents pointed out the need for clearer and more accessible financial data to ensure easier access to actionable information. • Suggestions for Better User Training on FMIS-MUSE Features. The majority of respondents (62.7%) called for a comprehensive training program for FMIS-MUSE, highlighting the need for a thorough and structured approach. Additionally, 24.1% suggested hands-on practice modules to enhance real-world application, while 13.2% supported refresher and update sessions to keep users informed about system changes for more consistent and effective use.
- 21. Methods of Data analysis • Improving Communication and Collaboration Regarding Financial Data • To improve communication and collaboration, 41% of respondents proposed shared financial dashboards for better data visibility. Automated notifications and alerts were favored by 32.5% to ensure timely updates on financial changes. Lastly, 26.5% suggested integrating commenting and discussion features in FMIS-MUSE to enable real-time dialogue, reducing reliance on external tools. • Suggestions for Enhancing Training/Support for FMIS-MUSE Users A majority of respondents (63.9%) stressed the importance of continuous training and support to keep users proficient with FMIS-MUSE. Additionally, 21.7% recommended a dedicated helpdesk for immediate assistance, while 14.4% suggested improving access to detailed user guides to facilitate independent troubleshooting and boost user confidence.
- 22. Conclusions. Identification and Analysis of Key Features of FMIS-MUSE FMIS-MUSE is well-received by VETA's financial staff, earning high ratings for usability (3.96) and relevance (3.95) due to its intuitive interface and alignment with key financial tasks like cash management, accounts payable, and report generation. Core features, such as report generation (4.40), are widely used, but lower familiarity with purchasing (2.50) and Treasury Single Account (1.80) highlights the need for further training and integration. While the system supports efficiency (3.59), improvements are needed in tools, technical support (3.07), and addressing connectivity issues (15.7%). Challenges in financial statement preparation and the need for institution-specific customization are noted. Despite these gaps, FMIS-MUSE enhances security, budgeting, troubleshooting, and accountability. Overall, the system's strengths are clear, but additional training and feature enhancements are necessary to fully meet VETA's financial needs.
- 23. Conclusions Influence of FMIS-MUSE on Organizational Performance FMIS-MUSE positively impacts VETA's organizational performance by enhancing financial tracking, accountability, transparency, and decision-making, with ratings of 3.59 for monitoring and decision-making, and 3.73 for transparency. It streamlines daily operations, reduces paperwork for 34.9% of users, and improves service delivery transparency (43.4%) and student financial management (14.5%). However, challenges like technical issues in financial statement consolidation (9.6%) and moderate budgeting functionality (3.25) highlight areas for improvement. FMIS-MUSE’s immediate data access and robust audit trails strengthen accountability and transparency, but addressing technical limitations is essential to fully align the system with VETA's organizational goals. Strategies for Optimizing FMIS-MUSE to Enhance Organizational Performance To optimize FMIS-MUSE and enhance VETA's organizational performance, key strategies include expanding system functionalities, improving training, strengthening communication tools, and bolstering technical support. Recommendations focus on refining budgeting tools, streamlining the user interface, and addressing system challenges like latency and integration issues through server upgrades and advanced features. Continuous hands-on training, shared dashboards, in-system commenting, and a dedicated helpdesk are suggested to improve user competency and communication. These strategies aim to streamline processes, enhance data clarity, and align FMIS-MUSE with VETA's financial and organizational goals, providing a clear roadmap for system improvement.
- 24. Conclusions General Satisfaction and Organizational Performance (VETA). The study on FMIS-MUSE at VETA reveals its positive impact on user satisfaction and organizational performance, with users reporting moderate satisfaction (mean scores: 3.45– 3.73) and strong consensus. Statistical analysis shows a significant correlation (R = 0.751) between FMIS features—functionality, design, strategies, and challenges—and organizational performance, with 56.4% of performance variance explained by these factors. Functionality and strategies significantly enhance performance, while challenges slightly detract from it. The findings highlight the importance of optimizing functionality and strategies to improve efficiency, accountability, and financial management. Additionally, the study underscores the need for tailored FMIS design and strategic support in public institutions, contributing valuable insights into enhancing system effectiveness for better organizational outcomes.
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