Choose A Data Set From The Database List, E.g., Performance

Choose A Set Of Data From The Database List Egperformance Data Or

Choose a set of data from the database list (e.g., Performance data or Performance Management application). Next, select the appropriate application program that the data interfaces with via the database management system (i.e., Performance program). Now, explain how information from the application and system are displayed on your computer screen as the user. Explain how you use the program and what functions are available to you. Provide recommendations you would make to improve the program's functionality to make it easier for end users.

Paper For Above instruction

In today's digitalized business environment, performance management systems play a crucial role in monitoring, analyzing, and enhancing organizational productivity. This paper explores the process of selecting a performance management application, how the system interacts with data, its user interface, and functionally enhance user experience through practical recommendations.

Selection of Data and Application Interface

The starting point involves choosing a relevant dataset from the organization’s database, such as employee performance metrics, project completion rates, or customer satisfaction scores. For this discussion, I opted for employee performance data stored within the company's database. This dataset provides insights into individual productivity, goal achievement, and competency assessments. The associated application program that interfaces with this data is typically a Performance Management System (PMS), which connects via a Database Management System (DBMS) to fetch, process, and display data.

The Performance Management System serves as an interface allowing users to retrieve and analyze employee data efficiently. The selection process involves using the application's user interface, which interacts with the backend database through structured query language (SQL) commands or Application Programming Interfaces (APIs). The system's architecture ensures data integrity, security, and efficient retrieval, facilitating real-time performance tracking.

Display of Information on the User’s Screen

Once logged into the PMS, the system displays information through a well-organized, intuitive graphical user interface (GUI). The dashboard primarily shows summary metrics, such as overall performance scores, recent appraisals, and key performance indicators (KPIs). Data visualization elements like charts, graphs, and progress bars are prominently used to provide a quick snapshot of individual or team performance (Laudon & Laudon, 2019). Details such as employee names, roles, review periods, and performance ratings are structured within tables for easy navigation.

The interface adapts dynamically based on user roles; managers and HR personnel have access to comprehensive data, including individual feedback, developmental plans, and historical evaluations. Conversely, employees might see their own performance summaries, goal status, and feedback comments. This role-based display promotes transparency and relevant data access, enhancing engagement (Sharma et al., 2020).

User Interaction and Functions

User interaction with the PMS typically involves multiple functions. Users can generate performance reports, update individual goals, provide feedback, and schedule appraisals. For example, a manager may select a specific employee record to review detailed feedback and performance trends. The system allows for data entry, note-taking, and uploading documents, facilitating a comprehensive performance review process (Mishra & Mishra, 2020).

Furthermore, the program offers analytical functions such as comparative analysis across departments, identifying high or under-performing individuals, and tracking improvement over time. Notifications and alerts inform users about upcoming review deadlines, pending feedback submissions, or performance anomalies. Such functionalities are designed to streamline workflows, promote accountability, and foster a data-driven culture (Kaur & Kaur, 2021).

Recommendations for Improving Functionality

Despite its capabilities, there are areas where the Performance Management System can be improved for enhanced user experience and efficiency. Firstly, integrating a mobile-friendly interface would allow users to access performance data remotely, increasing flexibility and responsiveness (Chen & Hwang, 2022). Secondly, incorporating artificial intelligence (AI) and machine learning algorithms could offer predictive analytics, identifying potential performance issues proactively and suggesting personalized development plans.

Thirdly, improving data visualization with more customizable dashboards tailored to user preferences would make data interpretation more straightforward. For example, allowing users to select specific KPIs or timeframes to display in their dashboards enhances relevance. Additionally, reducing system redundancies by streamlining data entry processes and integrating third-party tools like communication platforms could promote smoother workflows (Johnson et al., 2021).

Lastly, implementing comprehensive training modules and help features within the system would assist end-users in maximizing its functionalities. User-friendly tutorials, FAQs, and support chatbots can reduce the learning curve and increase adoption rates (Patel & Anjum, 2020).

Conclusion

In conclusion, selecting appropriate data and application systems, understanding their interface design, and user functionalities are vital aspects of effective performance management. While the current system provides essential features for performance monitoring and feedback, strategic enhancements—such as mobility, AI integration, customizable interfaces, and user support—are critical for optimizing usability and driving organizational performance. Through these improvements, performance management systems can become more accessible, insightful, and adaptable to evolving organizational needs.

References

  • Chen, L., & Hwang, G. J. (2022). Mobile learning and performance management: Opportunities and challenges. Journal of Educational Computing Research, 60(4), 755-779.
  • Johnson, P., Smith, R., & Lee, H. (2021). Improving data visualization in performance management systems. International Journal of Information Management, 58, 102-112.
  • Kaur, P., & Kaur, G. (2021). Role-based access control in performance management systems. Journal of Business Analytics, 14(2), 200-215.
  • Laudon, K. C., & Laudon, J. P. (2019). Management Information Systems: Managing the Digital Firm. Pearson.
  • Mishra, P., & Mishra, P. (2020). Enhancing performance appraisal systems through technological integration. International Journal of Human Resource Management, 31(7), 911-935.
  • Patel, D., & Anjum, R. (2020). User adoption of performance management systems: Training and support strategies. Journal of Systems and Software, 164, 110567.
  • Sharma, R., Khandelwal, S., & Verma, P. (2020). Impact of role-based data access in performance management. Journal of Computing Technologies, 11(3), 154-162.
  • Smith, A., & Williams, J. (2023). Evolving trends in performance management software. Technology in Business Today, 35(1), 45-55.
  • Xu, Y., & Wang, Q. (2019). Data visualization techniques for effective performance dashboards. Journal of Visualization & Computer Graphics, 25(4), 1281-1294.
  • Zhang, T., & Liu, S. (2022). Artificial intelligence applications in HR performance systems. Journal of Management Analytics, 9(2), 189-204.

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