Performance management and continuous process improvement are essential for businesses to monitor how well their operations are running, find ways to improve them, and bring about good change. However, making decisions based on data in these areas can be challenging because performance data is complicated. This research looks into how panel analytics and data visualization tools can help manage performance well and make processes better all the time. A literature study is done on performance management frameworks, process improvement methods, data visualization techniques, and dashboard solutions that are already out there. The Lean, Six Sigma, and balanced scorecard methods are looked at for success indicators and metrics. It also looks into data visualization tools' design principles and methods like dashboards, tables, charts, and interactive features. Interviews, observations, document reviews, and internal files are ways a case organization gathers both primary and secondary data. Key performance indicators for quality, delivery, productivity, safety, and customer happiness are found in several different business roles and processes. To look at performance trends and relationships, SPSS is used for descriptive statistics and hypothesis testing. Interactive dashboard examples that use different data visualization methods are created by thinking about how the user will experience it, how it will work with other systems, and how it will help them make decisions. Dashboards let you dig deeper into processes, determine why problems happen, and compare actuals to goals. Usability testing checks how easy the tools are and how well decision-makers can learn from them. The results show that dashboard analytics can make handling performance and improvement projects easier based on data. Insights made it possible to keep track of KPIs, find methods that were not working well, and work together across teams. There are also talks about problems with data quality and change management.