Key Learning Outcome: This study demonstrates that integrating field data with optimization and probabilistic forecasting within a decision support system (DSS) could transform produced water management from reactive to proactive, enabling enhanced operational efficiency and decision-making. Abstract: In the realm of produced water management in the offshore oil and gas industry, transitioning from reactive to proactive strategies is crucial for enhancing operational efficiency and sustainability. This study explores a holistic approach that integrates field data (historical and forecast periods), simulation tools, and system specifications within an interactive Decision Support System (DSS). By leveraging predictive analytics and real-time monitoring technologies, the DSS enables operators to anticipate and mitigate potential issues before they escalate, ensuring continuous and efficient operations. The DSS utilizes comprehensive inputs, including operational knowledge of all equipment and their parameters, to initiate forward simulations. These simulations generate outputs that visualize multiple unmeasured parameters, aiding experts in making informed decisions. Additionally, an optimization toolbox within the DSS allows for the optimization of various parameters, focusing on environmental regulations and other predefined objective functions. The DSS also facilitates primitive uncertainty assessments, further enhancing decision-making processes. Through case studies and real-world applications, this research highlights the transformative potential of combining field data with advanced simulation techniques. The findings underscore the importance of adopting innovative technologies to drive efficiency and sustainability in the oil and gas industry.