Demand forecasting models are crucial for predicting customer demand and planning inventory levels, helping businesses meet demand without overstocking or stockouts. The demand forecasting model approval process involves reviewing and authorizing models to ensure they are accurate, reliable, and aligned with business goals. Manual handling of demand forecasting model approvals can lead to delays, inaccuracies, and potential inefficiencies in inventory planning, affecting overall supply chain performance. Automating the demand forecasting model approval process allows supply chain managers and analysts to quickly review and approve models based on predefined criteria. Automated workflows can ensure that all necessary information, such as historical sales data, market trends, and statistical methods, is submitted and verified before approval. This reduces the risk of errors, such as approving unreliable or outdated models, and ensures that demand forecasting is aligned with inventory management goals and business strategies. In addition, automation enhances visibility and control over the forecasting process. Stakeholders can track the status of demand forecasting model approvals in real-time, ensuring that all relevant parties are informed and aligned. This transparency reduces the likelihood of miscommunications and ensures that forecasting models are managed according to plan, optimizing inventory planning and supporting supply chain efficiency.