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Innovative Article | Procurement and Supply Chain Management | Volume 15 Issue 6, June 2026 | Pages: 1604 - 1606 | United States
Weighted Blend Forecast
Abstract: This whitepaper introduces the Weighted Blend Forecast methodology, a modern approach to demand planning designed to address the limitations of single-source forecasting models. Traditional forecasting methods rely heavily on historical sales data or isolated expert inputs, often failing to account for market volatility, external disruptions, and inherent biases. The proposed framework integrates multiple data streams-including internal operational data, sales intelligence, and external market indicators-into a unified, consensus-driven forecast using a weighted blending mechanism. This triangulation approach enables organizations to neutralize biases, identify anomalies, and improve forecast reliability. The paper outlines the architecture of blended forecasting, highlights key limitations of conventional models, and demonstrates how combining diverse inputs leads to improved forecast accuracy, reduced inventory waste, and enhanced decision-making. Ultimately, the Weighted Blend Forecast approach represents a strategic shift from reactive planning to proactive, data-informed orchestration in modern supply chain environments.
Keywords: Demand Forecasting, Weighted Blend Forecast, Supply Chain Planning, Forecast Accuracy, Demand Sensing, Predictive Analytics, Sales Forecasting, Inventory Optimization, Data Integration
How to Cite?: Sukhvinder Singh, "Weighted Blend Forecast", Volume 15 Issue 6, June 2026, International Journal of Science and Research (IJSR), Pages: 1604-1606, https://www.ijsr.net/getabstract.php?paperid=SR26623202847, DOI: https://dx.doi.org/10.21275/SR26623202847