OPTIMIZACIÓN DE LA PROYECCIÓN DE DEMANDA QUE PERMITA EN LA EMPRESA RAINBOW, MEJORAR LA GESTIÓN DE INVENTARIOS Y LA DISPONIBILIDAD DE PRODUCTOS.

Abstract

This applied research aims to optimize demand forecasting at Rainbow, a global agrochemical company operating in Ecuador, which currently faces significant challenges in inventory management. The issue is defined by the coexistence of excess inventory for low-rotation products—resulting in high storage costs and obsolescence—and frequent stockouts of high-rotation items, leading to lost sales, customer To address this issue, four strategic alternatives were evaluated: (1) liquidation and promotion campaigns for overstocked products, (2) implementation of Rolling Forecast and pilot planning programs, (3) digital marketing strategies to improve product visibility, and (4) ABC analysis combined with dynamic pricing and import volume adjustment. Tools such as the PDSA cycle, impact matrix, risk assessment, and technology cost analysis (SAP vs Microsoft Dynamics) were employed. The results identify the Rolling Forecast model as the most sustainable and high-impact solution. This proposal aims to reduce excess inventory of low-rotation items by 10% and decrease losses from stockouts by 30%, through collaborative planning, monthly forecast updates, and real-time performance monitoring (KPIs). Financially, it offers tangible benefits such as reduced storage costs, improved inventory turnover, regained sales, and enhanced operating margins. Additionally, it aligns operational planning with market trends, customer demand, and interdepartmental coordination.