How Demand Variability and Forecast Accuracy Influence Storage Configuration Decisions in a Growing Beverage SME: The Case of Drink a Flower

Details

Supervisors

Chevalier, Philippe

Faculty

Louvain School of Management

Degree label

Master [120] : ingénieur de gestion, à finalité spécialisée

Abstract

enThis thesis examines how demand variability and forecast accuracy influence storage configuration decisions in a growing beverage SME, using the case study of Drink a Flower. As rapidly expanding companies face increasing operational complexity, balancing inventory levels, storage capacity, and service performance becomes a major supply chain challenge. The research analyzes the relationship between predictive accuracy, inventory management, and storage-related decisions under fluctuating demand and operational uncertainty. Several forecasting methods, including moving average, weighted moving average, and exponential smoothing, are evaluated using historical sales and inventory data collected throughout 2025. Their performance is assessed through key indicators such as forecast error, demand variability, and inventory-related measures. The results demonstrate that demand variability significantly shapes inventory requirements and storage decisions by increasing the need for operational flexibility and adaptive inventory management practices. The study also highlights that relatively simple forecasting methods can provide sufficiently reliable results for SMEs operating with limited data and resources. However, predictive modeling alone does not fully eliminate operational uncertainty, underscoring the importance of flexible storage and inventory strategies capable of supporting growth while maintaining operational efficiency. Based on these findings, this study proposes practical recommendations to support forecasting and inventory management improvements in growing SMEs. More broadly, the research illustrates how supply chain practices can be adapted to the operational realities of fast-growing companies facing uncertainty, resource constraints, and evolving logistics needs.