Reducing Overstock in Hospitality Lighting Inventory with Data Forecasting
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V7I2P148Keywords:
Inventory Management, Demand Forecasting, Hospitality Lighting, Overstock Reduction, Data Analytics, Time Series AnalysisAbstract
In the hospitality lighting sector, man-aging inventory efficiently remains a persistent challenge. Overstocking not only ties up capital but also consumes valuable warehouse space, es-pecially in an industry characterized by seasonal demand and complex project timelines. This paper presents a data-driven forecasting methodology to reduce overstock in hospitality lighting. By lever-aging historical sales data and applying time series analysis, suppliers can more accurately predict de-mand patterns, streamline procurement, and re-duce waste. The proposed approach improves in-ventory turnover and helps lighting vendors align with the needs of the dynamic hospitality sector. The analysis demonstrates that proper forecasting methods not only mitigate risks associated with surplus inventory but also enhance the respon-siveness of the supply chain. This ultimately re-sults in cost savings, improved margins, and ele-vated customer satisfaction.
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