Proposed Improvement of Demand Forecast Accuracy using Six Sigma DMAIC in PT XYZ

I Putu Edward Narayana, Yuanita Handayati


This research aimed to optimizing strategies for PT XYZ, specifically focusing on bridging the gaps between demand forecasts and actual market demand of lubricants product, with a strong emphasis on the Business-to-Business (B2B) segment. B2B introduces unique challenges, necessitating a specialized approach. Employing the Six Sigma DMAIC methodology, a comprehensive analysis is conducted to uncover deficiencies in current sales forecasting methods. The Holt-Winter method is then applied to offer robust remedies, effectively minimizing complexities such as seasonal patterns and market trends. Drawing on historical data from the B2B lubricants segment served by PT XYZ, the analysis establishes a solid empirical foundation. This comprehensive forecasting approach positions PT XYZ as a market leader, equipped to anticipate and pre-empt market fluctuations. The application of the Holt-Winter time series method not only significantly enhances forecasting accuracy but also mitigates substantial risks linked to inventory imbalances concerning demand. The implementation of such a robust forecasting framework stands to elevate the operational efficiency of PT XYZ, with a paramount commitment to maintaining customer satisfaction in the dynamic business landscape.


demand forecasting; lubricants product; six sigma DMAIC, time series forecasting

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