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Journal : ComTech: Computer, Mathematics and Engineering Applications

Comparative Analysis of Reconciliation Techniques: Bottom-Up, Top-Down, and MinT for Product Forecasting in Retail SMEs Rambing, Danni; Kusumaningrum, Retno; Sugiharto, Aris
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 1 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i1.12293

Abstract

Small and Medium Enterprises (SMEs) have experienced rapid growth, contributing approximately 95% to the global economy, 60% to global employment, and 50% to global GDP. This growth is accompanied by significant challenges, with approximately 70% of SMEs failing within the first three years, primarily due to poor inventory management. It emphasizes the crucial role of accurate demand forecasting for SMEs, particularly in the retail sector, where time series at various levels of hierarchical structure exhibit different scales and display diverse patterns. However, most existing research on demand forecasting for SMEs focuses on a single hierarchical level—either bottom, middle, or top—without addressing the entire hierarchy. The research sought to address this gap by forecasting across all hierarchical levels and evaluating different reconciliation techniques to generate coherent and accurate forecasts for multiple products in retail SMEs. The ETS state space model was used as the base forecasting model. This model was widely recognized as a benchmark in forecasting competitions. The reconciliation methods assessed were Bottom-Up, Top-Down based on historical proportions (average proportions), Top-Down based on forecast proportions, and Minimum Trace (MinT) (Ordinary Least Squares (OLS), OLS Non-Negative (OLS Non-Neg), Weighted Least Squares (WLS), and WLS Non-Negative (WLS Non-Neg)). The evaluation results show that the OLS Non-Negative method, with an average SMAPE value of 35.335%, produces more accurate reconciliation than other methods. In addition, this method also outperforms the base model with an increase in accuracy of 13%.
Co-Authors Abd. Rasyid Syamsuri Adi Wibowo Adieb, M. Risqi Amirul Adiputera, Yusuf Fahmi Afry Rachmat Agus Suwandono Andi Gunawan Antariksa, Muhammad Deagama Surya Ari Wibawa Budi Santosa Arief Hidayat Arif Wibawa, Helmie Arkan, Tsaqif Muhammad Ary Setyadi Bagoes Widjanarko Baihaqi, Muhamad Nur Bayu Surarso Budi Warsito Budi Warsito Dedy Kurniawan Hadi Putra, Dedy Kurniawan Hadi Didit Suprihanto, Didit Eko Adi Sarwoko Eko Didik Widianto Eko Didik Widianto Eko Nur Hidayat Eko Prasetiawan Fajar Hari Prasetyo Fajar Nugraha Ganis Khufad Arridho Hanif Setiawan, Syariful Helmi Arif Wibawa Helmie Arif Wibawa Helmie Arif Wibawa Henny Indriyawati Hidayat, Agung Rahmad Ikhthison Mekongga Indriyati Indriyati Irfan Pradipta Juwanda, Farikhin Kamal Maulana Kushartantya Kushartantya Kusworo Adi Lusiana Kristiyanti Lutfi Rinanto Mochammad Hosam Muhammad Malik Hakim, Muhammad Malik Mustafid Mustafid Nazla Nurmila, Nazla Nikmah Rahmawati Pradhitya Nur Diyah S Pramudita Eka Hananto Prastio, Wahyu Tedi Priyo Sidik Sasongko R Rizal Isnanto Ragil Saputra Ragil Saputra Rahmat Gernowo Rambing, Danni Riyana Putri, Fayza Nayla Rizki Saputra, Naufal Roby Hanintyo Nursio Sakti Rukun Santoso Satriyo Adhy Sembiring, Rinawati Septya Maharani, Septya Sinta Tridian Galih Sugiyamto Sugiyamto, Sugiyamto suhartono, Suahrtono Sukmawati Nur Endah Supriyono Supriyono Suryo Hartanto Sutikno Sutikno Sutopo Patria Jati Tantyoko, Henri Tarno Tarno Toni Prahasto Victor Gayuh Utomo Wahyu Adi, Prajanto Wahyu Krisna Hidayat Wahyu Krisna Hidayat Wahyudi Setiawan widowati widowati Wijayanto, Ahmad Yudie Irawan Yulianto Prabowo