Internet of Things (IoT) in Beauty Retail: A Cross-Disciplinary Approach to Sociolla's Omnichannel Strategy

Elizabeth Christy Go, Boyke Rudy Purnomo, S.E., M.M., PhD., CFP

2025 | Skripsi | MANAJEMEN

Sociolla, sebagai perusahaan ritel kecantikan terkemuka, dikenal dengan inovasinya dalam strategi omnichannel, salah satunya melalui penerapan Internet of Things (IoT) dalam sistem replenishment. Dengan tujuan awal untuk meningkatkan akurasi peramalan permintaan serta meningkatkan pengalaman belanja konsumen secara simultan, realitas penggunaan IoT justru menyebabkan disrupsi rantai pasok, yang mengarah pada fenomena overstocking. Oleh karena itu, penelitian ini bertujuan untuk menggali lebih dalam dampak yang ditimbulkan oleh IoT terhadap manajemen inventaris serta kepuasan konsumen, sekaligus menawarkan solusi untuk mengatasi permasalahan yang muncul. Untuk mendukung tujuan tersebut, metode pengumpulan data dilakukan melalui purposive sampling dengan pendekatan mixed-method, yang mencakup: 1) wawancara, 2) analisis dokumen, 3) observasi, dan 4) kuesioner. Analisis data akan dilakukan dengan menggunakan Mean Absolute Percentage Error (MAPE) sebagai alat evaluasi utama dalam menilai Collaborative Planning, Forecasting, and Replenishment (CPFR), serta gap score dalam Service Quality (SERVQUAL), yang hubungannya akan dikembangkan melalui pendekatan Stimulus-Organism-Response (SOR). Hasil penelitian menunjukkan bahwa sebagian besar peramalan permintaan tidak akurat, di mana Januari 2024 memiliki MAPE tertinggi sebesar 13%, dengan hanya dua bulan yang menghasilkan tingkat akurasi yang memadai. Di sisi lain, di antara dimensi SERVQUAL, Tangible memiliki gap terbesar sebesar -0,040, yang menunjukkan perlunya peningkatan pengalaman berbelanja di toko fisik Sociolla. Oleh karena itu, solusi yang diusulkan berfokus pada integrasi teknologi, di mana penggunaan Artificial intelligence (AI) akan membantu mengatasi ketidakakuratan dalam peramalan permintaan, sementara Augmented Reality (AR) akan membantu memperbaiki pengalaman belanja yang terganggu akibat overstocking, serta pelatihan karyawan agar lebih siap dalam menghadapi transformasi digital.

Sociolla, a leading beauty retail company, has been known with its innovation in omni channels, one of which is through incorporating the use of the Internet of Things (IoT) in its replenishment system. With its initial aim to perform accurate demand forecasting and simultaneous increase in consumer shopping experience, the reality of IoT utilization has created supply chain disruptions, leading to overstocking phenomenon. Due to this, the research aims to deep dive into the impacts caused by IoT towards its inventory management as well as onto consumer satisfaction, where solutions to address such surging problems are proposed. To support such objectives, the data collection methods utilize purposive sampling through mixed-method approach, including: 1) interview, 2) document analysis, 3) observation, and 4) questionnaire. The data collection analysis will be done through incorporating Mean Absolute Percentage Error (MAPE), as the main evaluation tool to assess the Collaborative Planning, Forecasting, and Replenishment (CPFR), and the score gap in Service Quality (SERVQUAL), which relationships will be expanded through the Stimulus-Organism-Response (SOR). As a result, it is found that most of the forecasts are inaccurate, with January 2024 having the highest MAPE for 13%, and with only two months producing accurate remarks of demand forecasting. On the other hand, amongst the dimensions of SERVQUAL, Tangible holds the biggest gap of -0.040, signifying a need for in-store improvements for Sociolla. Hence, the solutions proposed focus on technological integration, whereby the use of Artificial intelligence (AI) will help tackle the demand forecasting inaccuracies, while Augmented Reality (AR) will help overcome the poor shopping experience caused by overstocking, as well as employee training to be equipped with digital skills.

Kata Kunci : Sociolla, Omnichannel, Inventory Management, Consumer Satisfaction, Demand Forecasting, Internet of Things (IoT), Collaborative Planning, Forecasting, and Replenishment (CPFR), Mean Absolute Percentage Error (MAPE), Service Quality (SERVQUAL), Stimulus-Or