Exploring Logistics Process Improvement Possibility with SCOR Digital Standard and Lean Waste Analysis

Authors

  • Adhie Prayogo Universitas Muria Kudus, Indonesia
  • Curie Habiba Universitas Muria Kudus, Indonesia
  • M. Mujiya Ulkhaq Diponegoro University, Indonesia
  • Dina Tauhida Universitas Muria Kudus, Indonesia
  • Fachri Rizky Sitompul Hungarian University of Agriculture and Life Sciences, Hungary

DOI:

https://doi.org/10.52435/jaiit.v7i2.723

Keywords:

Business Process Modelling, Lean Waste Analysis, Logistics, Process Improvement, SCOR Digital Standard

Abstract

Inbound logistics, including receiving goods, quality and physical checking, item inquiry, and stock-level checking are essential aspects within supply chain management in which the unresponsive operation may lead to inefficiency. This study aims to observed the ongoing operations in a mid-sized paper manufacturer using a combination of Business Process Modelling to map the current flow process, Lean Waste Analysis to identify possible wastes, and SCOR Digital Standard to offer improvement opportunities. The results show that waiting, motion, overprocessing, and inventory wastes are identified across the three logistics main processes. Additional waste, human skill, is observed in the stock-level checking procedure. Subsequently, SCOR DS recommends the firm to escalate the human skills of lean manufacturing, bar code handling & RFID, ERP system, automation tool, time management, and collaboration, to support the performance improvement. Finally, the study proposed metrics within four dimensions to validate the solution impact on the performance, including the responsiveness, reliability, asset management, and people.

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Published

2025-11-26

How to Cite

Adhie Prayogo, Curie Habiba, Ulkhaq, M. M., Dina Tauhida, & Sitompul, F. R. (2025). Exploring Logistics Process Improvement Possibility with SCOR Digital Standard and Lean Waste Analysis. Journal of Advances in Information and Industrial Technology, 7(2), 151–164. https://doi.org/10.52435/jaiit.v7i2.723

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Section

Research Article