Open AccessImproving Efficiency for Retail Warehouse Using Data Envelopment Analysis
Author(s) -
Elisa Kusrini,
Indro Prakoso,
Syarif Hidayatuloh
Publication year - 2022
Publication title -
mathematical modelling and engineering problems/mathematical modelling of engineering problems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.26
H-Index - 11
eISSN - 2369-0747
pISSN - 2369-0739
DOI - 10.18280/mmep.090132
Subject(s) - benchmarking , data envelopment analysis , productivity , warehouse , analytic hierarchy process , variable (mathematics) , order (exchange) , operations management , lead time , computer science , operations research , supply chain , economic order quantity , business , quality (philosophy) , engineering , marketing , economics , mathematics , statistics , mathematical analysis , philosophy , finance , epistemology , macroeconomics
Warehouse has an important role in supply chain management and has many complex activities that require special attention. This study aims to improve warehouse efficiency performance. Data Envelopment Analysis (DEA) method is employed to obtain the level of efficiency and benchmarking on five indicators, namely financial, productivity, utilization, quality, and cycle time along with five business processes in warehousing, i.e. receiving, put away, storage, order picking, and shipping. The decision making unit is a warehouse in four retailers in Yogyakarta province, in Indonesia. The input and output variables are selected based on the highest priority weight using the Analytical Hierarchy Process (AHP). The most important variable for receiving is productivity (receipt per man-hour), variable for put away is cycle time (put away cycle time), variable for storage is utilization (% location and cube occupied), variable for order picking is cycle time (order picking cycle time) and variable for shipping is productivity (order prepared for shipment per man-hour). The research results show that the benchmarking model with DEA can be used to increase warehouse efficiency performance by up to 22% by increasing receiving and shipping productivity, increasing storage utilization and reducing cycle time at put away and order picking.